Upload extensionsa using SD-Hub extension

.gitattributes

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extensionsa/1-sd-dynamic-thresholding/.github/FUNDING.yml

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+github: mcmonkey4eva

extensionsa/1-sd-dynamic-thresholding/.github/workflows/publish.yml

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+name: Publish to Comfy registry
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - master
+    paths:
+      - "pyproject.toml"
+
+jobs:
+  publish-node:
+    name: Publish Custom Node to registry
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+      - name: Publish Custom Node
+        uses: Comfy-Org/publish-node-action@main
+        with:
+          ## Add your own personal access token to your Github Repository secrets and reference it here.
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}

extensionsa/1-sd-dynamic-thresholding/.gitignore

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+__pycache__/

extensionsa/1-sd-dynamic-thresholding/LICENSE.txt

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+The MIT License (MIT)
+
+Copyright (c) 2023 Alex "mcmonkey" Goodwin
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

extensionsa/1-sd-dynamic-thresholding/README.md

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+# Stable Diffusion Dynamic Thresholding (CFG Scale Fix)
+
+### Concept
+
+Extension for [SwarmUI](https://github.com/mcmonkeyprojects/SwarmUI), [ComfyUI](https://github.com/comfyanonymous/ComfyUI), and [AUTOMATIC1111 Stable Diffusion WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) that enables a way to use higher CFG Scales without color issues.
+
+This works by clamping latents between steps. You can read more [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/3962) or [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/3268) or [this tweet](https://twitter.com/Birchlabs/status/1582165379832348672).
+
+--------------
+
+### Credit
+
+The core functionality of this PR was originally developed by [Birch-san](https://github.com/Birch-san) and ported to the WebUI by [dtan3847](https://github.com/dtan3847), then converted to an Auto WebUI extension and given a UI by [mcmonkey4eva](https://github.com/mcmonkey4eva), further development and research done by [mcmonkey4eva](https://github.com/mcmonkey4eva) and JDMLeverton. Ported by ComfyUI by [TwoDukes](https://github.com/TwoDukes) and [mcmonkey4eva](https://github.com/mcmonkey4eva). Ported to SwarmUI by [mcmonkey4eva](https://github.com/mcmonkey4eva).
+
+--------------
+
+### Examples
+
+![img](github/cat_demo_1.jpg)
+
+![img](github/ui.png)
+
+
+--------------
+
+### Demo Grid
+
+View at <https://sd.mcmonkey.org/dynthresh/>.
+
+![img](github/grid_preview.png)
+
+(Was generated via [this YAML config](https://gist.github.com/mcmonkey4eva/fccd29172f44424dfc0217a482c824f6) for the [Infinite Grid Generator](https://github.com/mcmonkeyprojects/sd-infinity-grid-generator-script))
+
+--------------
+
+### Installation and Usage
+
+#### SwarmUI
+
+- Supported out-of-the-box on default installations.
+    - If using a custom installation, just make sure the backend you use has this repo installed per the instructions specific to the backend as written below.
+- It's under the "Display Advanced Options" parameter checkbox.
+
+#### Auto WebUI
+
+- You must have the [AUTOMATIC1111 Stable Diffusion WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) already installed and working. Refer to that project's readme for help with that.
+- Open the WebUI, go to the `Extensions` tab
+- -EITHER- Option **A**:
+    - go to the `Available` tab with
+    - click `Load from` (with the default list)
+    - Scroll down to find `Dynamic Thresholding (CFG Scale Fix)`, or use `CTRL+F` to find it
+- -OR- Option **B**:
+    - Click on `Install from URL`
+    - Copy/paste this project's URL into the `URL for extension's git repository` textbox: `https://github.com/mcmonkeyprojects/sd-dynamic-thresholding`
+- Click `Install`
+- Restart or reload the WebUI
+- Go to txt2img or img2img
+- Check the `Enable Dynamic Thresholding (CFG Scale Fix)` box
+- Read the info on-page and set the sliders where you want em.
+- Click generate.
+
+
+#### ComfyUI
+
+- Must have [ComfyUI](https://github.com/comfyanonymous/ComfyUI) already installed and working. Refer to that project's readme for help with that.
+- -EITHER- Option **A**: (TODO: Manager install)
+- -OR- Option **B**:
+    - `cd ComfyUI/custom_nodes`
+    - `git clone https://github.com/mcmonkeyprojects/sd-dynamic-thresholding`
+    - restart ComfyUI
+    - Add node `advanced/mcmonkey/DynamicThresholdingSimple` (or `Full`)
+    - Link your model to the input, and then link the output model to your KSampler's input
+
+![img](github/comfy_node.png)
+
+--------------
+
+### Supported Auto WebUI Extensions
+
+- This can be configured within the [Infinity Grid Generator](https://github.com/mcmonkeyprojects/sd-infinity-grid-generator-script#supported-extensions) extension, see the readme of that project for details.
+
+### ComfyUI Compatibility
+
+- This would work with any variant of the `KSampler` node, including custom ones, so long as they do not totally override the internal sampling function (most don't).
+
+----------------------
+
+### Licensing pre-note:
+
+This is an open source project, provided entirely freely, for everyone to use and contribute to.
+
+If you make any changes that could benefit the community as a whole, please contribute upstream.
+
+### The short of the license is:
+
+You can do basically whatever you want, except you may not hold any developer liable for what you do with the software.
+
+### The long version of the license follows:
+
+The MIT License (MIT)
+
+Copyright (c) 2023 Alex "mcmonkey" Goodwin
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

extensionsa/1-sd-dynamic-thresholding/__init__.py

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+from . import dynthres_comfyui
+
+NODE_CLASS_MAPPINGS = {
+    "DynamicThresholdingSimple": dynthres_comfyui.DynamicThresholdingSimpleComfyNode,
+    "DynamicThresholdingFull": dynthres_comfyui.DynamicThresholdingComfyNode,
+}

extensionsa/1-sd-dynamic-thresholding/dynthres_comfyui.py

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+from .dynthres_core import DynThresh
+
+class DynamicThresholdingComfyNode:
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "mimic_scale": ("FLOAT", {"default": 7.0, "min": 0.0, "max": 100.0, "step": 0.5}),
+                "threshold_percentile": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
+                "mimic_mode": (DynThresh.Modes, ),
+                "mimic_scale_min": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.5}),
+                "cfg_mode": (DynThresh.Modes, ),
+                "cfg_scale_min": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.5}),
+                "sched_val": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
+                "separate_feature_channels": (["enable", "disable"], ),
+                "scaling_startpoint": (DynThresh.Startpoints, ),
+                "variability_measure": (DynThresh.Variabilities, ),
+                "interpolate_phi": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
+                }
+        }
+
+    RETURN_TYPES = ("MODEL",)
+    FUNCTION = "patch"
+    CATEGORY = "advanced/mcmonkey"
+
+    def patch(self, model, mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi):
+
+        dynamic_thresh = DynThresh(mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, 0, 999, separate_feature_channels == "enable", scaling_startpoint, variability_measure, interpolate_phi)
+        
+        def sampler_dyn_thresh(args):
+            input = args["input"]
+            cond = input - args["cond"]
+            uncond = input - args["uncond"]
+            cond_scale = args["cond_scale"]
+            time_step = model.model.model_sampling.timestep(args["sigma"])
+            time_step = time_step[0].item()
+            dynamic_thresh.step = 999 - time_step
+
+            if cond_scale == mimic_scale:
+                return input - (uncond + (cond - uncond) * cond_scale)
+            else:
+                return input - dynamic_thresh.dynthresh(cond, uncond, cond_scale, None)
+
+        m = model.clone()
+        m.set_model_sampler_cfg_function(sampler_dyn_thresh)
+        return (m, )
+
+class DynamicThresholdingSimpleComfyNode:
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "mimic_scale": ("FLOAT", {"default": 7.0, "min": 0.0, "max": 100.0, "step": 0.5}),
+                "threshold_percentile": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
+                }
+        }
+
+    RETURN_TYPES = ("MODEL",)
+    FUNCTION = "patch"
+    CATEGORY = "advanced/mcmonkey"
+
+    def patch(self, model, mimic_scale, threshold_percentile):
+
+        dynamic_thresh = DynThresh(mimic_scale, threshold_percentile, "CONSTANT", 0, "CONSTANT", 0, 0, 0, 999, False, "MEAN", "AD", 1)
+        
+        def sampler_dyn_thresh(args):
+            input = args["input"]
+            cond = input - args["cond"]
+            uncond = input - args["uncond"]
+            cond_scale = args["cond_scale"]
+            time_step = model.model.model_sampling.timestep(args["sigma"])
+            time_step = time_step[0].item()
+            dynamic_thresh.step = 999 - time_step
+
+            if cond_scale == mimic_scale:
+                return input - (uncond + (cond - uncond) * cond_scale)
+            else:
+                return input - dynamic_thresh.dynthresh(cond, uncond, cond_scale, None)
+
+        m = model.clone()
+        m.set_model_sampler_cfg_function(sampler_dyn_thresh)
+        return (m, )

extensionsa/1-sd-dynamic-thresholding/dynthres_core.py

@@ -0,0 +1,167 @@
+import torch, math
+
+######################### DynThresh Core #########################
+
+class DynThresh:
+
+    Modes = ["Constant", "Linear Down", "Cosine Down", "Half Cosine Down", "Linear Up", "Cosine Up", "Half Cosine Up", "Power Up", "Power Down", "Linear Repeating", "Cosine Repeating", "Sawtooth"]
+    Startpoints = ["MEAN", "ZERO"]
+    Variabilities = ["AD", "STD"]
+
+    def __init__(self, mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, experiment_mode, max_steps, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi):
+        self.mimic_scale = mimic_scale
+        self.threshold_percentile = threshold_percentile
+        self.mimic_mode = mimic_mode
+        self.cfg_mode = cfg_mode
+        self.max_steps = max_steps
+        self.cfg_scale_min = cfg_scale_min
+        self.mimic_scale_min = mimic_scale_min
+        self.experiment_mode = experiment_mode
+        self.sched_val = sched_val
+        self.sep_feat_channels = separate_feature_channels
+        self.scaling_startpoint = scaling_startpoint
+        self.variability_measure = variability_measure
+        self.interpolate_phi = interpolate_phi
+
+    def interpret_scale(self, scale, mode, min):
+        scale -= min
+        max = self.max_steps - 1
+        frac = self.step / max
+        if mode == "Constant":
+            pass
+        elif mode == "Linear Down":
+            scale *= 1.0 - frac
+        elif mode == "Half Cosine Down":
+            scale *= math.cos(frac)
+        elif mode == "Cosine Down":
+            scale *= math.cos(frac * 1.5707)
+        elif mode == "Linear Up":
+            scale *= frac
+        elif mode == "Half Cosine Up":
+            scale *= 1.0 - math.cos(frac)
+        elif mode == "Cosine Up":
+            scale *= 1.0 - math.cos(frac * 1.5707)
+        elif mode == "Power Up":
+            scale *= math.pow(frac, self.sched_val)
+        elif mode == "Power Down":
+            scale *= 1.0 - math.pow(frac, self.sched_val)
+        elif mode == "Linear Repeating":
+            portion = (frac * self.sched_val) % 1.0
+            scale *= (0.5 - portion) * 2 if portion < 0.5 else (portion - 0.5) * 2
+        elif mode == "Cosine Repeating":
+            scale *= math.cos(frac * 6.28318 * self.sched_val) * 0.5 + 0.5
+        elif mode == "Sawtooth":
+            scale *= (frac * self.sched_val) % 1.0
+        scale += min
+        return scale
+
+    def dynthresh(self, cond, uncond, cfg_scale, weights):
+        mimic_scale = self.interpret_scale(self.mimic_scale, self.mimic_mode, self.mimic_scale_min)
+        cfg_scale = self.interpret_scale(cfg_scale, self.cfg_mode, self.cfg_scale_min)
+        # uncond shape is (batch, 4, height, width)
+        conds_per_batch = cond.shape[0] / uncond.shape[0]
+        assert conds_per_batch == int(conds_per_batch), "Expected # of conds per batch to be constant across batches"
+        cond_stacked = cond.reshape((-1, int(conds_per_batch)) + uncond.shape[1:])
+
+        ### Normal first part of the CFG Scale logic, basically
+        diff = cond_stacked - uncond.unsqueeze(1)
+        if weights is not None:
+            diff = diff * weights
+        relative = diff.sum(1)
+
+        ### Get the normal result for both mimic and normal scale
+        mim_target = uncond + relative * mimic_scale
+        cfg_target = uncond + relative * cfg_scale
+        ### If we weren't doing mimic scale, we'd just return cfg_target here
+
+        ### Now recenter the values relative to their average rather than absolute, to allow scaling from average
+        mim_flattened = mim_target.flatten(2)
+        cfg_flattened = cfg_target.flatten(2)
+        mim_means = mim_flattened.mean(dim=2).unsqueeze(2)
+        cfg_means = cfg_flattened.mean(dim=2).unsqueeze(2)
+        mim_centered = mim_flattened - mim_means
+        cfg_centered = cfg_flattened - cfg_means
+
+        if self.sep_feat_channels:
+            if self.variability_measure == 'STD':
+                mim_scaleref = mim_centered.std(dim=2).unsqueeze(2)
+                cfg_scaleref = cfg_centered.std(dim=2).unsqueeze(2)
+            else: # 'AD'
+                mim_scaleref = mim_centered.abs().max(dim=2).values.unsqueeze(2)
+                cfg_scaleref = torch.quantile(cfg_centered.abs(), self.threshold_percentile, dim=2).unsqueeze(2)
+
+        else:
+            if self.variability_measure == 'STD':
+                mim_scaleref = mim_centered.std()
+                cfg_scaleref = cfg_centered.std()
+            else: # 'AD'
+                mim_scaleref = mim_centered.abs().max()
+                cfg_scaleref = torch.quantile(cfg_centered.abs(), self.threshold_percentile)
+
+        if self.scaling_startpoint == 'ZERO':
+            scaling_factor = mim_scaleref / cfg_scaleref
+            result = cfg_flattened * scaling_factor
+
+        else: # 'MEAN'
+            if self.variability_measure == 'STD':
+                cfg_renormalized = (cfg_centered / cfg_scaleref) * mim_scaleref
+            else: # 'AD'
+                ### Get the maximum value of all datapoints (with an optional threshold percentile on the uncond)
+                max_scaleref = torch.maximum(mim_scaleref, cfg_scaleref)
+                ### Clamp to the max
+                cfg_clamped = cfg_centered.clamp(-max_scaleref, max_scaleref)
+                ### Now shrink from the max to normalize and grow to the mimic scale (instead of the CFG scale)
+                cfg_renormalized = (cfg_clamped / max_scaleref) * mim_scaleref
+
+            ### Now add it back onto the averages to get into real scale again and return
+            result = cfg_renormalized + cfg_means
+
+        actual_res = result.unflatten(2, mim_target.shape[2:])
+
+        if self.interpolate_phi != 1.0:
+            actual_res = actual_res * self.interpolate_phi + cfg_target * (1.0 - self.interpolate_phi)
+
+        if self.experiment_mode == 1:
+            num = actual_res.cpu().numpy()
+            for y in range(0, 64):
+                for x in range (0, 64):
+                    if num[0][0][y][x] > 1.0:
+                        num[0][1][y][x] *= 0.5
+                    if num[0][1][y][x] > 1.0:
+                        num[0][1][y][x] *= 0.5
+                    if num[0][2][y][x] > 1.5:
+                        num[0][2][y][x] *= 0.5
+            actual_res = torch.from_numpy(num).to(device=uncond.device)
+        elif self.experiment_mode == 2:
+            num = actual_res.cpu().numpy()
+            for y in range(0, 64):
+                for x in range (0, 64):
+                    over_scale = False
+                    for z in range(0, 4):
+                        if abs(num[0][z][y][x]) > 1.5:
+                            over_scale = True
+                    if over_scale:
+                        for z in range(0, 4):
+                            num[0][z][y][x] *= 0.7
+            actual_res = torch.from_numpy(num).to(device=uncond.device)
+        elif self.experiment_mode == 3:
+            coefs = torch.tensor([
+                #  R       G        B      W
+                [0.298,   0.207,  0.208, 0.0], # L1
+                [0.187,   0.286,  0.173, 0.0], # L2
+                [-0.158,  0.189,  0.264, 0.0], # L3
+                [-0.184, -0.271, -0.473, 1.0], # L4
+            ], device=uncond.device)
+            res_rgb = torch.einsum("laxy,ab -> lbxy", actual_res, coefs)
+            max_r, max_g, max_b, max_w = res_rgb[0][0].max(), res_rgb[0][1].max(), res_rgb[0][2].max(), res_rgb[0][3].max()
+            max_rgb = max(max_r, max_g, max_b)
+            print(f"test max = r={max_r}, g={max_g}, b={max_b}, w={max_w}, rgb={max_rgb}")
+            if self.step / (self.max_steps - 1) > 0.2:
+                if max_rgb < 2.0 and max_w < 3.0:
+                    res_rgb /= max_rgb / 2.4
+            else:
+                if max_rgb > 2.4 and max_w > 3.0:
+                    res_rgb /= max_rgb / 2.4
+            actual_res = torch.einsum("laxy,ab -> lbxy", res_rgb, coefs.inverse())
+
+        return actual_res

extensionsa/1-sd-dynamic-thresholding/dynthres_unipc.py

@@ -0,0 +1,111 @@
+import gradio as gr
+import torch
+import math
+import traceback
+from modules import shared
+try:
+    from modules.models.diffusion import uni_pc
+except Exception as e:
+    from modules import unipc as uni_pc
+
+######################### UniPC Implementation logic #########################
+
+# The majority of this is straight from modules.models/diffusion/uni_pc/sampler.py
+# Unfortunately that's not an easy middle-injection point, so, just copypasta'd it all
+# It's like they designed it to intentionally be as difficult to inject into as possible :(
+# (It has hooks but not in useful locations)
+# I stripped the original comments for brevity.
+# Some never-used code (scheduler modes, noise modes, guidance modes) have been removed as well for brevity.
+# The actual impl comes down to just the last line in particular, and the `before_sample` insert to track step count.
+
+class CustomUniPCSampler(uni_pc.sampler.UniPCSampler):
+    def __init__(self, model, **kwargs):
+        super().__init__(model, *kwargs)
+    @torch.no_grad()
+    def sample(self, S, batch_size, shape, conditioning=None, callback=None, normals_sequence=None, img_callback=None,
+               quantize_x0=False, eta=0., mask=None, x0=None, temperature=1., noise_dropout=0., score_corrector=None,
+               corrector_kwargs=None, verbose=True, x_T=None, log_every_t=100, unconditional_guidance_scale=1.,
+               unconditional_conditioning=None, **kwargs):
+        if conditioning is not None:
+            if isinstance(conditioning, dict):
+                ctmp = conditioning[list(conditioning.keys())[0]]
+                while isinstance(ctmp, list): ctmp = ctmp[0]
+                cbs = ctmp.shape[0]
+                if cbs != batch_size:
+                    print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
+
+            elif isinstance(conditioning, list):
+                for ctmp in conditioning:
+                    if ctmp.shape[0] != batch_size:
+                        print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
+            else:
+                if conditioning.shape[0] != batch_size:
+                    print(f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}")
+        C, H, W = shape
+        size = (batch_size, C, H, W)
+        device = self.model.betas.device
+        if x_T is None:
+            img = torch.randn(size, device=device)
+        else:
+            img = x_T
+        ns = uni_pc.uni_pc.NoiseScheduleVP('discrete', alphas_cumprod=self.alphas_cumprod)
+        model_type = "v" if self.model.parameterization == "v" else "noise"
+        model_fn = CustomUniPC_model_wrapper(lambda x, t, c: self.model.apply_model(x, t, c), ns, model_type=model_type, guidance_scale=unconditional_guidance_scale, dt_data=self.main_class)
+        self.main_class.step = 0
+        def before_sample(x, t, cond, uncond):
+            self.main_class.step += 1
+            return self.before_sample(x, t, cond, uncond)
+        uni_pc_inst = uni_pc.uni_pc.UniPC(model_fn, ns, predict_x0=True, thresholding=False, variant=shared.opts.uni_pc_variant, condition=conditioning, unconditional_condition=unconditional_conditioning, before_sample=before_sample, after_sample=self.after_sample, after_update=self.after_update)
+        x = uni_pc_inst.sample(img, steps=S, skip_type=shared.opts.uni_pc_skip_type, method="multistep", order=shared.opts.uni_pc_order, lower_order_final=shared.opts.uni_pc_lower_order_final)
+        return x.to(device), None
+
+def CustomUniPC_model_wrapper(model, noise_schedule, model_type="noise", model_kwargs={}, guidance_scale=1.0, dt_data=None):
+    def expand_dims(v, dims):
+        return v[(...,) + (None,)*(dims - 1)]
+    def get_model_input_time(t_continuous):
+        return (t_continuous - 1. / noise_schedule.total_N) * 1000.
+    def noise_pred_fn(x, t_continuous, cond=None):
+        if t_continuous.reshape((-1,)).shape[0] == 1:
+            t_continuous = t_continuous.expand((x.shape[0]))
+        t_input = get_model_input_time(t_continuous)
+        if cond is None:
+            output = model(x, t_input, None, **model_kwargs)
+        else:
+            output = model(x, t_input, cond, **model_kwargs)
+        if model_type == "noise":
+            return output
+        elif model_type == "v":
+            alpha_t, sigma_t = noise_schedule.marginal_alpha(t_continuous), noise_schedule.marginal_std(t_continuous)
+            dims = x.dim()
+            return expand_dims(alpha_t, dims) * output + expand_dims(sigma_t, dims) * x
+    def model_fn(x, t_continuous, condition, unconditional_condition):
+        if t_continuous.reshape((-1,)).shape[0] == 1:
+            t_continuous = t_continuous.expand((x.shape[0]))
+        if guidance_scale == 1. or unconditional_condition is None:
+            return noise_pred_fn(x, t_continuous, cond=condition)
+        else:
+            x_in = torch.cat([x] * 2)
+            t_in = torch.cat([t_continuous] * 2)
+            if isinstance(condition, dict):
+                assert isinstance(unconditional_condition, dict)
+                c_in = dict()
+                for k in condition:
+                    if isinstance(condition[k], list):
+                        c_in[k] = [torch.cat([
+                            unconditional_condition[k][i],
+                            condition[k][i]]) for i in range(len(condition[k]))]
+                    else:
+                        c_in[k] = torch.cat([
+                            unconditional_condition[k],
+                            condition[k]])
+            elif isinstance(condition, list):
+                c_in = list()
+                assert isinstance(unconditional_condition, list)
+                for i in range(len(condition)):
+                    c_in.append(torch.cat([unconditional_condition[i], condition[i]]))
+            else:
+                c_in = torch.cat([unconditional_condition, condition])
+            noise_uncond, noise = noise_pred_fn(x_in, t_in, cond=c_in).chunk(2)
+            #return noise_uncond + guidance_scale * (noise - noise_uncond)
+            return dt_data.dynthresh(noise, noise_uncond, guidance_scale, None)
+    return model_fn

extensionsa/1-sd-dynamic-thresholding/javascript/active.js

@@ -0,0 +1,68 @@
+let dynthres_update_enabled = function() {
+    return Array.from(arguments);
+};
+
+(function(){
+    let accordions = {};
+    let enabled = {};
+    onUiUpdate(() => {
+        let accordion_id_prefix = "#dynthres_";
+        let extension_checkbox_class = ".dynthres-enabled";
+
+        dynthres_update_enabled = function() {
+            let res = Array.from(arguments);
+            let tabname = res[1] ? "img2img" : "txt2img";
+
+            let checkbox = accordions[tabname]?.querySelector(extension_checkbox_class + ' input');
+            checkbox?.dispatchEvent(new Event('change'));
+
+            return res;
+        };
+
+        function attachEnabledButtonListener(checkbox, accordion) {
+            let span = accordion.querySelector('.label-wrap span');
+            let badge = document.createElement('input');
+            badge.type = "checkbox";
+            badge.checked = checkbox.checked;
+            badge.addEventListener('click', (e) => {
+                checkbox.checked = !checkbox.checked;
+                badge.checked = checkbox.checked;
+                checkbox.dispatchEvent(new Event('change'));
+                e.stopPropagation();
+            });
+
+            badge.className = checkbox.className;
+            badge.classList.add('primary');
+            span.insertBefore(badge, span.firstChild);
+            let space = document.createElement('span');
+            space.innerHTML = " ";
+            span.insertBefore(space, badge.nextSibling);
+
+            checkbox.addEventListener('change', () => {
+                let badge = accordion.querySelector('.label-wrap span input');
+                badge.checked = checkbox.checked;
+            });
+            checkbox.parentNode.style.display = "none";
+        }
+
+        if (Object.keys(accordions).length < 2) {
+            let accordion = gradioApp().querySelector(accordion_id_prefix + 'txt2img');
+            if (accordion) {
+                accordions.txt2img = accordion;
+            }
+            accordion = gradioApp().querySelector(accordion_id_prefix + 'img2img');
+            if (accordion) {
+                accordions.img2img = accordion;
+            }
+        }
+
+        if (Object.keys(accordions).length > 0 && accordions.txt2img && !enabled.txt2img) {
+            enabled.txt2img = accordions.txt2img.querySelector(extension_checkbox_class + ' input');
+            attachEnabledButtonListener(enabled.txt2img, accordions.txt2img);
+        }
+        if (Object.keys(accordions).length > 0 && accordions.img2img && !enabled.img2img) {
+            enabled.img2img = accordions.img2img.querySelector(extension_checkbox_class + ' input');
+            attachEnabledButtonListener(enabled.img2img, accordions.img2img);
+        }
+    });
+})();

extensionsa/1-sd-dynamic-thresholding/pyproject.toml

@@ -0,0 +1,13 @@
+[project]
+name = "sd-dynamic-thresholding"
+description = "Adds nodes for Dynamic Thresholding, CFG scheduling, and related techniques"
+version = "1.0.1"
+license = { file = "LICENSE.txt" }
+
+[project.urls]
+Repository = "https://github.com/mcmonkeyprojects/sd-dynamic-thresholding"
+
+[tool.comfy]
+PublisherId = "mcmonkey"
+DisplayName = "Dynamic Thresholding"
+Icon = ""

extensionsa/1-sd-dynamic-thresholding/scripts/dynamic_thresholding.py

@@ -0,0 +1,270 @@
+##################
+# Stable Diffusion Dynamic Thresholding (CFG Scale Fix)
+#
+# Author: Alex 'mcmonkey' Goodwin
+# GitHub URL: https://github.com/mcmonkeyprojects/sd-dynamic-thresholding
+# Created: 2022/01/26
+# Last updated: 2023/01/30
+#
+# For usage help, view the README.md file in the extension root, or via the GitHub page.
+#
+##################
+
+import gradio as gr
+import torch, traceback
+import dynthres_core
+from modules import scripts, script_callbacks, sd_samplers, sd_samplers_compvis, sd_samplers_common
+try:
+    import dynthres_unipc
+except Exception as e:
+    print(f"\n\n======\nError! UniPC sampler support failed to load! Is your WebUI up to date?\n(Error: {e})\n======")
+try:
+    from modules.sd_samplers_kdiffusion import CFGDenoiserKDiffusion as cfgdenoisekdiff
+    IS_AUTO_16 = True
+except Exception as e:
+    print(f"\n\n======\nWarning! Using legacy KDiff version! Is your WebUI up to date?\n======")
+    from modules.sd_samplers_kdiffusion import CFGDenoiser as cfgdenoisekdiff
+    IS_AUTO_16 = False
+
+DISABLE_VISIBILITY = True
+
+######################### Data values #########################
+MODES_WITH_VALUE = ["Power Up", "Power Down", "Linear Repeating", "Cosine Repeating", "Sawtooth"]
+
+######################### Script class entrypoint #########################
+class Script(scripts.Script):
+
+    def title(self):
+        return "Dynamic Thresholding (CFG Scale Fix)"
+
+    def show(self, is_img2img):
+        return scripts.AlwaysVisible
+
+    def ui(self, is_img2img):
+        def vis_change(is_vis):
+            return {"visible": is_vis, "__type__": "update"}
+        # "Dynamic Thresholding (CFG Scale Fix)"
+        dtrue = gr.Checkbox(value=True, visible=False)
+        dfalse = gr.Checkbox(value=False, visible=False)
+        with gr.Accordion("Dynamic Thresholding (CFG Scale Fix)", open=False, elem_id="dynthres_" + ("img2img" if is_img2img else "txt2img")):
+            with gr.Row():
+                enabled = gr.Checkbox(value=False, label="Enable Dynamic Thresholding (CFG Scale Fix)", elem_classes=["dynthres-enabled"], elem_id='dynthres_enabled')
+            with gr.Group():
+                gr.HTML(value=f"View <a style=\"border-bottom: 1px #00ffff dotted;\" href=\"https://github.com/mcmonkeyprojects/sd-dynamic-thresholding/wiki/Usage-Tips\">the wiki for usage tips.</a><br><br>", elem_id='dynthres_wiki_link')
+                mimic_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='Mimic CFG Scale', value=7.0, elem_id='dynthres_mimic_scale')
+                with gr.Accordion("Advanced Options", open=False, elem_id='dynthres_advanced_opts'):
+                    with gr.Row():
+                        threshold_percentile = gr.Slider(minimum=90.0, value=100.0, maximum=100.0, step=0.05, label='Top percentile of latents to clamp', elem_id='dynthres_threshold_percentile')
+                        interpolate_phi = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="Interpolate Phi", value=1.0, elem_id='dynthres_interpolate_phi')
+                    with gr.Row():
+                        mimic_mode = gr.Dropdown(dynthres_core.DynThresh.Modes, value="Constant", label="Mimic Scale Scheduler", elem_id='dynthres_mimic_mode')
+                        cfg_mode = gr.Dropdown(dynthres_core.DynThresh.Modes, value="Constant", label="CFG Scale Scheduler", elem_id='dynthres_cfg_mode')
+                    mimic_scale_min = gr.Slider(minimum=0.0, maximum=30.0, step=0.5, visible=DISABLE_VISIBILITY, label="Minimum value of the Mimic Scale Scheduler", elem_id='dynthres_mimic_scale_min')
+                    cfg_scale_min = gr.Slider(minimum=0.0, maximum=30.0, step=0.5, visible=DISABLE_VISIBILITY, label="Minimum value of the CFG Scale Scheduler", elem_id='dynthres_cfg_scale_min')
+                    sched_val = gr.Slider(minimum=0.0, maximum=40.0, step=0.5, value=4.0, visible=DISABLE_VISIBILITY, label="Scheduler Value", info="Value unique to the scheduler mode - for Power Up/Down, this is the power. For Linear/Cosine Repeating, this is the number of repeats per image.", elem_id='dynthres_sched_val')
+                    with gr.Row():
+                        separate_feature_channels = gr.Checkbox(value=True, label="Separate Feature Channels", elem_id='dynthres_separate_feature_channels')
+                        scaling_startpoint = gr.Radio(["ZERO", "MEAN"], value="MEAN", label="Scaling Startpoint")
+                        variability_measure = gr.Radio(["STD", "AD"], value="AD", label="Variability Measure")
+        def should_show_scheduler_value(cfg_mode, mimic_mode):
+            sched_vis = cfg_mode in MODES_WITH_VALUE or mimic_mode in MODES_WITH_VALUE or DISABLE_VISIBILITY
+            return vis_change(sched_vis), vis_change(mimic_mode != "Constant" or DISABLE_VISIBILITY), vis_change(cfg_mode != "Constant" or DISABLE_VISIBILITY)
+        cfg_mode.change(should_show_scheduler_value, inputs=[cfg_mode, mimic_mode], outputs=[sched_val, mimic_scale_min, cfg_scale_min])
+        mimic_mode.change(should_show_scheduler_value, inputs=[cfg_mode, mimic_mode], outputs=[sched_val, mimic_scale_min, cfg_scale_min])
+        enabled.change(
+            _js="dynthres_update_enabled",
+            fn=None,
+            inputs=[enabled, dtrue if is_img2img else dfalse],
+            show_progress = False)
+        self.infotext_fields = (
+            (enabled, lambda d: gr.Checkbox.update(value="Dynamic thresholding enabled" in d)),
+            (mimic_scale, "Mimic scale"),
+            (separate_feature_channels, "Separate Feature Channels"),
+            (scaling_startpoint, lambda d: gr.Radio.update(value=d.get("Scaling Startpoint", "MEAN"))),
+            (variability_measure, lambda d: gr.Radio.update(value=d.get("Variability Measure", "AD"))),
+            (interpolate_phi, "Interpolate Phi"),
+            (threshold_percentile, "Threshold percentile"),
+            (mimic_scale_min, "Mimic scale minimum"),
+            (mimic_mode, lambda d: gr.Dropdown.update(value=d.get("Mimic mode", "Constant"))),
+            (cfg_mode, lambda d: gr.Dropdown.update(value=d.get("CFG mode", "Constant"))),
+            (cfg_scale_min, "CFG scale minimum"),
+            (sched_val, "Scheduler value"))
+        return [enabled, mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi]
+
+    last_id = 0
+
+    def process_batch(self, p, enabled, mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi, batch_number, prompts, seeds, subseeds):
+        enabled = getattr(p, 'dynthres_enabled', enabled)
+        if not enabled:
+            return
+        orig_sampler_name = p.sampler_name
+        orig_latent_sampler_name = getattr(p, 'latent_sampler', None)
+        if orig_sampler_name in ["DDIM", "PLMS"]:
+            raise RuntimeError(f"Cannot use sampler {orig_sampler_name} with Dynamic Thresholding")
+        if orig_latent_sampler_name in ["DDIM", "PLMS"]:
+            raise RuntimeError(f"Cannot use secondary sampler {orig_latent_sampler_name} with Dynamic Thresholding")
+        if 'UniPC' in (orig_sampler_name, orig_latent_sampler_name) and p.enable_hr:
+            raise RuntimeError(f"UniPC does not support Hires Fix. Auto WebUI silently swaps to DDIM for this, which DynThresh does not support. Please swap to a sampler capable of img2img processing for HR Fix to work.")
+        mimic_scale = getattr(p, 'dynthres_mimic_scale', mimic_scale)
+        separate_feature_channels = getattr(p, 'dynthres_separate_feature_channels', separate_feature_channels)
+        scaling_startpoint = getattr(p, 'dynthres_scaling_startpoint', scaling_startpoint)
+        variability_measure = getattr(p, 'dynthres_variability_measure', variability_measure)
+        interpolate_phi = getattr(p, 'dynthres_interpolate_phi', interpolate_phi)
+        threshold_percentile = getattr(p, 'dynthres_threshold_percentile', threshold_percentile)
+        mimic_mode = getattr(p, 'dynthres_mimic_mode', mimic_mode)
+        mimic_scale_min = getattr(p, 'dynthres_mimic_scale_min', mimic_scale_min)
+        cfg_mode = getattr(p, 'dynthres_cfg_mode', cfg_mode)
+        cfg_scale_min = getattr(p, 'dynthres_cfg_scale_min', cfg_scale_min)
+        experiment_mode = getattr(p, 'dynthres_experiment_mode', 0)
+        sched_val = getattr(p, 'dynthres_scheduler_val', sched_val)
+        p.extra_generation_params["Dynamic thresholding enabled"] = True
+        p.extra_generation_params["Mimic scale"] = mimic_scale
+        p.extra_generation_params["Separate Feature Channels"] = separate_feature_channels
+        p.extra_generation_params["Scaling Startpoint"] = scaling_startpoint
+        p.extra_generation_params["Variability Measure"] = variability_measure
+        p.extra_generation_params["Interpolate Phi"] = interpolate_phi
+        p.extra_generation_params["Threshold percentile"] = threshold_percentile
+        p.extra_generation_params["Sampler"] = orig_sampler_name
+        if mimic_mode != "Constant":
+            p.extra_generation_params["Mimic mode"] = mimic_mode
+            p.extra_generation_params["Mimic scale minimum"] = mimic_scale_min
+        if cfg_mode != "Constant":
+            p.extra_generation_params["CFG mode"] = cfg_mode
+            p.extra_generation_params["CFG scale minimum"] = cfg_scale_min
+        if cfg_mode in MODES_WITH_VALUE or mimic_mode in MODES_WITH_VALUE:
+            p.extra_generation_params["Scheduler value"] = sched_val
+        # Note: the ID number is to protect the edge case of multiple simultaneous runs with different settings
+        Script.last_id += 1
+        # Percentage to portion
+        threshold_percentile *= 0.01
+
+        def make_sampler(orig_sampler_name):
+            fixed_sampler_name = f"{orig_sampler_name}_dynthres{Script.last_id}"
+
+            # Make a placeholder sampler
+            sampler = sd_samplers.all_samplers_map[orig_sampler_name]
+            dt_data = dynthres_core.DynThresh(mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, experiment_mode, p.steps, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi)
+            if orig_sampler_name == "UniPC":
+                def unipc_constructor(model):
+                    return CustomVanillaSDSampler(dynthres_unipc.CustomUniPCSampler, model, dt_data)
+                new_sampler = sd_samplers_common.SamplerData(fixed_sampler_name, unipc_constructor, sampler.aliases, sampler.options)
+            else:
+                def new_constructor(model):
+                    result = sampler.constructor(model)
+                    cfg = CustomCFGDenoiser(result if IS_AUTO_16 else result.model_wrap_cfg.inner_model, dt_data)
+                    result.model_wrap_cfg = cfg
+                    return result
+                new_sampler = sd_samplers_common.SamplerData(fixed_sampler_name, new_constructor, sampler.aliases, sampler.options)
+            return fixed_sampler_name, new_sampler
+
+        # Apply for usage
+        p.orig_sampler_name = orig_sampler_name
+        p.orig_latent_sampler_name = orig_latent_sampler_name
+        p.fixed_samplers = []
+
+        if orig_latent_sampler_name:
+            latent_sampler_name, latent_sampler = make_sampler(orig_latent_sampler_name)
+            sd_samplers.all_samplers_map[latent_sampler_name] = latent_sampler
+            p.fixed_samplers.append(latent_sampler_name)
+            p.latent_sampler = latent_sampler_name
+
+        if orig_sampler_name != orig_latent_sampler_name:
+            p.sampler_name, new_sampler = make_sampler(orig_sampler_name)
+            sd_samplers.all_samplers_map[p.sampler_name] = new_sampler
+            p.fixed_samplers.append(p.sampler_name)
+        else:
+            p.sampler_name = p.latent_sampler
+
+        if p.sampler is not None:
+            p.sampler = sd_samplers.create_sampler(p.sampler_name, p.sd_model)
+
+    def postprocess_batch(self, p, enabled, mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi, batch_number, images):
+        if not enabled or not hasattr(p, 'orig_sampler_name'):
+            return
+        p.sampler_name = p.orig_sampler_name
+        if p.orig_latent_sampler_name:
+            p.latent_sampler = p.orig_latent_sampler_name
+        for added_sampler in p.fixed_samplers:
+            del sd_samplers.all_samplers_map[added_sampler]
+        del p.fixed_samplers
+        del p.orig_sampler_name
+        del p.orig_latent_sampler_name
+
+######################### CompVis Implementation logic #########################
+
+class CustomVanillaSDSampler(sd_samplers_compvis.VanillaStableDiffusionSampler):
+    def __init__(self, constructor, sd_model, dt_data):
+        super().__init__(constructor, sd_model)
+        self.sampler.main_class = dt_data
+
+######################### K-Diffusion Implementation logic #########################
+
+class CustomCFGDenoiser(cfgdenoisekdiff):
+    def __init__(self, model, dt_data):
+        super().__init__(model)
+        self.main_class = dt_data
+
+    def combine_denoised(self, x_out, conds_list, uncond, cond_scale):
+        if isinstance(uncond, dict) and 'crossattn' in uncond:
+            uncond = uncond['crossattn']
+        denoised_uncond = x_out[-uncond.shape[0]:]
+        # conds_list shape is (batch, cond, 2)
+        weights = torch.tensor(conds_list, device=uncond.device).select(2, 1)
+        weights = weights.reshape(*weights.shape, 1, 1, 1)
+        self.main_class.step = self.step
+        if hasattr(self, 'total_steps'):
+            self.main_class.max_steps = self.total_steps
+
+        if self.main_class.experiment_mode >= 4 and self.main_class.experiment_mode <= 5:
+            # https://arxiv.org/pdf/2305.08891.pdf "Rescale CFG". It's not good, but if you want to test it, just set experiment_mode = 4 + phi.
+            denoised = torch.clone(denoised_uncond)
+            fi = self.main_class.experiment_mode - 4.0
+            for i, conds in enumerate(conds_list):
+                for cond_index, weight in conds:
+                    xcfg = (denoised_uncond[i] + (x_out[cond_index] - denoised_uncond[i]) * (cond_scale * weight))
+                    xrescaled = xcfg * (torch.std(x_out[cond_index]) / torch.std(xcfg))
+                    xfinal = fi * xrescaled + (1.0 - fi) * xcfg
+                    denoised[i] = xfinal
+            return denoised
+
+        return self.main_class.dynthresh(x_out[:-uncond.shape[0]], denoised_uncond, cond_scale, weights)
+
+######################### XYZ Plot Script Support logic #########################
+
+def make_axis_options():
+    xyz_grid = [x for x in scripts.scripts_data if x.script_class.__module__ in ("xyz_grid.py", "scripts.xyz_grid")][0].module
+    def apply_mimic_scale(p, x, xs):
+        if x != 0:
+            setattr(p, "dynthres_enabled", True)
+            setattr(p, "dynthres_mimic_scale", x)
+        else:
+            setattr(p, "dynthres_enabled", False)
+    def confirm_scheduler(p, xs):
+        for x in xs:
+            if x not in dynthres_core.DynThresh.Modes:
+                raise RuntimeError(f"Unknown Scheduler: {x}")
+    extra_axis_options = [
+        xyz_grid.AxisOption("[DynThres] Mimic Scale", float, apply_mimic_scale),
+        xyz_grid.AxisOption("[DynThres] Separate Feature Channels", int,
+                            xyz_grid.apply_field("dynthres_separate_feature_channels")),
+        xyz_grid.AxisOption("[DynThres] Scaling Startpoint", str, xyz_grid.apply_field("dynthres_scaling_startpoint"), choices=lambda:['ZERO', 'MEAN']),
+        xyz_grid.AxisOption("[DynThres] Variability Measure", str, xyz_grid.apply_field("dynthres_variability_measure"), choices=lambda:['STD', 'AD']),
+        xyz_grid.AxisOption("[DynThres] Interpolate Phi", float, xyz_grid.apply_field("dynthres_interpolate_phi")),
+        xyz_grid.AxisOption("[DynThres] Threshold Percentile", float, xyz_grid.apply_field("dynthres_threshold_percentile")),
+        xyz_grid.AxisOption("[DynThres] Mimic Scheduler", str, xyz_grid.apply_field("dynthres_mimic_mode"), confirm=confirm_scheduler, choices=lambda: dynthres_core.DynThresh.Modes),
+        xyz_grid.AxisOption("[DynThres] Mimic minimum", float, xyz_grid.apply_field("dynthres_mimic_scale_min")),
+        xyz_grid.AxisOption("[DynThres] CFG Scheduler", str, xyz_grid.apply_field("dynthres_cfg_mode"), confirm=confirm_scheduler, choices=lambda: dynthres_core.DynThresh.Modes),
+        xyz_grid.AxisOption("[DynThres] CFG minimum", float, xyz_grid.apply_field("dynthres_cfg_scale_min")),
+        xyz_grid.AxisOption("[DynThres] Scheduler value", float, xyz_grid.apply_field("dynthres_scheduler_val"))
+    ]
+    if not any("[DynThres]" in x.label for x in xyz_grid.axis_options):
+        xyz_grid.axis_options.extend(extra_axis_options)
+
+def callback_before_ui():
+    try:
+        make_axis_options()
+    except Exception as e:
+        traceback.print_exc()
+        print(f"Failed to add support for X/Y/Z Plot Script because: {e}")
+
+script_callbacks.on_before_ui(callback_before_ui)

extensionsa/2-sd-webui-reactor/.github/ISSUE_TEMPLATE/bug_report.yml

@@ -0,0 +1,58 @@
+name: Bug Report
+description: You think somethings is broken
+labels: ["bug", "new"]
+
+body:
+  - type: checkboxes
+    attributes:
+      label: First, confirm
+      description: Make sure you use the latest version of the ReActor extension and you have already searched to see if an issue already exists for the bug you encountered before you create a new Issue.
+      options:
+        - label: I have read the [instruction](https://github.com/Gourieff/sd-webui-reactor/blob/main/README.md) carefully
+          required: true
+        - label: I have searched the existing issues
+          required: true
+        - label: I have updated the extension to the latest version
+          required: true
+  - type: markdown
+    attributes:
+      value: |
+        *Please fill this form with as much information as possible and *provide screenshots if possible**
+  - type: textarea
+    id: what-did
+    attributes:
+      label: What happened?
+      description: Tell what happened in a very clear and simple way
+    validations:
+      required: true
+  - type: textarea
+    id: steps
+    attributes:
+      label: Steps to reproduce the problem
+      description: Please provide with precise step by step instructions on how to reproduce the bug
+      value: |
+        1. Go to .... 
+        2. Press ....
+        3. ...
+    validations:
+      required: true
+  - type: textarea
+    id: sysinfo
+    attributes:
+      label: Sysinfo
+      description: Describe your platform. OS, browser, GPU, what SD WebUI you use, what version and what extensions are also enabled. If you use A1111 you can generate "System info file" (Settings -> Sysinfo) and put it here.
+    validations:
+      required: true
+  - type: textarea
+    id: logs
+    attributes:
+      label: Relevant console log
+      description: Please provide cmd/terminal logs from the moment you started UI to the momemt you got an error. This will be automatically formatted into code, so no need for backticks.
+      render: Shell
+    validations:
+      required: true
+  - type: textarea
+    id: misc
+    attributes:
+      label: Additional information
+      description: Please provide with any relevant additional info or context.

extensionsa/2-sd-webui-reactor/.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,5 @@
+blank_issues_enabled: false
+contact_links:
+  - name: ReActor Extension Community Support
+    url: https://github.com/Gourieff/sd-webui-reactor/discussions
+    about: Please ask and answer questions here.

extensionsa/2-sd-webui-reactor/.github/ISSUE_TEMPLATE/feature_request.yml

@@ -0,0 +1,16 @@
+name: Feature request
+description: Suggest an idea for this project
+title: "[Feature]: "
+labels: ["enhancement", "new"]
+
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Feature description
+      description: Describe the feature in a clear and simple way
+      value: 
+  - type: markdown
+    attributes:
+      value: |
+        The best way to propose an idea is to start a new discussion via the [Discussions](https://github.com/Gourieff/sd-webui-reactor/discussions) section (choose the "Idea" category)

extensionsa/2-sd-webui-reactor/.gitignore

@@ -0,0 +1,10 @@
+__pycache__/
+*.py[cod]
+*$py.class
+*.pyc
+
+.vscode/
+
+example
+*.txt
+!requirements.txt

extensionsa/2-sd-webui-reactor/API.md

@@ -0,0 +1,85 @@
+# <div align="center">ReActor Extension API</div>
+
+<div align="center">
+
+[Built-in SD WebUI API](#built-in-sd-webui-api) | [External ReActor API](#external-reactor-api)
+
+---
+</div>
+
+Gourieff's **ReActor** SD WebUI Extension allows to operate via API: both built-in and external (POST and GET requests).
+
+
+## Built-in SD WebUI API
+
+This API is actual if you use Automatic1111 stable-diffusion-webui.
+
+First of all - check the [SD Web API Wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/API) for how to use the API.
+
+* Call `requests.get(url=f'{address}/sdapi/v1/script-info')` to find the args that ReActor needs;
+* Define ReActor script args and add like this `"alwayson_scripts": {"reactor":{"args":args}}` in the payload;
+* Call the API. 
+
+You can find the [full usage example](./example/api_example.py) with all the available parameters and discriptions in the "example" folder.
+
+## External ReActor API
+
+ReActor extension supports for external calls via POST or GET requests while your SD WebUI server is working.
+
+> :warning: Source and Target images must be "base64".
+
+Example:
+
+```
+curl -X POST \
+	'http://127.0.0.1:7860/reactor/image' \
+    -H 'accept: application/json' \
+    -H 'Content-Type: application/json' \
+    -d '{
+    "source_image": "data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABQAAD/7g...",
+    "target_image": "data:image/png;base64,/9j/4QAYRXhpZgAASUkqAAgAAAAAAAAAAAAAAP/sABFEdWNreQABAAQAAABCAAD/7g...",
+    "source_faces_index": [0],
+    "face_index": [0],
+    "upscaler": "4x_NMKD-Siax_200k",
+    "scale": 2,
+    "upscale_visibility": 1,
+    "face_restorer": "CodeFormer",
+    "restorer_visibility": 1,
+    "restore_first": 1,
+    "model": "inswapper_128.onnx",
+    "gender_source": 0,
+    "gender_target": 0,
+    "save_to_file": 0,
+    "result_file_path": "",
+    "device": "CUDA",
+    "mask_face": 1,
+    "select_source": 1,
+    "face_model": "elena.safetensors",
+    "source_folder": "C:/faces",
+    "random_image": 1,
+    "upscale_force": 1
+	}'
+```
+
+* Set `"upscaler"` to `"None"` and `"scale"` to `1` if you don't need to upscale;
+* Set `"save_to_file"` to `1` if you need to save result to a file;
+* `"result_file_path"` is set to the `"outputs/api"` folder by default (please, create the folder beforehand to avoid any errors) with a timestamped filename; (output_YYYY-MM-DD_hh-mm-ss), you can set any specific path, e.g. `"C:/stable-diffusion-webui/outputs/api/output.png"`;
+* Set `"mask_face"` to `1` if you want ReActor to mask the face or to `0` if want ReActor to create a bbox around the face;
+* Set `"select_source"` to: 0 - Image, 1 - Face Model, 2 - Source Folder;
+* Set `"face_model"` to the face model file you want to choose if you set `"select_source": 1`;
+* Set `"source_folder"` to the path with source images (with faces you need as the results) if you set `"select_source": 2`;
+* Set `"random_image"` to `1` if want ReActor to choose a random image from the path of `"source_folder"`;
+* Set `"upscale_force"` to `1` if you want ReActor to upscale the image even if no face found.
+
+You can find full usage examples with all the available parameters in the "example" folder: [cURL](./example/api_external.curl), [JSON](./example/api_external.json).
+
+As a result you recieve a "base64" image:
+
+```
+{"image":"iVBORw0KGgoAAAANSUhEUgAABlAAAARQCAIAAAAdiYuqAAEAAElEQVR4nOz9+ZMlSXImBn6qau4vIjKzzr5wzwBCDrm/7f+/K7IHV3ZkhUIuyZHlkBhiMGig0Y0..."}
+```
+
+A list of available models can be seen by GET:
+* http://127.0.0.1:7860/reactor/models
+* http://127.0.0.1:7860/reactor/upscalers
+* http://127.0.0.1:7860/reactor/facemodels

extensionsa/2-sd-webui-reactor/LICENSE

@@ -0,0 +1,661 @@
+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+                            Preamble
+
+  The GNU Affero General Public License is a free, copyleft license for
+software and other kinds of works, specifically designed to ensure
+cooperation with the community in the case of network server software.
+
+  The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works.  By contrast,
+our General Public Licenses are intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users.
+
+  When we speak of free software, we are referring to freedom, not
+price.  Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
+them if you wish), that you receive source code or can get it if you
+want it, that you can change the software or use pieces of it in new
+free programs, and that you know you can do these things.
+
+  Developers that use our General Public Licenses protect your rights
+with two steps: (1) assert copyright on the software, and (2) offer
+you this License which gives you legal permission to copy, distribute
+and/or modify the software.
+
+  A secondary benefit of defending all users' freedom is that
+improvements made in alternate versions of the program, if they
+receive widespread use, become available for other developers to
+incorporate.  Many developers of free software are heartened and
+encouraged by the resulting cooperation.  However, in the case of
+software used on network servers, this result may fail to come about.
+The GNU General Public License permits making a modified version and
+letting the public access it on a server without ever releasing its
+source code to the public.
+
+  The GNU Affero General Public License is designed specifically to
+ensure that, in such cases, the modified source code becomes available
+to the community.  It requires the operator of a network server to
+provide the source code of the modified version running there to the
+users of that server.  Therefore, public use of a modified version, on
+a publicly accessible server, gives the public access to the source
+code of the modified version.
+
+  An older license, called the Affero General Public License and
+published by Affero, was designed to accomplish similar goals.  This is
+a different license, not a version of the Affero GPL, but Affero has
+released a new version of the Affero GPL which permits relicensing under
+this license.
+
+  The precise terms and conditions for copying, distribution and
+modification follow.
+
+                       TERMS AND CONDITIONS
+
+  0. Definitions.
+
+  "This License" refers to version 3 of the GNU Affero General Public License.
+
+  "Copyright" also means copyright-like laws that apply to other kinds of
+works, such as semiconductor masks.
+
+  "The Program" refers to any copyrightable work licensed under this
+License.  Each licensee is addressed as "you".  "Licensees" and
+"recipients" may be individuals or organizations.
+
+  To "modify" a work means to copy from or adapt all or part of the work
+in a fashion requiring copyright permission, other than the making of an
+exact copy.  The resulting work is called a "modified version" of the
+earlier work or a work "based on" the earlier work.
+
+  A "covered work" means either the unmodified Program or a work based
+on the Program.
+
+  To "propagate" a work means to do anything with it that, without
+permission, would make you directly or secondarily liable for
+infringement under applicable copyright law, except executing it on a
+computer or modifying a private copy.  Propagation includes copying,
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+public, and in some countries other activities as well.
+
+  To "convey" a work means any kind of propagation that enables other
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+
+  An interactive user interface displays "Appropriate Legal Notices"
+to the extent that it includes a convenient and prominently visible
+feature that (1) displays an appropriate copyright notice, and (2)
+tells the user that there is no warranty for the work (except to the
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+
+  1. Source Code.
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+  The "source code" for a work means the preferred form of the work
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extensionsa/2-sd-webui-reactor/README.md

@@ -0,0 +1,413 @@
+<div align="center">
+
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_NEW_EN.png?raw=true" alt="logo" width="180px"/>
+    
+  ![Version](https://img.shields.io/badge/version-0.7.1_alpha2-lightgreen?style=for-the-badge&labelColor=darkgreen)
+  
+  <a href="https://boosty.to/artgourieff" target="_blank">
+    <img src="https://lovemet.ru/www/boosty.jpg" width="108" alt="Support Me on Boosty"/>
+    <br>
+    <sup>
+      Support This Project
+    </sup>
+  </a>
+
+  <hr>
+  
+  [![Commit activity](https://img.shields.io/github/commit-activity/t/Gourieff/sd-webui-reactor/main?cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/commits/main)
+  ![Last commit](https://img.shields.io/github/last-commit/Gourieff/sd-webui-reactor/main?cacheSeconds=0)
+  [![Opened issues](https://img.shields.io/github/issues/Gourieff/sd-webui-reactor?color=red)](https://github.com/Gourieff/sd-webui-reactor/issues?cacheSeconds=0)
+  [![Closed issues](https://img.shields.io/github/issues-closed/Gourieff/sd-webui-reactor?color=green&cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/issues?q=is%3Aissue+is%3Aclosed)
+  ![License](https://img.shields.io/github/license/Gourieff/sd-webui-reactor)
+
+  English | [Русский](/README_RU.md)
+
+# ReActor for Stable Diffusion
+
+### The Fast and Simple FaceSwap Extension with a lot of improvements and without NSFW filter (uncensored, use it on your own [responsibility](#disclaimer))
+
+---
+  <b>
+    <a href="#latestupdate">What's new</a> | <a href="#installation">Installation</a> | <a href="#features">Features</a> | <a href="#usage">Usage</a> | <a href="#api">API</a> | <a href="#troubleshooting">Troubleshooting</a> | <a href="#updating">Updating</a> | <a href="#comfyui">ComfyUI</a> | <a href="#disclaimer">Disclaimer</a>
+  </b>
+</div>
+
+---
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/demo_crop.jpg?raw=true" alt="example"/>
+
+<a name="latestupdate">
+
+## What's new in the latest updates
+
+<details>
+	<summary><a>Click to expand</a></summary>
+
+### 0.7.0 <sub><sup>BETA2
+
+- X/Y/Z is improved! One more parameter is ready: you can now select several face models to create a variation of swaps to choose the best one!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-05.jpg?raw=true" alt="0.7.0-whatsnew-05" width="100%"/>
+
+To use "Face Model" axis - you should enable ReActor and choose any face model as the Source:<br>
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-07.jpg?raw=true" alt="0.7.0-whatsnew-07" width="50%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-06.jpg?raw=true" alt="0.7.0-whatsnew-06" width="50%"/>
+
+Full size demo image: [xyz_demo_2.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo_2.png)
+
+### 0.7.0 <sub><sup>BETA1
+
+- X/Y/Z Script support (up to 3 axes: CodeFormer Weight, Restorer Visibility, Face Mask Correction)
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-03.jpg?raw=true" alt="0.7.0-whatsnew-03" width="100%"/>
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-04.jpg?raw=true" alt="0.7.0-whatsnew-04" width="100%"/>
+
+Full size demo image: [xyz_demo.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo.png)
+
+__Don't forget to enable ReActor and set any source (to prevent "no source" error)__
+
+### 0.7.0 <sub><sup>ALPHA1
+
+- You can now blend faces to build blended face models ("Tools->Face Models->Blend") - due to popular demand
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-01.jpg?raw=true" alt="0.7.0-whatsnew-01" width="100%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-02.jpg?raw=true" alt="0.7.0-whatsnew-02" width="100%"/>
+
+- CUDA 12 Support in the Installer script for 1.17.0 ORT-GPU library
+- New tab "Detection" with "Threshold" and "Max Faces" parameters
+
+### 0.6.1 <sub><sup>BETA3
+
+- 'Force Upscale' option inside the 'Upscale' tab: ReActor will run the Upscaler even if there's no face is detected (FR https://github.com/Gourieff/sd-webui-reactor/issues/116)
+- ReActor shows filenames of source images in-process when the multiple images mode or the folder mode (random as well) is selected
+
+### 0.6.1 <sub><sup>BETA2
+
+- 'Save original' option works fine now when you select 'Multiple Images' or 'Source Folder'
+- Random Mode for 'Source Folder'
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/random_from_folder_demo_01.jpg?raw=true" alt="0.6.1-whatsnew-01" width="100%"/>
+
+### 0.6.0
+
+- New Logo
+- Adaptation to A1111 1.7.0 (appropriate GFPGAN loader)
+- New URL for the main model file
+- UI reworked
+- You can now load several source images (with reference faces) or set the path to the folder containing faces images
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_01.png?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_02.png?raw=true" alt="0.6.0-whatsnew-02" width="100%"/>
+
+### 0.5.1
+
+- You can save face models as "safetensors" files (stored in `<sd-web-ui-folder>\models\reactor\faces`) and load them into ReActor, keeping super lightweight face models of the faces you use;
+- "Face Mask Correction" option - if you encounter some pixelation around face contours, this option will be useful;
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/face_model_demo_01.jpg?raw=true" alt="0.5.0-whatsnew-01" width="100%"/>
+
+</details>
+
+## Installation
+
+[A1111 WebUI / WebUI-Forge](#a1111) | [SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
+
+<a name="a1111">If you use [AUTOMATIC1111 SD WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) or [SD WebUI Forge](https://github.com/lllyasviel/stable-diffusion-webui-forge):
+
+1. (For Windows Users):
+  - Install **Visual Studio 2022** (Community version, for example - you need this step to build some of dependencies):
+  https://visualstudio.microsoft.com/downloads/
+  - OR only **VS C++ Build Tools** (if you don't need the whole Visual Studio) and select "Desktop Development with C++" under "Workloads -> Desktop & Mobile":
+  https://visualstudio.microsoft.com/visual-cpp-build-tools/
+  - OR if you don't want to install VS or VS C++ BT - follow [this steps (sec. VIII)](#insightfacebuild)
+2. In web-ui, go to the "Extensions" tab, load "Available" extensions and type "ReActor" in the search field or use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab - and click "Install"
+3. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
+4. Check the last message in your SD-WebUI Console:
+* If you see the message "--- PLEASE, RESTART the Server! ---" - so, do it, stop the Server (CTRL+C or CMD+C) and start it again - or just go to the "Installed" tab, click "Apply and restart UI" 
+* If you see the message "Done!", just reload the UI
+5. Enjoy!
+
+<a name="sdnext">If you use [SD.Next](https://github.com/vladmandic/automatic):
+
+1. Close (stop) your SD WebUI Server if it's running
+2. (For Windows Users) See the [1st step](#a1111) for Automatic1111 (if you followed [this steps (sec. VIII)](#insightfacebuild) instead - go to the Step 5)
+3. Go to (Windows)`automatic\venv\Scripts` or (MacOS/Linux)`automatic/venv/bin`, run Terminal or Console (cmd) for that folder and type `activate`
+4. Run `pip install insightface==0.7.3`
+5. Run SD.Next, go to the "Extensions" tab and use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab and click "Install"
+6. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
+7. Check the last message in your SD.Next Console:
+* If you see the message "--- PLEASE, RESTART the Server! ---" - stop the Server (CTRL+C or CMD+C) or just close your console
+8. Go to the `automatic\extensions\sd-webui-reactor` directory - if you see there `models\insightface` folder with the file `inswapper_128.onnx`, just move the file to the `automatic\models\insightface` folder
+9. Run your SD.Next WebUI and enjoy!
+
+<a name="colab">If you use [Cagliostro Colab UI](https://github.com/Linaqruf/sd-notebook-collection):
+
+1. In active WebUI, go to the "Extensions" tab, load "Available" extensions and type "ReActor" in the search field or use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab - and click "Install"
+2. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
+3. When you see the message "--- PLEASE, RESTART the Server! ---" (in your Colab Notebook Start UI section "Start Cagliostro Colab UI") - just go to the "Installed" tab and click "Apply and restart UI"
+4. Enjoy!
+
+## Features
+
+- Very fast and accurate **face replacement (face swap)** in images
+- **Multiple faces support**
+- **Gender detection**
+- Ability to **save original images** (made before swapping)
+- **Face restoration** of a swapped face
+- **Upscaling** of a resulting image
+- Saving ans loading **Safetensors Face Models**
+- **Facial Mask Correction** to avoid any  pixelation around face contours
+- Ability to set the **Postprocessing order**
+- **100% compatibility** with different **SD WebUIs**: Automatic1111, SD.Next, Cagliostro Colab UI
+- **Fast performance** even with CPU, ReActor for SD WebUI is absolutely not picky about how powerful your GPU is
+- **CUDA** acceleration support since version 0.5.0
+- **[API](/API.md) support**: both SD WebUI built-in and external (via POST/GET requests)
+- **ComfyUI [support](https://github.com/Gourieff/comfyui-reactor-node)**
+- **Mac M1/M2 [support](https://github.com/Gourieff/sd-webui-reactor/issues/42)**
+- Console **log level control**
+- **NSFW filter free** (this extension is aimed at highly developed intellectual people, not at perverts; our society must be oriented on its way towards the highest standards, not the lowest - this is the essence of development and evolution; so, my position is - that mature-minded people are clever enough to understand for themselves what is good and what is bad and take full responsibility for personal actions; for others - no "filters" will help until they do understand how Universe works)
+
+## Usage
+
+> Using this software you are agree with [disclaimer](#disclaimer)
+
+1. Under "ReActor" drop-down menu, import an image containing a face;
+2. Turn on the "Enable" checkbox;
+3. That's it, now the generated result will have the face you selected.
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/example.jpg?raw=true" alt="example" width="808"/>
+
+### Face Indexes
+
+ReActor detects faces in images in the following order:<br>
+left->right, top->bottom
+
+And if you need to specify faces, you can set indexes for source and input images.
+
+Index of the first detected face is 0.
+
+You can set indexes in the order you need.<br>
+E.g.: 0,1,2 (for Source); 1,0,2 (for Input).<br>
+This means: the second Input face (index = 1) will be swapped by the first Source face (index = 0) and so on.
+
+### Genders
+
+You can specify the gender to detect in images.<br>
+ReActor will swap a face only if it meets the given condition.
+
+### The result face is blurry
+Use the "Restore Face" option. You can also try the "Upscaler" option or for more finer control, use an upscaler from the "Extras" tab.
+You can also set the postproduction order (from 0.1.0 version):
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/pp-order.png?raw=true" alt="example"/>
+
+*The old logic was the opposite (Upscale -> then Restore), resulting in worse face quality (and big texture differences) after upscaling.* 
+
+### There are multiple faces in result
+Select the face numbers you wish to swap using the "Comma separated face number(s)" option for swap-source and result images. You can use different index order.
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/multiple-faces.png?raw=true" alt="example"/>
+
+### ~~The result is totally black~~
+~~This means NSFW filter detected that your image is NSFW.~~
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/IamSFW.jpg?raw=true" alt="IamSFW" width="50%"/>
+
+### Img2Img
+
+You can choose to activate the swap on the source image or on the generated image, or on both using the checkboxes. Activating on source image allows you to start from a given base and apply the diffusion process to it.
+
+ReActor works with Inpainting - but only the masked part will be swapped.<br>Please use with the "Only masked" option for "Inpaint area" if you enabled "Upscaler". Otherwise use the upscale option via the Extras tab or via the Script loader (below the screen) with "SD upscale" or "Ultimate SD upscale".
+
+### Extras Tab
+
+From the version 0.5.0 you can use ReActor via the Extras Tab. It gives a superfast perfomance and ability to swap face2image avoiding SD pipeline that can cause smushing of original image's details
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/extras_tab.jpg?raw=true" alt="IamSFW"/>
+
+## API
+
+You can use ReActor with the built-in Webui API or via an external API.
+
+Please follow **[this](/API.md)** page for the detailed instruction.
+
+## Troubleshooting
+
+### **I. "You should at least have one model in models directory"**
+
+Please, check the path where "inswapper_128.onnx" model is stored. It must be inside the folder `stable-diffusion-webui\models\insightface`. Move the model there if it's stored in a different directory.
+
+### **II. Any problems with installing Insightface or other dependencies**
+
+(for Mac M1/M2 users) If you get errors when trying to install Insightface - please read https://github.com/Gourieff/sd-webui-reactor/issues/42
+
+(for Windows Users) If you have VS C++ Build Tools or MS VS 2022 installed but still have a problem, then try the next step:
+1. Close (stop) your SD WebUI Server and start it again
+   
+(for Any OS Users) If the problem still there, then do the following:
+1. Close (stop) your SD WebUI Server if it's running
+2. Go to (Windows)`venv\Lib\site-packages` folder or (MacOS/Linux)`venv/lib/python3.10/site-packages`
+3. If you see any folders with names start from `~` (e.g. "~rotobuf") - delete them
+4. Go to (Windows)`venv\Scripts` or (MacOS/Linux)`venv/bin`
+5. Run Terminal or Console (cmd) for that folder and type `activate`
+6. Update your pip at first: `pip install -U pip`
+7. Then one-by-one:
+   - `pip install insightface==0.7.3`
+   - `pip install onnx`
+   - `pip install "onnxruntime-gpu>=1.16.1"`
+   - `pip install opencv-python`
+   - `pip install tqdm`
+8. Type `deactivate`, you can close your Terminal or Console and start your SD WebUI, ReActor should start OK - if not, welcome to the Issues section.
+
+### **III. "TypeError: UpscaleOptions.init() got an unexpected keyword argument 'do_restore_first'"**
+
+First of all - you need to disable any other Roop-based extensions:
+- Go to 'Extensions -> Installed' tab and uncheck any Roop-based extensions except this one
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/roop-off.png?raw=true" alt="uncompatible-with-other-roop"/>
+- Click 'Apply and restart UI'
+
+Alternative solutions: 
+- https://github.com/Gourieff/sd-webui-reactor/issues/3#issuecomment-1615919243
+- https://github.com/Gourieff/sd-webui-reactor/issues/39#issuecomment-1666559134 (can be actual, if you use Vladmandic SD.Next)
+
+### **IV. "AttributeError: 'FaceSwapScript' object has no attribute 'enable'"**
+
+Probably, you need to disable the "SD-CN-Animation" extension (or perhaps some another that causes the conflict)
+
+### **V. "INVALID_PROTOBUF : Load model from <...>\models\insightface\inswapper_128.onnx failed:Protobuf parsing failed" OR "AttributeError: 'NoneType' object has no attribute 'get'" OR "AttributeError: 'FaceSwapScript' object has no attribute 'save_original'"**
+
+This error may occur if there's smth wrong with the model file `inswapper_128.onnx`
+
+Try to download it manually from [here](https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/inswapper_128.onnx)
+and put it to the `stable-diffusion-webui\models\insightface` replacing existing one
+
+### **VI. "ValueError: This ORT build has ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider'] enabled" OR "ValueError: This ORT build has ['AzureExecutionProvider', 'CPUExecutionProvider'] enabled"**
+
+1. Close (stop) your SD WebUI Server if it's running
+2. Go to the (Windows)`venv\Lib\site-packages` or (MacOS/Linux)`venv/lib/python3.10/site-packages` and see if there are any folders with names start from "~" (for example "~rotobuf"), delete them
+3. Go to the (Windows)`venv\Scripts` or (MacOS/Linux)`venv/bin` run Terminal or Console (cmd) there and type `activate`
+4. Then:
+- `python -m pip install -U pip`
+- `pip uninstall -y onnxruntime onnxruntime-gpu onnxruntime-silicon onnxruntime-extensions`
+- `pip install "onnxruntime-gpu>=1.16.1"`
+
+If it didn't help - it seems that you have another extension reinstalling `onnxruntime` when SD WebUI checks requirements. Please see your extensions list. Some extensions can causes reinstalling of `onnxruntime-gpu` to `onnxruntime<1.16.1` every time SD WebUI runs.<br>ORT 1.16.0 has a bug https://github.com/microsoft/onnxruntime/issues/17631 - don't install it!
+
+### **VII. "ImportError: cannot import name 'builder' from 'google.protobuf.internal'"**
+
+1. Close (stop) your SD WebUI Server if it's running
+2. Go to the (Windows)`venv\Lib\site-packages` or (MacOS/Linux)`venv/lib/python3.10/site-packages` and see if there are any folders with names start from "~" (for example "~rotobuf"), delete them
+3. Go to the "google" folder (inside the "site-packages") and delete any folders there with names start from "~"
+4. Go to the (Windows)`venv\Scripts` or (MacOS/Linux)`venv/bin` run Terminal or Console (cmd) there and type `activate`
+5. Then:
+- `python -m pip install -U pip`
+- `pip uninstall protobuf`
+- `pip install "protobuf>=3.20.3"`
+
+If this method doesn't help - there is some other extension that has a wrong version of protobuf dependence and SD WebUI installs it on a startup requirements check
+
+<a name="insightfacebuild">
+
+### **VIII. (For Windows users) If you still cannot build Insightface for some reasons or just don't want to install Visual Studio or VS C++ Build Tools - do the following:**
+
+1. Close (stop) your SD WebUI Server if it's running
+2. Download and put [prebuilt Insightface package](https://github.com/Gourieff/Assets/raw/main/Insightface/insightface-0.7.3-cp310-cp310-win_amd64.whl) into the stable-diffusion-webui (or SD.Next) root folder where you have "webui-user.bat" file or (A1111 Portable) "run.bat"
+3. From stable-diffusion-webui (or SD.Next) root folder run CMD and `.\venv\Scripts\activate`<br>OR<br>(A1111 Portable) Run CMD
+4. Then update your PIP: `python -m pip install -U pip`<br>OR<br>(A1111 Portable)`system\python\python.exe -m pip install -U pip`
+5. Then install Insightface: `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`<br>OR<br>(A1111 Portable)`system\python\python.exe -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`
+6. Enjoy!
+
+### **IX. 07-August-23 Update problem**
+
+If after `git pull` you see the message: `Merge made by the 'recursive' strategy` and then when you check `git status` you see `Your branch is ahead of 'origin/main' by`
+
+Please do the next:
+
+Inside the folder `extensions\sd-webui-reactor` run Terminal or Console (cmd) and then:
+- `git reset f48bdf1 --hard`
+- `git pull`
+
+OR
+
+Just delete the folder `sd-webui-reactor` inside the `extensions` directory and then run Terminal or Console (cmd) and type `git clone https://github.com/Gourieff/sd-webui-reactor`
+
+### **X. StabilityMatrix Issues**
+
+If you encounter any issues with installing this extension in the StabilityMatrix package manager - read here how to solve: https://github.com/Gourieff/sd-webui-reactor/issues/129#issuecomment-1768210875
+
+## Updating
+
+A good and quick way to check for Extensions updates: https://github.com/Gourieff/sd-webui-extensions-updater
+
+## ComfyUI
+
+You can use ReActor with ComfyUI.<br>
+For the installation instruction follow the [ReActor Node repo](https://github.com/Gourieff/comfyui-reactor-node)
+
+## Disclaimer
+
+This software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.
+
+The developers of this software are aware of its possible unethical application and are committed to take preventative measures against them. We will continue to develop this project in the positive direction while adhering to law and ethics.
+
+Users of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. **Developers and Contributors of this software are not responsible for actions of end-users.**
+
+By using this extension you are agree not to create any content that:
+- violates any laws;
+- causes any harm to a person or persons;
+- propogates (spreads) any information (both public or personal) or images (both public or personal) which could be meant for harm;
+- spreads misinformation;
+- targets vulnerable groups of people.
+
+This software utilizes the pre-trained models `buffalo_l` and `inswapper_128.onnx`, which are provided by [InsightFace](https://github.com/deepinsight/insightface/). These models are included under the following conditions:
+
+[From insighface licence](https://github.com/deepinsight/insightface/tree/master/python-package): The InsightFace’s pre-trained models are available for non-commercial research purposes only. This includes both auto-downloading models and manually downloaded models.
+
+Users of this software must strictly adhere to these conditions of use. The developers and maintainers of this software are not responsible for any misuse of InsightFace’s pre-trained models.
+
+Please note that if you intend to use this software for any commercial purposes, you will need to train your own models or find models that can be used commercially.
+
+### Models Hashsum
+
+#### Safe-to-use models have the folowing hash:
+
+inswapper_128.onnx
+```
+MD5:a3a155b90354160350efd66fed6b3d80
+SHA256:e4a3f08c753cb72d04e10aa0f7dbe3deebbf39567d4ead6dce08e98aa49e16af
+```
+
+1k3d68.onnx
+
+```
+MD5:6fb94fcdb0055e3638bf9158e6a108f4
+SHA256:df5c06b8a0c12e422b2ed8947b8869faa4105387f199c477af038aa01f9a45cc
+```
+
+2d106det.onnx
+
+```
+MD5:a3613ef9eb3662b4ef88eb90db1fcf26
+SHA256:f001b856447c413801ef5c42091ed0cd516fcd21f2d6b79635b1e733a7109dbf
+```
+
+det_10g.onnx
+
+```
+MD5:4c10eef5c9e168357a16fdd580fa8371
+SHA256:5838f7fe053675b1c7a08b633df49e7af5495cee0493c7dcf6697200b85b5b91
+```
+
+genderage.onnx
+
+```
+MD5:81c77ba87ab38163b0dec6b26f8e2af2
+SHA256:4fde69b1c810857b88c64a335084f1c3fe8f01246c9a191b48c7bb756d6652fb
+```
+
+w600k_r50.onnx
+
+```
+MD5:80248d427976241cbd1343889ed132b3
+SHA256:4c06341c33c2ca1f86781dab0e829f88ad5b64be9fba56e56bc9ebdefc619e43
+```
+
+**Please check hashsums if you download these models from unverified (or untrusted) sources**

extensionsa/2-sd-webui-reactor/README_RU.md

@@ -0,0 +1,420 @@
+<div align="center">
+
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_NEW_RU.png?raw=true" alt="logo" width="180px"/>
+    
+  ![Version](https://img.shields.io/badge/версия-0.7.1_alpha2-lightgreen?style=for-the-badge&labelColor=darkgreen)
+  
+  <a href="https://boosty.to/artgourieff" target="_blank">
+    <img src="https://lovemet.ru/www/boosty.jpg" width="108" alt="Поддержать проект на Boosty"/>
+    <br>
+    <sup>
+      Поддержать проект
+    </sup>
+  </a>
+  
+  <hr>
+  
+  [![Commit activity](https://img.shields.io/github/commit-activity/t/Gourieff/sd-webui-reactor/main?cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/commits/main)
+  ![Last commit](https://img.shields.io/github/last-commit/Gourieff/sd-webui-reactor/main?cacheSeconds=0)
+  [![Opened issues](https://img.shields.io/github/issues/Gourieff/sd-webui-reactor?color=red)](https://github.com/Gourieff/sd-webui-reactor/issues?cacheSeconds=0)
+  [![Closed issues](https://img.shields.io/github/issues-closed/Gourieff/sd-webui-reactor?color=green&cacheSeconds=0)](https://github.com/Gourieff/sd-webui-reactor/issues?q=is%3Aissue+is%3Aclosed)
+  ![License](https://img.shields.io/github/license/Gourieff/sd-webui-reactor)
+
+  [English](/README.md) | Русский
+
+# ReActor для Stable Diffusion
+### Расширение для быстрой и простой замены лиц на любых изображениях. Без фильтра цензуры, 18+, используйте под вашу собственную [ответственность](#disclaimer)
+
+---
+  <b>
+    <a href="#latestupdate">Что нового</a> | <a href="#installation">Установка</a> | <a href="#features">Возможности</a> | <a href="#usage">Использование</a> | <a href="#api">API</a> | <a href="#troubleshooting">Устранение проблем</a> | <a href="#updating">Обновление</a> | <a href="#comfyui">ComfyUI</a> | <a href="#disclaimer">Ответственность</a>
+  </b>
+</div>
+
+---
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/demo_crop.jpg?raw=true" alt="example"/>
+
+<a name="latestupdate">
+
+## Что нового в последних обновлениях
+
+<details>
+	<summary><a>Нажмите, чтобы посмотреть</a></summary>
+
+### 0.7.0 <sub><sup>BETA2
+
+- X/Y/Z опция улучшена! Добавлен ещё один параметр: теперь вы можете выбрать несколько моделей лиц для создания вариации замененных лиц, чтобы выбрать наилучшие!
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-05.jpg?raw=true" alt="0.7.0-whatsnew-05" width="100%"/>
+
+Чтобы использовать ось "Face Model" - активируйте РеАктор и выбирите любую модель лица в качестве источника:<br>
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-07.jpg?raw=true" alt="0.7.0-whatsnew-07" width="50%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-06.jpg?raw=true" alt="0.7.0-whatsnew-06" width="50%"/>
+
+Полноразмерное демо-изображение: [xyz_demo_2.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo_2.png)
+
+### 0.7.0 <sub><sup>BETA1
+
+- Поддержка X/Y/Z скрипта (до 3-х параметров: CodeFormer Weight, Restorer Visibility, Face Mask Correction)
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-03.jpg?raw=true" alt="0.7.0-whatsnew-03" width="100%"/>
+
+Полноразмерное демо-изображение: [xyz_demo.png](https://raw.githubusercontent.com/Gourieff/Assets/main/sd-webui-reactor/xyz_demo.png)
+
+### 0.7.0 <sub><sup>ALPHA1
+
+- По многочисленным просьбам появилась возможность строить смешанные модели лиц ("Tools->Face Models->Blend")
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-01.jpg?raw=true" alt="0.7.0-whatsnew-01" width="100%"/><img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/0.7.0-whatsnew-02.jpg?raw=true" alt="0.7.0-whatsnew-02" width="100%"/>
+
+- Поддержка CUDA 12 в скрипте установщика для библиотеки ORT-GPU версии 1.17.0
+- Новая вкладка "Detection" с параметрами "Threshold" и "Max Faces"
+
+### 0.6.1 <sub><sup>BETA3
+
+- Опция 'Force Upscale' внутри вкладки 'Upscale': апскейл выполнится, даже если не было обнаружено ни одного лица (FR https://github.com/Gourieff/sd-webui-reactor/issues/116)
+- Отображение имён файлов используемых из��бражений, когда выбрано несколько изображений или папка (а также режим случайного изображения)
+
+### 0.6.1 <sub><sup>BETA2
+
+- Опция 'Save original' теперь работает правильно, когда вы выбираете 'Multiple Images' или 'Source Folder'
+- Добавлен режим выбора случайного изображения для 'Source Folder'
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/random_from_folder_demo_01.jpg?raw=true" alt="0.6.1-whatsnew-01" width="100%"/>
+
+### 0.6.0
+
+- Новый логотип
+- Адаптация к версии A1111 1.7.0 (правильная загрузка GFPGAN)
+- Новая ссылка для файла основной модели
+- UI переработан
+- Появилась возможность загружать несколько исходных изображений с лицами или задавать путь к папке, содержащей такие изображения
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_01.png?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_02.png?raw=true" alt="0.6.0-whatsnew-02" width="100%"/>
+
+### 0.5.1
+
+- Теперь можно сохранять модели лиц в качестве файлов "safetensors" (находятся в `<sd-web-ui-folder>\models\reactor\faces`) и загружать их с ReActor, храня супер легкие модели лиц, которые вы чаще всего используете;
+- Новые опция "Face Mask Correction" - если вы сталкиваетесь с пикселизацией вокруг контуров лица, эта опция будет полезной;
+
+<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/face_model_demo_01.jpg?raw=true" alt="0.5.0-whatsnew-01" width="100%"/>
+
+</details>
+
+<a name="installation">
+
+## Установка
+
+[A1111 WebUI / WebUI-Forge](#a1111) | [SD.Next](#sdnext) | [Google Colab SD WebUI](#colab)
+
+<a name="a1111">Если вы используете [AUTOMATIC1111 SD WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) или [SD WebUI Forge](https://github.com/lllyasviel/stable-diffusion-webui-forge):
+
+1. (Для пользователей Windows):
+  - Установите **Visual Studio 2022** (Например, версию Community - этот шаг нужен для правильной компиляции библиотеки Insightface):
+  https://visualstudio.microsoft.com/downloads/
+  - ИЛИ только **VS C++ Build Tools** (если вам не нужен весь пакет Visual Studio), выберите "Desktop Development with C++" в разделе "Workloads -> Desktop & Mobile":
+  https://visualstudio.microsoft.com/visual-cpp-build-tools/
+  - ИЛИ если же вы не хотите устанавливать что-либо из вышеуказанного - выполните [следующие шаги (пункт VIII)](#insightfacebuild)
+2. Внутри SD Web-UI перейдите во вкладку "Extensions", загрузите список доступных расширений (вкладка "Available") и введите "ReActor" в строке поиска или же вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" - и нажмите "Install"
+3. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
+4. Проверьте последнее сообщение в консоли SD-WebUI:
+* Если вы видите "--- PLEASE, RESTART the Server! ---" - остановите Сервер (CTRL+C или CMD+C) и запустите его заново - ИЛИ же перейдите во вкладку "Installed", нажмите "Apply and restart UI" 
+* Если вы видите "Done!", просто перезагрузите UI, нажав на "Reload UI"
+5. Готово!
+
+<a name="sdnext">Если вы используете [SD.Next](https://github.com/vladmandic/automatic):
+
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. (Для пользователей Windows) Смотрите [Шаг 1](#a1111) для Automatic1111 (если же вы следовали [данным шагам (пункт VIII)](#insightfacebuild) вместо этого - переходите к Шагу 5)
+3. Перейдите в (Windows)`automatic\venv\Scripts` или (MacOS/Linux)`automatic/venv/bin`, запустите Терминал или Консоль (cmd) для данной папки и выполните `activate`
+4. Выполните `pip install insightface==0.7.3`
+5. Запустите SD.Next, перейдите во вкладку "Extensions", вставьте эту ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" и нажмите "Install"
+6. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
+7. Проверьте последнее сообщение в консоли SD.Next:
+* Если вы видите "--- PLEASE, RESTART the Server! ---" - остановите Сервер (CTRL+C или CMD+C) или просто закройте консоль
+8. Перейдите в директорию `automatic\extensions\sd-webui-reactor` - если вы видите там папку `models\insightface` с файлом `inswapper_128.onnx` внутри, переместите его в папку `automatic\models\insightface`
+9. Готово, можете запустить SD.Next WebUI!
+
+<a name="colab">Если вы используете [Cagliostro Colab UI](https://github.com/Linaqruf/sd-notebook-collection):
+
+1. В активном WebUI перейдите во вкладку "Extensions", загрузите список доступных расширений (вкладка "Available") и введите "ReActor" в строке поиска или же вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" - и нажмите "Install"
+2. Пожалуйста, подождите некоторое время, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
+3. Когда вы увидите сообщение "--- PLEASE, RESTART the Server! ---" (в секции "Start UI" вашего ноутбука "Start Cagliostro Colab UI") - перейдите во вкладку "Installed" и нажмите "Apply and restart UI"
+4. Готово!
+
+<a name="features">
+
+## Возможности
+
+- Быстрая и точна **замена лиц (faceswap)** на изображении
+- **Поддержка нескольких лиц**
+- **Определение пола**
+- Функция **сохранения оригинального изображения** (сгенерированного до замены лица)
+- **Восстановление лица** после замены
+- **Увеличение размера** полученного изображения
+- Сохранение и загрузка **Моделей Лиц типа Safetensors**
+- **Коррекция Маски Лица** для предотвращения какой-либо пикселизации вокруг контуров лиц
+- Возможность задать **порядок постобработки**
+- **100% совместимость** с разными **SD WebUI**: Automatic1111, SD.Next, Cagliostro Colab UI
+- **Отличная производительность** даже с использованием ЦПУ, ReActor для SD WebUI абсолютно не требователен к мощности вашей видеокарты
+- **Поддержка CUDA**, начиная с версии 0.5.0
+- **Поддержка [API](/API.md)**: как встроенного в SD WebUI, так и внешнего (через POST/GET запросы)
+- **[Поддержка](https://github.com/Gourieff/comfyui-reactor-node) ComfyUI**
+- **[Поддержка](https://github.com/Gourieff/sd-webui-reactor/issues/42) компьютеров Mac M1/M2**
+- **Регулировка уровня логов** консоли
+- **Без NSFW фильтров** (данное расширение адресовано высокоразвитым интеллектуальным людям, а не извращенцам; наше общество должно быть ориентировано на своём пути на высшие стандарты, а не на низшие - в этом состоит суть развития и эволюции человеческого общества; поэтому, моя позиция такова - что зрелые умом люди достаточно разумны, чтобы понимать, что есть хорошо, а что плохо и нести полную ответственность за собственные действия; для прочих - никакие "фильтры" не помогут, пока эти люди сами не поймут, как работает Вселенная)
+
+<a name="usage">
+
+## Использование
+
+> Используя данное программное обеспечение, вы соглашаетесь с [ответственностью](#disclaimer)
+
+1. В раскрывающимся меню "ReActor" импортируйте изображение, содержащее лицо;
+2. Установите флажок "Enable";
+3. Готово, теперь результат будет иметь то лицо, которое вы выбрали.
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/example.jpg?raw=true" alt="example" width="808"/>
+
+### Индексы Лиц (Face Indexes)
+
+ReActor определяет лица на изображении в следующей последовательности:<br>
+слева-направо, сверху-вниз.
+
+Если вам нужно заменить определенное лицо, вы можете указать индекс для исходного (source, с лицом) и входного (input, где будет замена лица) изображений.
+
+Индекс первого обнаруженного лица - 0.
+
+Вы можете задать индексы в том порядке, который вам нужен.<br>
+Например: 0,1,2 (для Source); 1,0,2 (для Input).<br>
+Это означает, что: второе лицо из Input (индекс = 1) будет заменено первым лицом из Source (индекс = 0) и так далее.
+
+### Определение Пола
+
+Вы можете обозначить, какой пол нужно определять на изображении.<br>
+ReActor заменит только то лицо, которое удовлетворяет заданному условию.
+
+### Если лицо получилось нечётким
+Используйте опцию "Restore Face". Также можете попробовать опцию "Upscaler". Для более точного контроля параметров используйте Upscaler во вкладке "Extras".
+Также вы можете установить порядок постобработки (начиная с версии 0.1.0):
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/pp-order.png?raw=true" alt="example"/>
+
+*Прежняя логика была противоположенной (Upscale -> затем Restore), что приводило к более худшему качеству изображения лица (а также к значительной разнице текстур) после увеличения.* 
+
+### Результат имеет несколько лиц
+Выберите номера лиц, которые нужно поменять, используя поля "Comma separated face number(s)" для исходного изображения лица и для результата. Можно устанавливать любой, необходимый вам, порядок лиц.
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/multiple-faces.png?raw=true" alt="example"/>
+
+### ~~Результат получился чёрным~~
+~~Это значит, что сработал NSFW фильтр.~~
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/IamSFW.jpg?raw=true" alt="IamSFW" width="50%"/>
+
+### Img2Img
+
+Используйте эту вкладку, чтобы заменить лицо на уже готовом изображении (флажок "Swap in source image") или на сгенерированном на основе готового (флажок "Swap in generated image").
+
+Inpainting также работает, но замена лица происходит только в области маски.<br>Пожалуйста, используйте с опцией "Only masked" для "Inpaint area", если вы применяете "Upscaler". Иначе, используйте функцию увеличения (апскейла) через вкладку "Extras" или через опциональный загрузчик "Script" (внизу экрана), применив "SD upscale" или "Ultimate SD upscale".
+
+### Extras
+
+Начиная с версии 0.5.0, вы можете использовать ReActor через вкладку Extras, что даёт очень быструю производительность и возможность замены лиц в обход пайплайна SD, что иногда вызывает размытие или искажение деталей оригинального изображения
+
+<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/extras_tab.jpg?raw=true" alt="IamSFW"/>
+
+## API
+
+Вы можете использовать ReActor как со встроенным SD Webui API так и через внешнее API.
+
+Подробная инструкция **[здесь](/API.md)**.
+
+<a name="troubleshooting">
+
+## Устранение проблем
+
+### **I. "You should at least have one model in models directory"**
+
+Проверьте путь, где хранится модель "inswapper_128.onnx". Файл должен находиться в папке `stable-diffusion-webui\models\insightface`. Переместите модель туда, если она находится в какой-то иной директории.
+
+### **II. Какие-либо проблемы с установкой Insightface или прочих пакетов**
+
+(Для пользователей Mac M1/M2) Если вы получаете ошибки в ходе установки Insightface - читайте https://github.com/Gourieff/sd-webui-reactor/issues/42
+
+(Для пользователей Windows) Если VS C++ Build Tools или MS VS 2022 установлены но вы видите ошибки, связанные с отсутствием Insightface, попробуйте следующее:
+1. Закройте (остановите) SD WebUI Сервер и запустите его снова (возможно, не прошла инициализация пакета после его установки)
+   
+(Для пользователей любых ОС) Попробуйте следующее:
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Перейдите в папку (Windows)`venv\Lib\site-packages` или (MacOS/Linux)`venv/lib/python3.10/site-packages`
+3. Если вы видите к-л папки с именами, начинающимися с `~` (например, "~rotobuf") - удалите их
+4. Перейдите в (Windows)`venv\Scripts` или (MacOS/Linux)`venv/bin`
+5. Откройте Терминал или Консоль (cmd) для этой папки и выполните `activate`
+6. Для начала обновите pip: `pip install -U pip`
+7. Далее:
+   - `pip install insightface==0.7.3`
+   - `pip install onnx`
+   - `pip install "onnxruntime-gpu>=1.16.1"`
+   - `pip install opencv-python`
+   - `pip install tqdm`
+8. Выполните `deactivate`, закройте Терминал или Консоль и запустите SD WebUI, ReActor должен запуститься без к-л проблем - если же нет, добро пожаловать в раздел "Issues".
+
+### **III. "TypeError: UpscaleOptions.init() got an unexpected keyword argument 'do_restore_first'"**
+
+Для начала отключите любые другие Roop-подобные расширения:
+- Перейдите в 'Extensions -> Installed' и снимите флажок с ненужных:
+  <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/roop-off.png?raw=true" alt="uncompatible-with-other-roop"/>
+- Нажмите 'Apply and restart UI'
+
+Альтернативные решения: 
+- https://github.com/Gourieff/sd-webui-reactor/issues/3#issuecomment-1615919243
+- https://github.com/Gourieff/sd-webui-reactor/issues/39#issuecomment-1666559134 (актуально для Vladmandic SD.Next)
+
+### **IV. "AttributeError: 'FaceSwapScript' object has no attribute 'enable'"**
+
+Отключите расширение "SD-CN-Animation" (или какое-либо другое, вызывающее конфликт)
+
+### **V. "INVALID_PROTOBUF : Load model from <...>\models\insightface\inswapper_128.onnx failed:Protobuf parsing failed" ИЛИ "AttributeError: 'NoneType' object has no attribute 'get'" ИЛИ "AttributeError: 'FaceSwapScript' object has no attribute 'save_original'"**
+
+Эта ошибка появляется, если что-то не так с файлом модели `inswapper_128.onnx`.
+
+Скачайте вручную по ссылке [here](https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/inswapper_128.onnx)
+и сохраните в директорию `stable-diffusion-webui\models\insightface`, заменив имеющийся файл.
+
+### **VI. "ValueError: This ORT build has ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider'] enabled" ИЛИ "ValueError: This ORT build has ['AzureExecutionProvider', 'CPUExecutionProvider'] enabled"**
+
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Перейдите в (Windows)`venv\Lib\site-packages` или (MacOS/Linux)`venv/lib/python3.10/site-packages` и посмотрите, если там папки с именам, начинающимися на "~" (например, "~rotobuf"), удалите их
+3. Перейдите в (Windows)`venv\Scripts` или (MacOS/Linux)`venv/bin`, откройте Терминал или Консоль (cmd) и выполните `activate`
+4. Затем:
+- `python -m pip install -U pip`
+- `pip uninstall -y onnxruntime onnxruntime-gpu onnxruntime-silicon onnxruntime-extensions`
+- `pip install "onnxruntime-gpu>=1.16.1"`
+
+Если это не помогло - значит какое-то другое расширение переустанавлив��ет `onnxruntime` всякий раз, когда SD WebUI проверяет требования пакетов. Внимательно посмотрите список активных расширений. Некоторые расширения могут вызывать переустановку `onnxruntime-gpu` на версию `onnxruntime<1.16.1` при каждом запуске SD WebUI.<br>ORT 1.16.0 выкатили с ошибкой https://github.com/microsoft/onnxruntime/issues/17631 - не устанавливайте её!
+
+### **VII. "ImportError: cannot import name 'builder' from 'google.protobuf.internal'"**
+
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Перейдите в (Windows)`venv\Lib\site-packages` или (MacOS/Linux)`venv/lib/python3.10/site-packages` и посмотрите, если там папки с именам, начинающимися на "~" (например, "~rotobuf"), удалите их
+3. Перейдите в папку "google" (внутри "site-packages") и удалите любые папки с именам, начинающимися на "~"
+4. Перейдите в (Windows)`venv\Scripts` или (MacOS/Linux)`venv/bin`, откройте Терминал или Консоль (cmd) и выполните `activate`
+5. Затем:
+- `python -m pip install -U pip`
+- `pip uninstall protobuf`
+- `pip install "protobuf>=3.20.3"`
+
+Если это не помгло - значит, есть к-л другое расширение, которое использует неподходящую версию пакета protobuf, и SD WebUI устанавливает эту версию при каждом запуске.
+
+<a name="insightfacebuild">
+
+### **VIII. (Для пользователей Windows) Если вы до сих пор не можете установить пакет Insightface по каким-то причинам или же просто не желаете устанавливать Visual Studio или VS C++ Build Tools - сделайте следующее:**
+
+1. Закройте (остановите) SD WebUI Сервер, если он запущен
+2. Скачайте готовый [пакет Insightface](https://github.com/Gourieff/Assets/raw/main/Insightface/insightface-0.7.3-cp310-cp310-win_amd64.whl) и сохраните его в корневую директорию stable-diffusion-webui (или SD.Next) - туда, где лежит файл "webui-user.bat" или (A1111 Portable) "run.bat"
+3. Из корневой директории откройте Консоль (CMD) и выполните `.\venv\Scripts\activate`<br>ИЛИ<br>(A1111 Portable) Откройте Консоль (CMD)
+4. Обновите PIP: `python -m pip install -U pip`<br>ИЛИ<br>(A1111 Portable)`system\python\python.exe -m pip install -U pip`
+5. Затем установите Insightface: `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`<br>ИЛИ<br>(A1111 Portable)`system\python\python.exe -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`
+6. Готово!
+
+### **IX. Ошибка обновления 07-Август-23**
+
+Если после очередного `git pull` вы получили сообщение: `Merge made by the 'recursive' strategy` и затем, когда проверяете статус репозитория через `git status`, вы видите `Your branch is ahead of 'origin/main' by`
+
+Выполните следующее:
+
+Внутри папки `extensions\sd-webui-reactor` запустите Терминал или Консоль (cmd) и затем:
+- `git reset f48bdf1 --hard`
+- `git pull`
+
+ИЛИ:
+
+Полностью удалите папку `sd-webui-reactor` внутри директории `extensions`, запустите Терминал или Консоль (cmd) и выполните `git clone https://github.com/Gourieff/sd-webui-reactor`
+
+### **X. Ошибки установки в StabilityMatrix**
+
+Если вы столкнулись с ошибками при установки данного расширения в пакетном менеджере StabilityMatrix - изучите информацию по ссылке: https://github.com/Gourieff/sd-webui-reactor/issues/129#issuecomment-1768210875
+
+<a name="updating">
+
+## Обновление
+
+Самый простой и удобный способ обновления SD WebUI и расширений: https://github.com/Gourieff/sd-webui-extensions-updater
+
+## ComfyUI
+
+Вы можете использовать ReActor с ComfyUI<br>
+Инструкция здесь: [ReActor Node](https://github.com/Gourieff/comfyui-reactor-node)
+
+<a name="disclaimer">
+
+## Ответственность
+
+Это программное обеспечение призвано стать продуктивным вкладом в быстрорастущую медиаиндустрию на основе генеративн��х сетей и искусственного интеллекта. Данное ПО поможет художникам в решении таких задач, как анимация собственного персонажа или использование персонажа в качестве модели для одежды и т.д.
+
+Разработчики этого программного обеспечения осведомлены о возможных неэтичных применениях и обязуются принять против этого превентивные меры. Мы продолжим развивать этот проект в позитивном направлении, придерживаясь закона и этики.
+
+Подразумевается, что пользователи этого программного обеспечения будут использовать его ответственно, соблюдая локальное законодательство. Если используется лицо реального человека, пользователь обязан получить согласие заинтересованного лица и четко указать, что это дипфейк при размещении контента в Интернете. **Разработчики и Со-авторы данного программного обеспечения не несут ответственности за действия конечных пользователей.**
+
+Используя данное расширение, вы соглашаетесь не создавать материалы, которые:
+- нарушают какие-либо действующие законы тех или иных государств или международных организаций;
+- причиняют какой-либо вред человеку или лицам;
+- пропагандируют любую информацию (как общедоступную, так и личную) или изображения (как общедоступные, так и личные), которые могут быть направлены на причинение вреда;
+- используются для распространения дезинформации;
+- нацелены на уязвимые группы людей.
+
+Данное программное обеспечение использует предварительно обученные модели `buffalo_l` и `inswapper_128.onnx`, представленные разработчиками [InsightFace](https://github.com/deepinsight/insightface/). Эти модели распространяются при следующих условиях:
+
+[Перевод из текста лицензии insighface](https://github.com/deepinsight/insightface/tree/master/python-package): Предварительно обученные модели InsightFace доступны только для некоммерческих исследовательских целей. Сюда входят как модели с автоматической загрузкой, так и модели, загруженные вручную.
+
+Пользователи данного программного обеспечения должны строго соблюдать данные условия использования. Разработчики и Со-авторы данного программного продукта не несут ответственности за неправильное использование предварительно обученных моделей InsightFace.
+
+Обратите внимание: если вы собираетесь использовать это программное обеспечение в каких-либо коммерческих целях, вам необходимо будет обучить свои собственные модели или найти модели, которые можно использовать в коммерческих целях.
+
+### Хэш файлов моделей
+
+#### Безопасные для использования модели имеют следующий хэш:
+
+inswapper_128.onnx
+```
+MD5:a3a155b90354160350efd66fed6b3d80
+SHA256:e4a3f08c753cb72d04e10aa0f7dbe3deebbf39567d4ead6dce08e98aa49e16af
+```
+
+1k3d68.onnx
+
+```
+MD5:6fb94fcdb0055e3638bf9158e6a108f4
+SHA256:df5c06b8a0c12e422b2ed8947b8869faa4105387f199c477af038aa01f9a45cc
+```
+
+2d106det.onnx
+
+```
+MD5:a3613ef9eb3662b4ef88eb90db1fcf26
+SHA256:f001b856447c413801ef5c42091ed0cd516fcd21f2d6b79635b1e733a7109dbf
+```
+
+det_10g.onnx
+
+```
+MD5:4c10eef5c9e168357a16fdd580fa8371
+SHA256:5838f7fe053675b1c7a08b633df49e7af5495cee0493c7dcf6697200b85b5b91
+```
+
+genderage.onnx
+
+```
+MD5:81c77ba87ab38163b0dec6b26f8e2af2
+SHA256:4fde69b1c810857b88c64a335084f1c3fe8f01246c9a191b48c7bb756d6652fb
+```
+
+w600k_r50.onnx
+
+```
+MD5:80248d427976241cbd1343889ed132b3
+SHA256:4c06341c33c2ca1f86781dab0e829f88ad5b64be9fba56e56bc9ebdefc619e43
+```
+
+**Пожалуйста, сравните хэш, если вы скачиваете данные модели из непроверенных источников**

extensionsa/2-sd-webui-reactor/example/api_example.py

@@ -0,0 +1,108 @@
+import base64, io, requests, json
+from PIL import Image, PngImagePlugin
+from datetime import datetime, date
+
+address = 'http://127.0.0.1:7860'
+input_file = "extensions\sd-webui-reactor\example\IamSFW.jpg" # Input file path
+time = datetime.now()
+today = date.today()
+current_date = today.strftime('%Y-%m-%d')
+current_time = time.strftime('%H-%M-%S')
+output = 'outputs/api/output_'+current_date+'_'+current_time # Output file path + name index
+try:
+    im = Image.open(input_file)
+except Exception as e:
+    print(e)
+finally:
+    print(im)
+
+img_bytes = io.BytesIO()
+im.save(img_bytes, format='PNG')
+img_base64 = base64.b64encode(img_bytes.getvalue()).decode('utf-8')
+
+# ReActor arguments:
+args=[
+    img_base64, #0
+    True, #1 Enable ReActor
+    '0', #2 Comma separated face number(s) from swap-source image
+    '0', #3 Comma separated face number(s) for target image (result)
+    'C:\stable-diffusion-webui\models\insightface\inswapper_128.onnx', #4 model path
+    'CodeFormer', #4 Restore Face: None; CodeFormer; GFPGAN
+    1, #5 Restore visibility value
+    True, #7 Restore face -> Upscale
+    '4x_NMKD-Superscale-SP_178000_G', #8 Upscaler (type 'None' if doesn't need), see full list here: http://127.0.0.1:7860/sdapi/v1/script-info -> reactor -> sec.8
+    1.5, #9 Upscaler scale value
+    1, #10 Upscaler visibility (if scale = 1)
+    False, #11 Swap in source image
+    True, #12 Swap in generated image
+    1, #13 Console Log Level (0 - min, 1 - med or 2 - max)
+    0, #14 Gender Detection (Source) (0 - No, 1 - Female Only, 2 - Male Only)
+    0, #15 Gender Detection (Target) (0 - No, 1 - Female Only, 2 - Male Only)
+    False, #16 Save the original image(s) made before swapping
+    0.8, #17 CodeFormer Weight (0 = maximum effect, 1 = minimum effect), 0.5 - by default
+    False, #18 Source Image Hash Check, True - by default
+    False, #19 Target Image Hash Check, False - by default
+    "CUDA", #20 CPU or CUDA (if you have it), CPU - by default
+    True, #21 Face Mask Correction
+    1, #22 Select Source, 0 - Image, 1 - Face Model, 2 - Source Folder
+    "elena.safetensors", #23 Filename of the face model (from "models/reactor/faces"), e.g. elena.safetensors, don't forger to set #22 to 1
+    "C:\PATH_TO_FACES_IMAGES", #24 The path to the folder containing source faces images, don't forger to set #22 to 2
+    None, #25 skip it for API
+    True, #26 Randomly select an image from the path
+    True, #27 Force Upscale even if no face found
+    0.6, #28 Face Detection Threshold
+    2, #29 Maximum number of faces to detect (0 is unlimited)
+]
+
+# The args for ReActor can be found by 
+# requests.get(url=f'{address}/sdapi/v1/script-info')
+
+prompt = "(8k, best quality, masterpiece, highly detailed:1.1),realistic photo of fantastic happy woman,hairstyle of blonde and red short bob hair,modern clothing,cinematic lightning,film grain,dynamic pose,bokeh,dof"
+
+neg = "ng_deepnegative_v1_75t,(badhandv4:1.2),(worst quality:2),(low quality:2),(normal quality:2),lowres,(bad anatomy),(bad hands),((monochrome)),((grayscale)),(verybadimagenegative_v1.3:0.8),negative_hand-neg,badhandv4,nude,naked,(strabismus),cross-eye,heterochromia,((blurred))"
+
+payload = {
+    "prompt": prompt,
+    "negative_prompt": neg,
+    "seed": -1,
+    "sampler_name": "DPM++ 2M Karras",
+    "steps": 15,
+    "cfg_scale": 7,
+    "width": 512,
+    "height": 768,
+    "restore_faces": False,
+    "alwayson_scripts": {"reactor":{"args":args}}
+}
+
+try:
+    print('Working... Please wait...')
+    result = requests.post(url=f'{address}/sdapi/v1/txt2img', json=payload)
+except Exception as e:
+    print(e)
+finally:
+    print('Done! Saving file...')
+
+if result is not None:
+    r = result.json()
+    n = 0
+
+    for i in r['images']:
+        image = Image.open(io.BytesIO(base64.b64decode(i.split(",",1)[0])))
+
+        png_payload = {
+            "image": "data:image/png;base64," + i
+        }
+        response2 = requests.post(url=f'{address}/sdapi/v1/png-info', json=png_payload)
+
+        pnginfo = PngImagePlugin.PngInfo()
+        pnginfo.add_text("parameters", response2.json().get("info"))
+        output_file = output+'_'+str(n)+'_.png'
+        try:
+            image.save(output_file, pnginfo=pnginfo)
+        except Exception as e:
+            print(e)
+        finally:
+            print(f'{output_file} is saved\nAll is done!')
+        n += 1
+else:
+    print('Something went wrong...')

extensionsa/2-sd-webui-reactor/install.py

@@ -0,0 +1,155 @@
+import subprocess
+import os, sys
+from typing import Any
+import pkg_resources
+from tqdm import tqdm
+import urllib.request
+from packaging import version as pv
+
+try:
+    from modules.paths_internal import models_path
+except:
+    try:
+        from modules.paths import models_path
+    except:
+        models_path = os.path.abspath("models")
+
+
+BASE_PATH = os.path.dirname(os.path.realpath(__file__))
+
+req_file = os.path.join(BASE_PATH, "requirements.txt")
+
+models_dir = os.path.join(models_path, "insightface")
+
+# DEPRECATED:
+# models_dir_old = os.path.join(models_path, "roop")
+# if os.path.exists(models_dir_old):
+#     if not os.listdir(models_dir_old) and (not os.listdir(models_dir) or not os.path.exists(models_dir)):
+#         os.rename(models_dir_old, models_dir)
+#     else:
+#         import shutil
+#         for file in os.listdir(models_dir_old):
+#             shutil.move(os.path.join(models_dir_old, file), os.path.join(models_dir, file))
+#         try:
+#             os.rmdir(models_dir_old)
+#         except Exception as e:
+#             print(f"OSError: {e}")
+            
+model_url = "https://huggingface.co/datasets/Gourieff/ReActor/resolve/main/models/inswapper_128.onnx"
+model_name = os.path.basename(model_url)
+model_path = os.path.join(models_dir, model_name)
+
+def pip_install(*args):
+    subprocess.run([sys.executable, "-m", "pip", "install", *args])
+
+def pip_uninstall(*args):
+    subprocess.run([sys.executable, "-m", "pip", "uninstall", "-y", *args])
+
+def is_installed (
+        package: str, version: str | None = None, strict: bool = True
+):
+    has_package = None
+    try:
+        has_package = pkg_resources.get_distribution(package)
+        if has_package is not None:
+            installed_version = has_package.version
+            if (installed_version != version and strict == True) or (pv.parse(installed_version) < pv.parse(version) and strict == False):
+                return False
+            else:
+                return True
+        else:
+            return False
+    except Exception as e:
+        print(f"Error: {e}")
+        return False
+    
+def download(url, path):
+    request = urllib.request.urlopen(url)
+    total = int(request.headers.get('Content-Length', 0))
+    with tqdm(total=total, desc='Downloading...', unit='B', unit_scale=True, unit_divisor=1024) as progress:
+        urllib.request.urlretrieve(url, path, reporthook=lambda count, block_size, total_size: progress.update(block_size))
+
+if not os.path.exists(models_dir):
+    os.makedirs(models_dir)
+
+if not os.path.exists(model_path):
+    download(model_url, model_path)
+
+# print("ReActor preheating...", end=' ')
+
+last_device = None
+first_run = False
+available_devices = ["CPU", "CUDA"]
+
+try:
+    last_device_log = os.path.join(BASE_PATH, "last_device.txt")
+    with open(last_device_log) as f:
+        last_device = f.readline().strip()
+    if last_device not in available_devices:
+        last_device = None
+except:
+    last_device = "CPU"
+    first_run = True
+    with open(os.path.join(BASE_PATH, "last_device.txt"), "w") as txt:
+        txt.write(last_device)
+
+with open(req_file) as file:
+    install_count = 0
+    ort = "onnxruntime-gpu"
+    import torch
+    cuda_version = None
+    try:
+        if torch.cuda.is_available():
+            cuda_version = torch.version.cuda
+            print(f"CUDA {cuda_version}")
+            if first_run or last_device is None:
+                last_device = "CUDA"
+        elif torch.backends.mps.is_available() or hasattr(torch,'dml') or hasattr(torch,'privateuseone'):
+            ort = "onnxruntime"
+            # to prevent errors when ORT-GPU is installed but we want ORT instead:
+            if first_run:
+                pip_uninstall("onnxruntime", "onnxruntime-gpu")
+            # just in case:
+            if last_device == "CUDA" or last_device is None:
+                last_device = "CPU"
+        else:
+            if last_device == "CUDA" or last_device is None:
+                last_device = "CPU"
+        with open(os.path.join(BASE_PATH, "last_device.txt"), "w") as txt:
+            txt.write(last_device)
+        if cuda_version is not None and float(cuda_version)>=12: # CU12
+            if not is_installed(ort,"1.17.1",False):
+                install_count += 1
+                pip_uninstall("onnxruntime", "onnxruntime-gpu")
+                pip_install(ort,"--extra-index-url","https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/")
+        elif not is_installed(ort,"1.16.1",False):
+            install_count += 1
+            pip_install(ort, "-U")
+    except Exception as e:
+        print(e)
+        print(f"\nERROR: Failed to install {ort} - ReActor won't start")
+        raise e
+    # print(f"Device: {last_device}")
+    strict = True
+    for package in file:
+        package_version = None
+        try:
+            package = package.strip()
+            if "==" in package:
+                package_version = package.split('==')[1]
+            elif ">=" in package:
+                package_version = package.split('>=')[1]
+                strict = False
+            if not is_installed(package,package_version,strict):
+                install_count += 1
+                pip_install(package)
+        except Exception as e:
+            print(e)
+            print(f"\nERROR: Failed to install {package} - ReActor won't start")
+            raise e
+    if install_count > 0:
+        print(f"""
+        +---------------------------------+
+        --- PLEASE, RESTART the Server! ---
+        +---------------------------------+
+        """)

extensionsa/2-sd-webui-reactor/last_device.txt

@@ -0,0 +1 @@
+CUDA

extensionsa/2-sd-webui-reactor/reactor_modules/reactor_mask.py

@@ -0,0 +1,176 @@
+import cv2
+import numpy as np
+from PIL import Image, ImageDraw
+
+from torchvision.transforms.functional import to_pil_image
+
+from scripts.reactor_logger import logger
+from scripts.reactor_inferencers.bisenet_mask_generator import BiSeNetMaskGenerator
+from scripts.reactor_entities.face import FaceArea
+from scripts.reactor_entities.rect import Rect
+
+
+colors = [
+    (255, 0, 0),
+    (0, 255, 0),
+    (0, 0, 255),
+    (255, 255, 0),
+    (255, 0, 255),
+    (0, 255, 255),
+    (255, 255, 255),
+    (128, 0, 0),
+    (0, 128, 0),
+    (128, 128, 0),
+    (0, 0, 128),
+    (0, 128, 128),
+]
+
+def color_generator(colors):
+    while True:
+        for color in colors:
+            yield color
+
+
+def process_face_image(
+        face: FaceArea,
+        **kwargs,
+    ) -> Image:
+        image = np.array(face.image)
+        overlay = image.copy()
+        color_iter = color_generator(colors)
+        cv2.rectangle(overlay, (0, 0), (image.shape[1], image.shape[0]), next(color_iter), -1)
+        l, t, r, b = face.face_area_on_image
+        cv2.rectangle(overlay, (l, t), (r, b), (0, 0, 0), 10)
+        if face.landmarks_on_image is not None:
+            for landmark in face.landmarks_on_image:
+                cv2.circle(overlay, (int(landmark.x), int(landmark.y)), 6, (0, 0, 0), 10)
+        alpha = 0.3
+        output = cv2.addWeighted(image, 1 - alpha, overlay, alpha, 0)
+        
+        return Image.fromarray(output)
+
+
+def apply_face_mask(swapped_image:np.ndarray,target_image:np.ndarray,target_face,entire_mask_image:np.array)->np.ndarray:
+    logger.status("Correcting Face Mask")
+    mask_generator =  BiSeNetMaskGenerator()
+    face = FaceArea(target_image,Rect.from_ndarray(np.array(target_face.bbox)),1.6,512,"")
+    face_image = np.array(face.image)
+    process_face_image(face)
+    face_area_on_image = face.face_area_on_image
+    mask = mask_generator.generate_mask(
+        face_image,
+        face_area_on_image=face_area_on_image,
+        affected_areas=["Face"],
+        mask_size=0,
+        use_minimal_area=True
+    )
+    mask = cv2.blur(mask, (12, 12))
+    # """entire_mask_image = np.zeros_like(target_image)"""
+    larger_mask = cv2.resize(mask, dsize=(face.width, face.height))
+    entire_mask_image[
+        face.top : face.bottom,
+        face.left : face.right,
+    ] = larger_mask
+   
+    result = Image.composite(Image.fromarray(swapped_image),Image.fromarray(target_image), Image.fromarray(entire_mask_image).convert("L"))
+    return np.array(result)
+
+
+def rotate_array(image: np.ndarray, angle: float) -> np.ndarray:
+    if angle == 0:
+        return image
+
+    h, w = image.shape[:2]
+    center = (w // 2, h // 2)
+
+    M = cv2.getRotationMatrix2D(center, angle, 1.0)
+    return cv2.warpAffine(image, M, (w, h))
+
+
+def rotate_image(image: Image, angle: float) -> Image:
+    if angle == 0:
+        return image
+    return Image.fromarray(rotate_array(np.array(image), angle))
+
+
+def correct_face_tilt(angle: float) -> bool:
+    angle = abs(angle)
+    if angle > 180:
+        angle = 360 - angle
+    return angle > 40
+
+
+def _dilate(arr: np.ndarray, value: int) -> np.ndarray:
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
+    return cv2.dilate(arr, kernel, iterations=1)
+
+
+def _erode(arr: np.ndarray, value: int) -> np.ndarray:
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
+    return cv2.erode(arr, kernel, iterations=1)
+
+
+def dilate_erode(img: Image.Image, value: int) -> Image.Image:
+    """
+    The dilate_erode function takes an image and a value.
+    If the value is positive, it dilates the image by that amount.
+    If the value is negative, it erodes the image by that amount.
+
+    Parameters
+    ----------
+        img: PIL.Image.Image
+            the image to be processed
+        value: int
+            kernel size of dilation or erosion
+
+    Returns
+    -------
+        PIL.Image.Image
+            The image that has been dilated or eroded
+    """
+    if value == 0:
+        return img
+
+    arr = np.array(img)
+    arr = _dilate(arr, value) if value > 0 else _erode(arr, -value)
+
+    return Image.fromarray(arr)
+
+def mask_to_pil(masks, shape: tuple[int, int]) -> list[Image.Image]:
+    """
+    Parameters
+    ----------
+    masks: torch.Tensor, dtype=torch.float32, shape=(N, H, W).
+        The device can be CUDA, but `to_pil_image` takes care of that.
+
+    shape: tuple[int, int]
+        (width, height) of the original image
+    """
+    n = masks.shape[0]
+    return [to_pil_image(masks[i], mode="L").resize(shape) for i in range(n)]
+
+def create_mask_from_bbox(
+    bboxes: list[list[float]], shape: tuple[int, int]
+) -> list[Image.Image]:
+    """
+    Parameters
+    ----------
+        bboxes: list[list[float]]
+            list of [x1, y1, x2, y2]
+            bounding boxes
+        shape: tuple[int, int]
+            shape of the image (width, height)
+
+    Returns
+    -------
+        masks: list[Image.Image]
+        A list of masks
+
+    """
+    masks = []
+    for bbox in bboxes:
+        mask = Image.new("L", shape, 0)
+        mask_draw = ImageDraw.Draw(mask)
+        mask_draw.rectangle(bbox, fill=255)
+        masks.append(mask)
+    return masks

extensionsa/2-sd-webui-reactor/reactor_ui/__init__.py

@@ -0,0 +1,5 @@
+import reactor_ui.reactor_upscale_ui as ui_upscale
+import reactor_ui.reactor_tools_ui as ui_tools
+import reactor_ui.reactor_settings_ui as ui_settings
+import reactor_ui.reactor_main_ui as ui_main
+import reactor_ui.reactor_detection_ui as ui_detection

extensionsa/2-sd-webui-reactor/reactor_ui/reactor_detection_ui.py

@@ -0,0 +1,54 @@
+import gradio as gr
+from scripts.reactor_swapper import (
+    clear_faces,
+    clear_faces_list,
+    clear_faces_target,
+    clear_faces_all
+)
+
+# TAB DETECTION
+def show(show_br: bool = True):
+    with gr.Tab("Detection"):
+        with gr.Row():
+            det_thresh = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.5,
+                step=0.01,
+                label="Threshold",
+                info="The higher the value, the more sensitive the detection is to what is considered a face (0.5 by default)",
+                scale=2
+            )
+            det_maxnum = gr.Slider(
+                minimum=0,
+                maximum=20,
+                value=0,
+                step=1,
+                label="Max Faces",
+                info="Maximum number of faces to detect (0 is unlimited)",
+                scale=1
+            )
+        # gr.Markdown("<br>", visible=show_br)
+        gr.Markdown("Hashed images get processed with previously set detection parameters (the face is hashed with all available parameters to bypass the analyzer and speed up the process). Please clear the hash if you want to apply new detection settings.", visible=show_br)
+        with gr.Row():
+            imgs_hash_clear_single = gr.Button(
+                value="Clear Source Images Hash (Single)",
+                scale=1
+            )
+            imgs_hash_clear_multiple = gr.Button(
+                value="Clear Source Images Hash (Multiple)",
+                scale=1
+            )
+            imgs_hash_clear_target = gr.Button(
+                value="Clear Target Image Hash",
+                scale=1
+            )
+            imgs_hash_clear_all = gr.Button(
+                value="Clear All Hash"
+            )
+        progressbar_area = gr.Markdown("")
+        imgs_hash_clear_single.click(clear_faces,None,[progressbar_area])
+        imgs_hash_clear_multiple.click(clear_faces_list,None,[progressbar_area])
+        imgs_hash_clear_target.click(clear_faces_target,None,[progressbar_area])
+        imgs_hash_clear_all.click(clear_faces_all,None,[progressbar_area])
+    return det_thresh, det_maxnum

extensionsa/2-sd-webui-reactor/reactor_ui/reactor_main_ui.py

@@ -0,0 +1,229 @@
+import gradio as gr
+from scripts.reactor_helpers import (
+    get_model_names, 
+    get_facemodels
+)
+from scripts.reactor_swapper import (
+    clear_faces_list,
+)
+from modules import shared
+
+# SAVE_ORIGINAL: bool = False
+
+def update_fm_list(selected: str):
+    try: # GR3.x
+        return gr.Dropdown.update(
+            value=selected, choices=get_model_names(get_facemodels)
+        )
+    except: # GR4.x
+        return gr.Dropdown(
+            value=selected, choices=get_model_names(get_facemodels)
+        )
+
+# TAB MAIN
+def show(is_img2img: bool, show_br: bool = True, **msgs):
+
+    # def on_select_source(selected: bool, evt: gr.SelectData):
+    def on_select_source(evt: gr.SelectData):
+        # global SAVE_ORIGINAL
+        if evt.index == 2:
+            # if SAVE_ORIGINAL != selected:
+            #     SAVE_ORIGINAL = selected
+            try: # GR3.x
+                return {
+                    control_col_1: gr.Column.update(visible=False),
+                    control_col_2: gr.Column.update(visible=False),
+                    control_col_3: gr.Column.update(visible=True),
+                    # save_original: gr.Checkbox.update(value=False,visible=False),
+                    imgs_hash_clear: gr.Button.update(visible=True)
+                }
+            except: # GR4.x
+                return {
+                    control_col_1: gr.Column(visible=False),
+                    control_col_2: gr.Column(visible=False),
+                    control_col_3: gr.Column(visible=True),
+                    # save_original: gr.Checkbox.update(value=False,visible=False),
+                    imgs_hash_clear: gr.Button(visible=True)
+                }
+        if evt.index == 0:
+            try: # GR3.x
+                return {
+                    control_col_1: gr.Column.update(visible=True),
+                    control_col_2: gr.Column.update(visible=False),
+                    control_col_3: gr.Column.update(visible=False),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                    imgs_hash_clear: gr.Button.update(visible=False)
+                }
+            except: # GR4.x
+                return {
+                    control_col_1: gr.Column(visible=True),
+                    control_col_2: gr.Column(visible=False),
+                    control_col_3: gr.Column(visible=False),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                    imgs_hash_clear: gr.Button(visible=False)
+                }
+        if evt.index == 1:
+            try: # GR3.x
+                return {
+                    control_col_1: gr.Column.update(visible=False),
+                    control_col_2: gr.Column.update(visible=True),
+                    control_col_3: gr.Column.update(visible=False),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                    imgs_hash_clear: gr.Button.update(visible=False)
+                }
+            except: # GR4.x
+                return {
+                    control_col_1: gr.Column(visible=False),
+                    control_col_2: gr.Column(visible=True),
+                    control_col_3: gr.Column(visible=False),
+                    # save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
+                    imgs_hash_clear: gr.Button(visible=False)
+                }
+        
+    progressbar_area = gr.Markdown("")
+    with gr.Tab("Main"):
+        with gr.Column():
+            with gr.Row():
+                select_source = gr.Radio(
+                    ["Image(s)","Face Model","Folder"],
+                    value="Image(s)",
+                    label="Select Source",
+                    type="index",
+                    scale=1,
+                )
+                with gr.Column(visible=False) as control_col_2:
+                    with gr.Row():
+                        face_models = get_model_names(get_facemodels)
+                        face_model = gr.Dropdown(
+                            choices=face_models,
+                            label="Choose Face Model",
+                            value="None",
+                            scale=1,
+                        )
+                        fm_update = gr.Button(
+                            value="🔄",
+                            variant="tool",
+                        )
+                        fm_update.click(
+                            update_fm_list, 
+                            inputs=[face_model],
+                            outputs=[face_model],
+                        )
+                imgs_hash_clear = gr.Button(
+                    value="Clear Source Images Hash",
+                    scale=1,
+                    visible=False,
+                )
+                imgs_hash_clear.click(clear_faces_list,None,[progressbar_area])
+            gr.Markdown("<br>", visible=show_br)
+            with gr.Column(visible=True) as control_col_1:
+                with gr.Row():
+                    selected_tab = gr.Textbox('tab_single', visible=False)
+                    with gr.Tabs() as tab_single:
+                        with gr.Tab('Single'):
+                            img = gr.Image(
+                                type="pil",
+                                label="Single Source Image",
+                            )
+                        with gr.Tab('Multiple') as tab_multiple:
+                            imgs = gr.Files(
+                                label=f"Multiple Source Images{msgs['extra_multiple_source']}",
+                                file_types=["image"],
+                            )
+                    tab_single.select(fn=lambda: 'tab_single', inputs=[], outputs=[selected_tab])
+                    tab_multiple.select(fn=lambda: 'tab_multiple', inputs=[], outputs=[selected_tab])
+            with gr.Column(visible=False) as control_col_3:
+                gr.Markdown("<span style='display:block;text-align:right;padding-right:3px;margin: -15px 0;font-size:1.1em'><sup>Clear Hash if you see the previous face was swapped instead of the new one</sup></span>")
+                with gr.Row():
+                    source_folder = gr.Textbox(
+                        value="",
+                        placeholder="Paste here the path to the folder containing source faces images",
+                        label=f"Source Folder{msgs['extra_multiple_source']}",
+                        scale=2,
+                    )
+                    random_image = gr.Checkbox(
+                        False,
+                        label="Random Image",
+                        info="Randomly select an image from the path",
+                        scale=1,
+                    )
+            setattr(face_model, "do_not_save_to_config", True)
+            if is_img2img:
+                save_original = gr.Checkbox(
+                    False,
+                    label="Save Original (Swap in generated only)", 
+                    info="Save the original image(s) made before swapping"
+                )
+            else:
+                save_original = gr.Checkbox(
+                    False,
+                    label="Save Original", 
+                    info="Save the original image(s) made before swapping",
+                    visible=show_br
+                )
+            # imgs.upload(on_files_upload_uncheck_so,[save_original],[save_original],show_progress=False)
+            # imgs.clear(on_files_clear,None,[save_original],show_progress=False)
+            imgs.clear(clear_faces_list,None,None,show_progress=False)
+            mask_face = gr.Checkbox(
+                False,
+                label="Face Mask Correction", 
+                info="Apply this option if you see some pixelation around face contours"
+            )
+            gr.Markdown("<br>", visible=show_br)
+            gr.Markdown("Source Image (above):")
+            with gr.Row():
+                source_faces_index = gr.Textbox(
+                    value="0",
+                    placeholder="Which face(s) to use as Source (comma separated)",
+                    label="Comma separated face number(s); Example: 0,2,1",
+                )
+                gender_source = gr.Radio(
+                    ["No", "Female Only", "Male Only"],
+                    value="No",
+                    label="Gender Detection (Source)",
+                    type="index",
+                )
+            gr.Markdown("<br>", visible=show_br)
+            gr.Markdown("Target Image (result):")
+            with gr.Row():
+                faces_index = gr.Textbox(
+                    value="0",
+                    placeholder="Which face(s) to Swap into Target (comma separated)",
+                    label="Comma separated face number(s); Example: 1,0,2",
+                )
+                gender_target = gr.Radio(
+                    ["No", "Female Only", "Male Only"],
+                    value="No",
+                    label="Gender Detection (Target)",
+                    type="index",
+                )
+            gr.Markdown("<br>", visible=show_br)
+            with gr.Row():
+                face_restorer_name = gr.Radio(
+                    label="Restore Face",
+                    choices=["None"] + [x.name() for x in shared.face_restorers],
+                    value=shared.face_restorers[0].name(),
+                    type="value",
+                )
+                with gr.Column():
+                    face_restorer_visibility = gr.Slider(
+                        0, 1, 1, step=0.1, label="Restore Face Visibility"
+                    )
+                    codeformer_weight = gr.Slider(
+                        0, 1, 0.5, step=0.1, label="CodeFormer Weight (Fidelity)", info="0 = far from original (max restoration), 1 = close to original (min restoration)"
+                    )
+            gr.Markdown("<br>", visible=show_br)
+            swap_in_source = gr.Checkbox(
+                False,
+                label="Swap in source image",
+                visible=is_img2img,
+            )
+            swap_in_generated = gr.Checkbox(
+                True,
+                label="Swap in generated image",
+                visible=is_img2img,
+            )
+    # select_source.select(on_select_source,[save_original],[control_col_1,control_col_2,control_col_3,save_original,imgs_hash_clear],show_progress=False)
+    select_source.select(on_select_source,None,[control_col_1,control_col_2,control_col_3,imgs_hash_clear],show_progress=False)
+
+    return img, imgs, selected_tab, select_source, face_model, source_folder, save_original, mask_face, source_faces_index, gender_source, faces_index, gender_target, face_restorer_name, face_restorer_visibility, codeformer_weight, swap_in_source, swap_in_generated, random_image

extensionsa/2-sd-webui-reactor/reactor_ui/reactor_settings_ui.py

@@ -0,0 +1,77 @@
+import gradio as gr
+from scripts.reactor_logger import logger
+from scripts.reactor_helpers import get_models, set_Device
+from scripts.reactor_globals import DEVICE, DEVICE_LIST
+try:
+    import torch.cuda as cuda
+    EP_is_visible = True if cuda.is_available() else False
+except:
+    EP_is_visible = False
+
+def update_models_list(selected: str):
+    return gr.Dropdown.update(
+        value=selected, choices=get_models()
+    )
+
+def show(hash_check_block: bool = True):
+    # TAB SETTINGS
+    with gr.Tab("Settings"):
+        models = get_models()
+        with gr.Row(visible=EP_is_visible):
+            device = gr.Radio(
+                label="Execution Provider",
+                choices=DEVICE_LIST,
+                value=DEVICE,
+                type="value",
+                info="Click 'Save' to apply. If you already run 'Generate' - RESTART is required: (A1111) Extensions Tab -> 'Apply and restart UI' or (SD.Next) close the Server and start it again",
+                scale=2,
+            )
+            save_device_btn = gr.Button("Save", scale=0)
+        save = gr.Markdown("", visible=EP_is_visible)
+        setattr(device, "do_not_save_to_config", True)
+        save_device_btn.click(
+            set_Device,
+            inputs=[device],
+            outputs=[save],
+        )
+        with gr.Row():
+            if len(models) == 0:
+                logger.warning(
+                    "You should at least have one model in models directory, please read the doc here: https://github.com/Gourieff/sd-webui-reactor/"
+                )
+                model = gr.Dropdown(
+                    choices=models,
+                    label="Model not found, please download one and refresh the list"
+                )
+            else:
+                model = gr.Dropdown(
+                    choices=models, label="Model", value=models[0]
+                )
+            models_update = gr.Button(
+                value="🔄",
+                variant="tool",
+            )
+            models_update.click(
+                update_models_list, 
+                inputs=[model],
+                outputs=[model],
+            )
+            console_logging_level = gr.Radio(
+                ["No log", "Minimum", "Default"],
+                value="Minimum",
+                label="Console Log Level",
+                type="index"
+            )
+        gr.Markdown("<br>", visible=hash_check_block)
+        with gr.Row(visible=hash_check_block):
+            source_hash_check = gr.Checkbox(
+                True,
+                label="Source Image Hash Check",
+                info="Recommended to keep it ON. Processing is faster when Source Image is the same."
+            )
+            target_hash_check = gr.Checkbox(
+                False,
+                label="Target Image Hash Check",
+                info="Affects if you use Extras tab or img2img with only 'Swap in source image' on."
+            )
+    return model, device, console_logging_level, source_hash_check, target_hash_check

extensionsa/2-sd-webui-reactor/reactor_ui/reactor_tools_ui.py

@@ -0,0 +1,61 @@
+import gradio as gr
+from scripts.reactor_swapper import build_face_model, blend_faces
+
+# TAB TOOLS
+def show():
+    with gr.Tab("Tools"):
+        with gr.Tab("Face Models"):
+
+            with gr.Tab("Single"):
+                gr.Markdown("Load an image containing one person, name it and click 'Build and Save'")
+                img_fm = gr.Image(
+                    type="pil",
+                    label="Load an Image to build -Face Model-",
+                )
+                with gr.Row(equal_height=True):
+                    fm_name = gr.Textbox(
+                        value="",
+                        placeholder="Please type any name (e.g. Elena)",
+                        label="Face Model Name",
+                    )
+                    save_fm_btn = gr.Button("Build and Save")
+                save_fm = gr.Markdown("You can find saved models in 'models/reactor/faces'")
+                save_fm_btn.click(
+                    build_face_model,
+                    inputs=[img_fm, fm_name],
+                    outputs=[save_fm],
+                )
+            
+            with gr.Tab("Blend"):
+                gr.Markdown("Load a set of images containing any person, name it and click 'Build and Save'")
+                with gr.Row():
+                    imgs_fm = gr.Files(
+                        label=f"Load Images to build -Blended Face Model-",
+                        file_types=["image"]
+                    )
+                    with gr.Column():
+                        compute_method = gr.Radio(
+                            ["Mean", "Median", "Mode"],
+                            value="Mean",
+                            label="Compute Method",
+                            type="index",
+                            info="Mean (recommended) - Average value (best result 👍); Median* - Mid-point value (may be funny 😅); Mode - Most common value (may be scary 😨); *Mean and Median will be similar if you load two images"
+                        )
+                        shape_check = gr.Checkbox(
+                            False,
+                            label="Check -Embedding Shape- on Similarity",
+                            info="(Experimental) Turn it ON if you want to skip the faces which are too much different from the first one in the list to prevent some probable 'shape mismatches'"
+                        )
+                with gr.Row(equal_height=True):
+                    fm_name = gr.Textbox(
+                        value="",
+                        placeholder="Please type any name (e.g. Elena)",
+                        label="Face Model Name",
+                    )
+                    save_fm_btn = gr.Button("Build and Save")
+                save_fm = gr.Markdown("You can find saved models in 'models/reactor/faces'")
+                save_fm_btn.click(
+                    blend_faces,
+                    inputs=[imgs_fm, fm_name, compute_method, shape_check],
+                    outputs=[save_fm],
+                )

extensionsa/2-sd-webui-reactor/reactor_ui/reactor_upscale_ui.py

@@ -0,0 +1,47 @@
+import gradio as gr
+from modules import shared
+
+def update_upscalers_list(selected: str):
+    return gr.Dropdown.update(
+        value=selected, choices=[upscaler.name for upscaler in shared.sd_upscalers]
+    )
+
+# TAB UPSCALE
+def show(show_br: bool = True):
+    with gr.Tab("Upscale"):
+        with gr.Row():
+            restore_first = gr.Checkbox(
+                True,
+                label="1. Restore Face -> 2. Upscale (-Uncheck- if you want vice versa)",
+                info="Postprocessing Order",
+                scale=2
+            )
+            upscale_force = gr.Checkbox(
+                False,
+                label="Force Upscale",
+                info="Upscale anyway - even if no face found",
+                scale=1
+            )
+        with gr.Row():
+            upscaler_name = gr.Dropdown(
+                choices=[upscaler.name for upscaler in shared.sd_upscalers],
+                label="Upscaler",
+                value="None",
+                info="Won't scale if you choose -Swap in Source- via img2img, only 1x-postprocessing will affect (texturing, denoising, restyling etc.)"
+            )
+            upscalers_update = gr.Button(
+                value="🔄",
+                variant="tool",
+            )
+        upscalers_update.click(
+            update_upscalers_list, 
+            inputs=[upscaler_name],
+            outputs=[upscaler_name],
+        )
+        gr.Markdown("<br>", visible=show_br)
+        with gr.Row():
+            upscaler_scale = gr.Slider(1, 8, 1, step=0.1, label="Scale by")
+            upscaler_visibility = gr.Slider(
+                0, 1, 1, step=0.1, label="Upscaler Visibility (if scale = 1)"
+            )
+    return restore_first, upscaler_name, upscaler_scale, upscaler_visibility, upscale_force

extensionsa/2-sd-webui-reactor/requirements.txt

@@ -0,0 +1,4 @@
+albumentations==1.4.3
+insightface==0.7.3
+onnx>=1.14.0
+opencv-python>=4.7.0.72