129 lines
3.6 KiB
Python
129 lines
3.6 KiB
Python
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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# https://docs.opencv.org/4.8.0/d2/df0/tutorial_py_hdr.html
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def merge_HDR(imgs: list, path: str, depth: str, fmt: str, gamma: float) -> np.ndarray:
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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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os.makedirs(output_folder, exist_ok=True)
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imgs_np = [np.asarray(img).astype(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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# print(f'{np.min(hdr)}, {np.max(hdr)}')
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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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return ldr
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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=5)
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gap = gr.Slider(
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label="Gaps", minimum=0.50, maximum=2.50, step=0.25, value=1.25
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)
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with gr.Accordion(
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"Merge Options",
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elem_id=f'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({"Enable": "False"})
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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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{
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"Enable": "True",
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"Alt": "True",
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"Brightness": brackets[it],
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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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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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else:
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baseline.images = [merge_HDR(imgs, p.outpath_samples, depth, fmt, gamma)]
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return baseline
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def brightness_brackets(count: int, gap: int) -> list[int]:
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half = count // 2
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return [gap * (i - half) for i in range(count)]
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