143 lines
3.9 KiB
Python
143 lines
3.9 KiB
Python
from modules.processing import process_images, get_fixed_seed
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from modules.shared import state
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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 mergeHDR(imgs: list, path: str, depth: str, fmt: str, gamma: float):
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"""https://docs.opencv.org/4.8.0/d2/df0/tutorial_py_hdr.html"""
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import datetime
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import math
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import os
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out_dir = os.path.join(os.path.dirname(path), "hdr")
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os.makedirs(out_dir, exist_ok=True)
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print(f'\nSaving HDR Outputs to "{out_dir}"\n')
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imgs_np = [np.asarray(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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# shift min to 0.0
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hdr += math.ceil(0.0 - 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 = np.uint16 if depth == "16bpc" else np.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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time = datetime.datetime.now().strftime("%H-%M-%S")
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cv.imwrite(os.path.join(out_dir, f"{time}{fmt}"), rgb)
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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(
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label="Brackets",
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minimum=3,
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maximum=9,
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step=2,
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value=5,
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)
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gap = gr.Slider(
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label="Gaps",
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minimum=0.50,
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maximum=2.50,
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step=0.25,
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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: int = count // 2
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brackets = brightness_brackets(count, gap)
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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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for it in range(count):
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if state.skipped or state.interrupted or state.stopping_generation:
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print("HDR Process Skipped...")
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return baseline
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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 auto:
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mergeHDR(imgs, p.outpath_samples, depth, fmt, gamma)
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baseline.images = imgs
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return baseline
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def brightness_brackets(count: int, gap: float) -> list[float]:
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half = count // 2
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return [gap * (i - half) for i in range(count)]
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