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Implement #16
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,109 @@ | ||
| import modules.scripts as scripts | ||
| import gradio as gr | ||
| import numpy as np | ||
| import cv2 as cv | ||
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| from modules.processing import process_images, get_fixed_seed | ||
| from copy import copy | ||
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| # https://docs.opencv.org/4.8.0/d2/df0/tutorial_py_hdr.html | ||
| def merge_HDR(imgs:list, path:str, depth:str, fmt:str, gamma:float): | ||
| import datetime | ||
| import math | ||
| import os | ||
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| output_folder = os.path.join(path, 'hdr') | ||
| if not os.path.exists(output_folder): | ||
| 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() | ||
| hdr = merge.process(imgs_np) | ||
| hdr += math.ceil(0 - np.min(hdr) * 1000) / 1000 | ||
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| #print(f'{np.min(hdr)}, {np.max(hdr)}') | ||
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| target = (65535 if depth == '16bpc' else 255) | ||
| 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) | ||
| rgb = cv.cvtColor(ldr, cv.COLOR_BGR2RGB) | ||
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| cv.imwrite(os.path.join(output_folder, f'{datetime.datetime.now().strftime("%H-%M-%S")}{fmt}'), rgb) | ||
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| class VectorHDR(scripts.Script): | ||
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| def title(self): | ||
| return "High Dynamic Range" | ||
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| def show(self, is_img2img): | ||
| return True | ||
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| def ui(self, is_img2img): | ||
| with gr.Row(): | ||
| count = gr.Slider(label="Brackets", minimum=3, maximum=9, step=2, value=7) | ||
| gap = gr.Slider(label="Gaps", minimum=0.50, maximum=2.50, step=0.25, value=1.50) | ||
|
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| with gr.Accordion("Merge Options", elem_id='vec-hdr-' + ('img' if is_img2img else 'txt'), open=False): | ||
| auto = gr.Checkbox(label="Automatically Merge", value=True) | ||
|
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| with gr.Row(): | ||
| depth = gr.Radio(['16bpc', '8bpc'], label="Bit Depth", value="16bpc") | ||
| fmt = gr.Radio(['.tiff', '.png'], label="Image Format", value=".tiff") | ||
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| gamma = gr.Slider(label="Gamma", info='Lower: Darker | Higher: Brighter',minimum=0.2, maximum=2.2, step=0.2, value=1.2) | ||
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| return [count, gap, auto, depth, fmt, gamma] | ||
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| def run(self, p, count:int, gap:float, auto:bool, depth:str, fmt:str, gamma:float): | ||
| center = count // 2 | ||
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| p.seed = get_fixed_seed(p.seed) | ||
| p.scripts.script('vectorscope cc').xyzCache.update({ | ||
| 'Enable':'True', | ||
| 'Alt':'True', | ||
| 'Skip': 0, | ||
| 'Brightness': 0, | ||
| 'DoHR': 'False', | ||
| 'Method': 'Ones', | ||
| 'Scaling': '1 - Cos' | ||
| }) | ||
|
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| baseline = process_images(p) | ||
| pc = copy(p) | ||
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| imgs = [None] * count | ||
| imgs[center] = baseline.images[0] | ||
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| brackets = brightness_brackets(count, gap) | ||
|
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| for it in range(count): | ||
| if it == center: | ||
| continue | ||
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| pc.scripts.script('vectorscope cc').xyzCache.update({ | ||
| 'Enable':'True', | ||
| 'Alt':'True', | ||
| 'Skip': 0, | ||
| 'Brightness': brackets[it], | ||
| 'DoHR': 'False', | ||
| 'Method': 'Ones', | ||
| 'Scaling': '1 - Cos' | ||
| }) | ||
|
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| proc = process_images(pc) | ||
| imgs[it] = proc.images[0] | ||
|
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| if not auto: | ||
| baseline.images = imgs | ||
| return baseline | ||
| else: | ||
| merge_HDR(imgs, p.outpath_samples, depth, fmt, gamma) | ||
| return baseline | ||
|
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| def brightness_brackets(count, gap): | ||
| half = count // 2 | ||
| return [gap * (i - half) for i in range(count)] |
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