| import os |
| from PIL import ImageOps |
| from impact.utils import * |
| import latent_preview |
|
|
|
|
| |
| |
| |
| from impact import core |
| |
| import random |
|
|
|
|
| class PreviewBridge: |
| @classmethod |
| def INPUT_TYPES(s): |
| return {"required": { |
| "images": ("IMAGE",), |
| "image": ("STRING", {"default": ""}), |
| }, |
| "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"}, |
| } |
|
|
| RETURN_TYPES = ("IMAGE", "MASK", ) |
|
|
| FUNCTION = "doit" |
|
|
| OUTPUT_NODE = True |
|
|
| CATEGORY = "ImpactPack/Util" |
|
|
| def __init__(self): |
| super().__init__() |
| self.output_dir = folder_paths.get_temp_directory() |
| self.type = "temp" |
| self.prev_hash = None |
|
|
| @staticmethod |
| def load_image(pb_id): |
| is_fail = False |
| if pb_id not in core.preview_bridge_image_id_map: |
| is_fail = True |
|
|
| image_path, ui_item = core.preview_bridge_image_id_map[pb_id] |
|
|
| if not os.path.isfile(image_path): |
| is_fail = True |
|
|
| if not is_fail: |
| i = Image.open(image_path) |
| i = ImageOps.exif_transpose(i) |
| image = i.convert("RGB") |
| image = np.array(image).astype(np.float32) / 255.0 |
| image = torch.from_numpy(image)[None,] |
|
|
| if 'A' in i.getbands(): |
| mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0 |
| mask = 1. - torch.from_numpy(mask) |
| else: |
| mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") |
| else: |
| image = empty_pil_tensor() |
| mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") |
| ui_item = { |
| "filename": 'empty.png', |
| "subfolder": '', |
| "type": 'temp' |
| } |
|
|
| return image, mask.unsqueeze(0), ui_item |
|
|
| def doit(self, images, image, unique_id, prompt=None, extra_pnginfo=None): |
| need_refresh = False |
|
|
| if unique_id not in core.preview_bridge_cache: |
| need_refresh = True |
|
|
| elif core.preview_bridge_cache[unique_id][0] is not images: |
| need_refresh = True |
|
|
| if not need_refresh: |
| pixels, mask, path_item = PreviewBridge.load_image(image) |
| image = [path_item] |
| else: |
| res = nodes.PreviewImage().save_images(images, filename_prefix="PreviewBridge/PB-", prompt=prompt, extra_pnginfo=extra_pnginfo) |
| image2 = res['ui']['images'] |
| pixels = images |
| mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") |
|
|
| path = os.path.join(folder_paths.get_temp_directory(), 'PreviewBridge', image2[0]['filename']) |
| core.set_previewbridge_image(unique_id, path, image2[0]) |
| core.preview_bridge_image_id_map[image] = (path, image2[0]) |
| core.preview_bridge_image_name_map[unique_id, path] = (image, image2[0]) |
| core.preview_bridge_cache[unique_id] = (images, image2) |
|
|
| image = image2 |
|
|
| return { |
| "ui": {"images": image}, |
| "result": (pixels, mask, ), |
| } |
|
|
|
|
| def decode_latent(latent, preview_method, vae_opt=None): |
| if vae_opt is not None: |
| image = nodes.VAEDecode().decode(vae_opt, latent)[0] |
| return image |
|
|
| from comfy.cli_args import LatentPreviewMethod |
| import comfy.latent_formats as latent_formats |
|
|
| if preview_method.startswith("TAE"): |
| decoder_name = None |
|
|
| if preview_method == "TAESD15": |
| decoder_name = "taesd" |
| elif preview_method == 'TAESDXL': |
| decoder_name = "taesdxl" |
| elif preview_method == 'TAESD3': |
| decoder_name = "taesd3" |
|
|
| if decoder_name: |
| vae = nodes.VAELoader().load_vae(decoder_name)[0] |
| image = nodes.VAEDecode().decode(vae, latent)[0] |
| return image |
|
|
| if preview_method == "Latent2RGB-SD15": |
| latent_format = latent_formats.SD15() |
| method = LatentPreviewMethod.Latent2RGB |
| elif preview_method == "Latent2RGB-SDXL": |
| latent_format = latent_formats.SDXL() |
| method = LatentPreviewMethod.Latent2RGB |
| elif preview_method == "Latent2RGB-SD3": |
| latent_format = latent_formats.SD3() |
| method = LatentPreviewMethod.Latent2RGB |
| elif preview_method == "Latent2RGB-SD-X4": |
| latent_format = latent_formats.SD_X4() |
| method = LatentPreviewMethod.Latent2RGB |
| elif preview_method == "Latent2RGB-Playground-2.5": |
| latent_format = latent_formats.SDXL_Playground_2_5() |
| method = LatentPreviewMethod.Latent2RGB |
| elif preview_method == "Latent2RGB-SC-Prior": |
| latent_format = latent_formats.SC_Prior() |
| method = LatentPreviewMethod.Latent2RGB |
| elif preview_method == "Latent2RGB-SC-B": |
| latent_format = latent_formats.SC_B() |
| method = LatentPreviewMethod.Latent2RGB |
| elif preview_method == "Latent2RGB-FLUX.1": |
| latent_format = latent_formats.Flux() |
| method = LatentPreviewMethod.Latent2RGB |
| else: |
| print(f"[Impact Pack] PreviewBridgeLatent: '{preview_method}' is unsupported preview method.") |
| latent_format = latent_formats.SD15() |
| method = LatentPreviewMethod.Latent2RGB |
|
|
| previewer = core.get_previewer("cpu", latent_format=latent_format, force=True, method=method) |
| samples = latent_format.process_in(latent['samples']) |
|
|
| pil_image = previewer.decode_latent_to_preview(samples) |
| pixels_size = pil_image.size[0]*8, pil_image.size[1]*8 |
| resized_image = pil_image.resize(pixels_size, resample=LANCZOS) |
|
|
| return to_tensor(resized_image).unsqueeze(0) |
|
|
|
|
| class PreviewBridgeLatent: |
| @classmethod |
| def INPUT_TYPES(s): |
| return {"required": { |
| "latent": ("LATENT",), |
| "image": ("STRING", {"default": ""}), |
| "preview_method": (["Latent2RGB-SD3", "Latent2RGB-SDXL", "Latent2RGB-SD15", |
| "Latent2RGB-SD-X4", "Latent2RGB-Playground-2.5", |
| "Latent2RGB-SC-Prior", "Latent2RGB-SC-B", |
| "Latent2RGB-FLUX.1", |
| "TAESD3", "TAESDXL", "TAESD15"],), |
| }, |
| "optional": { |
| "vae_opt": ("VAE", ) |
| }, |
| "hidden": {"unique_id": "UNIQUE_ID", "prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, |
| } |
|
|
| RETURN_TYPES = ("LATENT", "MASK", ) |
|
|
| FUNCTION = "doit" |
|
|
| OUTPUT_NODE = True |
|
|
| CATEGORY = "ImpactPack/Util" |
|
|
| def __init__(self): |
| super().__init__() |
| self.output_dir = folder_paths.get_temp_directory() |
| self.type = "temp" |
| self.prev_hash = None |
| self.prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5)) |
|
|
| @staticmethod |
| def load_image(pb_id): |
| is_fail = False |
| if pb_id not in core.preview_bridge_image_id_map: |
| is_fail = True |
|
|
| image_path, ui_item = core.preview_bridge_image_id_map[pb_id] |
|
|
| if not os.path.isfile(image_path): |
| is_fail = True |
|
|
| if not is_fail: |
| i = Image.open(image_path) |
| i = ImageOps.exif_transpose(i) |
| image = i.convert("RGB") |
| image = np.array(image).astype(np.float32) / 255.0 |
| image = torch.from_numpy(image)[None,] |
|
|
| if 'A' in i.getbands(): |
| mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0 |
| mask = 1. - torch.from_numpy(mask) |
| else: |
| mask = None |
| else: |
| image = empty_pil_tensor() |
| mask = None |
| ui_item = { |
| "filename": 'empty.png', |
| "subfolder": '', |
| "type": 'temp' |
| } |
|
|
| return image, mask, ui_item |
|
|
| def doit(self, latent, image, preview_method, vae_opt=None, unique_id=None, prompt=None, extra_pnginfo=None): |
| latent_channels = latent['samples'].shape[1] |
| preview_method_channels = 16 if 'SD3' in preview_method or 'SC-Prior' in preview_method or 'FLUX.1' in preview_method else 4 |
|
|
| if vae_opt is None and latent_channels != preview_method_channels: |
| print(f"[PreviewBridgeLatent] The version of latent is not compatible with preview_method.\nSD3, SD1/SD2, SDXL, SC-Prior, SC-B and FLUX.1 are not compatible with each other.") |
| raise Exception("The version of latent is not compatible with preview_method.<BR>SD3, SD1/SD2, SDXL, SC-Prior, SC-B and FLUX.1 are not compatible with each other.") |
|
|
| need_refresh = False |
|
|
| if unique_id not in core.preview_bridge_cache: |
| need_refresh = True |
|
|
| elif (core.preview_bridge_cache[unique_id][0] is not latent |
| or (vae_opt is None and core.preview_bridge_cache[unique_id][2] is not None) |
| or (vae_opt is None and core.preview_bridge_cache[unique_id][1] != preview_method) |
| or (vae_opt is not None and core.preview_bridge_cache[unique_id][2] is not vae_opt)): |
| need_refresh = True |
|
|
| if not need_refresh: |
| pixels, mask, path_item = PreviewBridge.load_image(image) |
|
|
| if mask is None: |
| mask = torch.ones(latent['samples'].shape[2:], dtype=torch.float32, device="cpu").unsqueeze(0) |
| if 'noise_mask' in latent: |
| res_latent = latent.copy() |
| del res_latent['noise_mask'] |
| else: |
| res_latent = latent |
| else: |
| res_latent = latent.copy() |
| res_latent['noise_mask'] = mask |
|
|
| res_image = [path_item] |
| else: |
| decoded_image = decode_latent(latent, preview_method, vae_opt) |
|
|
| if 'noise_mask' in latent: |
| mask = latent['noise_mask'].squeeze(0) |
|
|
| decoded_pil = to_pil(decoded_image) |
|
|
| inverted_mask = 1 - mask |
| resized_mask = resize_mask(inverted_mask, (decoded_image.shape[1], decoded_image.shape[2])) |
| result_pil = apply_mask_alpha_to_pil(decoded_pil, resized_mask) |
|
|
| full_output_folder, filename, counter, _, _ = folder_paths.get_save_image_path("PreviewBridge/PBL-"+self.prefix_append, folder_paths.get_temp_directory(), result_pil.size[0], result_pil.size[1]) |
| file = f"{filename}_{counter}.png" |
| result_pil.save(os.path.join(full_output_folder, file), compress_level=4) |
| res_image = [{ |
| 'filename': file, |
| 'subfolder': 'PreviewBridge', |
| 'type': 'temp', |
| }] |
| else: |
| mask = torch.ones(latent['samples'].shape[2:], dtype=torch.float32, device="cpu").unsqueeze(0) |
| res = nodes.PreviewImage().save_images(decoded_image, filename_prefix="PreviewBridge/PBL-", prompt=prompt, extra_pnginfo=extra_pnginfo) |
| res_image = res['ui']['images'] |
|
|
| path = os.path.join(folder_paths.get_temp_directory(), 'PreviewBridge', res_image[0]['filename']) |
| core.set_previewbridge_image(unique_id, path, res_image[0]) |
| core.preview_bridge_image_id_map[image] = (path, res_image[0]) |
| core.preview_bridge_image_name_map[unique_id, path] = (image, res_image[0]) |
| core.preview_bridge_cache[unique_id] = (latent, preview_method, vae_opt, res_image) |
|
|
| res_latent = latent |
|
|
| return { |
| "ui": {"images": res_image}, |
| "result": (res_latent, mask, ), |
| } |
|
|
