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from modules.processing import process_images, get_fixed_seed |
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from modules import scripts |
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from copy import copy |
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import gradio as gr |
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import numpy as np |
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import cv2 as cv |
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def merge_HDR(imgs: list, path: str, depth: str, fmt: str, gamma: float): |
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import datetime |
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import math |
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import os |
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output_folder = os.path.join(path, "hdr") |
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if not os.path.exists(output_folder): |
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os.makedirs(output_folder) |
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imgs_np = [np.array(img, dtype=np.uint8) for img in imgs] |
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merge = cv.createMergeMertens() |
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hdr = merge.process(imgs_np) |
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hdr += math.ceil(0 - np.min(hdr) * 1000) / 1000 |
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target = 65535 if depth == "16bpc" else 255 |
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precision = "uint16" if depth == "16bpc" else "uint8" |
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hdr = np.power(hdr, (1 / gamma)) |
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ldr = np.clip(hdr * target, 0, target).astype(precision) |
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rgb = cv.cvtColor(ldr, cv.COLOR_BGR2RGB) |
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cv.imwrite( |
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os.path.join( |
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output_folder, f'{datetime.datetime.now().strftime("%H-%M-%S")}{fmt}' |
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), |
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rgb, |
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) |
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class VectorHDR(scripts.Script): |
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def title(self): |
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return "High Dynamic Range" |
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def show(self, is_img2img): |
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return True |
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def ui(self, is_img2img): |
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with gr.Row(): |
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count = gr.Slider(label="Brackets", minimum=3, maximum=9, step=2, value=7) |
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gap = gr.Slider( |
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label="Gaps", minimum=0.50, maximum=2.50, step=0.25, value=1.50 |
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) |
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with gr.Accordion( |
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"Merge Options", |
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elem_id="vec-hdr-" + ("img" if is_img2img else "txt"), |
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open=False, |
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): |
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auto = gr.Checkbox(label="Automatically Merge", value=True) |
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with gr.Row(): |
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depth = gr.Radio(["16bpc", "8bpc"], label="Bit Depth", value="16bpc") |
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fmt = gr.Radio([".tiff", ".png"], label="Image Format", value=".tiff") |
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gamma = gr.Slider( |
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label="Gamma", |
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info="Lower: Darker | Higher: Brighter", |
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minimum=0.2, |
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maximum=2.2, |
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step=0.2, |
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value=1.2, |
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) |
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for comp in [count, gap, auto, depth, fmt, gamma]: |
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comp.do_not_save_to_config = True |
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return [count, gap, auto, depth, fmt, gamma] |
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def run( |
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self, p, count: int, gap: float, auto: bool, depth: str, fmt: str, gamma: float |
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): |
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center = count // 2 |
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p.seed = get_fixed_seed(p.seed) |
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p.scripts.script("vectorscope cc").xyzCache.update( |
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{ |
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"Enable": "True", |
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"Alt": "True", |
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"Brightness": 0, |
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"DoHR": "False", |
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"Method": "Ones", |
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"Scaling": "1 - Cos", |
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} |
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) |
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baseline = process_images(p) |
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pc = copy(p) |
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imgs = [None] * count |
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imgs[center] = baseline.images[0] |
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brackets = brightness_brackets(count, gap) |
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for it in range(count): |
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if it == center: |
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continue |
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pc.scripts.script("vectorscope cc").xyzCache.update( |
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{"Brightness": brackets[it]} |
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) |
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proc = process_images(pc) |
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imgs[it] = proc.images[0] |
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if not auto: |
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baseline.images = imgs |
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return baseline |
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else: |
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merge_HDR(imgs, p.outpath_samples, depth, fmt, gamma) |
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return baseline |
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def brightness_brackets(count, gap): |
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half = count // 2 |
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return [gap * (i - half) for i in range(count)] |
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