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AUTOMATIC1111
GitHub Repository: AUTOMATIC1111/stable-diffusion-webui
Path: blob/master/extensions-builtin/postprocessing-for-training/scripts/postprocessing_split_oversized.py
2448 views
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import math
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from modules import scripts_postprocessing, ui_components
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import gradio as gr
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def split_pic(image, inverse_xy, width, height, overlap_ratio):
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if inverse_xy:
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from_w, from_h = image.height, image.width
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to_w, to_h = height, width
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else:
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from_w, from_h = image.width, image.height
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to_w, to_h = width, height
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h = from_h * to_w // from_w
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if inverse_xy:
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image = image.resize((h, to_w))
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else:
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image = image.resize((to_w, h))
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split_count = math.ceil((h - to_h * overlap_ratio) / (to_h * (1.0 - overlap_ratio)))
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y_step = (h - to_h) / (split_count - 1)
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for i in range(split_count):
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y = int(y_step * i)
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if inverse_xy:
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splitted = image.crop((y, 0, y + to_h, to_w))
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else:
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splitted = image.crop((0, y, to_w, y + to_h))
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yield splitted
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class ScriptPostprocessingSplitOversized(scripts_postprocessing.ScriptPostprocessing):
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name = "Split oversized images"
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order = 4000
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def ui(self):
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with ui_components.InputAccordion(False, label="Split oversized images") as enable:
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with gr.Row():
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split_threshold = gr.Slider(label='Threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_split_threshold")
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overlap_ratio = gr.Slider(label='Overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="postprocess_overlap_ratio")
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return {
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"enable": enable,
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"split_threshold": split_threshold,
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"overlap_ratio": overlap_ratio,
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}
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def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, split_threshold, overlap_ratio):
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if not enable:
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return
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width = pp.shared.target_width
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height = pp.shared.target_height
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if not width or not height:
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return
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if pp.image.height > pp.image.width:
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ratio = (pp.image.width * height) / (pp.image.height * width)
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inverse_xy = False
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else:
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ratio = (pp.image.height * width) / (pp.image.width * height)
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inverse_xy = True
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if ratio >= 1.0 or ratio > split_threshold:
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return
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result, *others = split_pic(pp.image, inverse_xy, width, height, overlap_ratio)
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pp.image = result
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pp.extra_images = [pp.create_copy(x) for x in others]
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