| import gradio as gr |
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| from annotator.util import resize_image, HWC3 |
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| model_canny = None |
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| def canny(img, res, l, h): |
| img = resize_image(HWC3(img), res) |
| global model_canny |
| if model_canny is None: |
| from annotator.canny import CannyDetector |
| model_canny = CannyDetector() |
| result = model_canny(img, l, h) |
| return [result] |
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| model_hed = None |
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| def hed(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_hed |
| if model_hed is None: |
| from annotator.hed import HEDdetector |
| model_hed = HEDdetector() |
| result = model_hed(img) |
| return [result] |
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| model_pidi = None |
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| def pidi(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_pidi |
| if model_pidi is None: |
| from annotator.pidinet import PidiNetDetector |
| model_pidi = PidiNetDetector() |
| result = model_pidi(img) |
| return [result] |
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| model_mlsd = None |
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| def mlsd(img, res, thr_v, thr_d): |
| img = resize_image(HWC3(img), res) |
| global model_mlsd |
| if model_mlsd is None: |
| from annotator.mlsd import MLSDdetector |
| model_mlsd = MLSDdetector() |
| result = model_mlsd(img, thr_v, thr_d) |
| return [result] |
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|
| model_midas = None |
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| def midas(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_midas |
| if model_midas is None: |
| from annotator.midas import MidasDetector |
| model_midas = MidasDetector() |
| result = model_midas(img) |
| return [result] |
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|
| model_zoe = None |
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| def zoe(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_zoe |
| if model_zoe is None: |
| from annotator.zoe import ZoeDetector |
| model_zoe = ZoeDetector() |
| result = model_zoe(img) |
| return [result] |
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|
| model_normalbae = None |
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| def normalbae(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_normalbae |
| if model_normalbae is None: |
| from annotator.normalbae import NormalBaeDetector |
| model_normalbae = NormalBaeDetector() |
| result = model_normalbae(img) |
| return [result] |
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| model_openpose = None |
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| def openpose(img, res, hand_and_face): |
| img = resize_image(HWC3(img), res) |
| global model_openpose |
| if model_openpose is None: |
| from annotator.openpose import OpenposeDetector |
| model_openpose = OpenposeDetector() |
| result = model_openpose(img, hand_and_face) |
| return [result] |
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|
| model_uniformer = None |
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| def uniformer(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_uniformer |
| if model_uniformer is None: |
| from annotator.uniformer import UniformerDetector |
| model_uniformer = UniformerDetector() |
| result = model_uniformer(img) |
| return [result] |
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| model_lineart_anime = None |
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| def lineart_anime(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_lineart_anime |
| if model_lineart_anime is None: |
| from annotator.lineart_anime import LineartAnimeDetector |
| model_lineart_anime = LineartAnimeDetector() |
| result = model_lineart_anime(img) |
| return [result] |
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|
| model_lineart = None |
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| def lineart(img, res, coarse=False): |
| img = resize_image(HWC3(img), res) |
| global model_lineart |
| if model_lineart is None: |
| from annotator.lineart import LineartDetector |
| model_lineart = LineartDetector() |
| result = model_lineart(img, coarse) |
| return [result] |
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| model_oneformer_coco = None |
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| def oneformer_coco(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_oneformer_coco |
| if model_oneformer_coco is None: |
| from annotator.oneformer import OneformerCOCODetector |
| model_oneformer_coco = OneformerCOCODetector() |
| result = model_oneformer_coco(img) |
| return [result] |
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|
| model_oneformer_ade20k = None |
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| def oneformer_ade20k(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_oneformer_ade20k |
| if model_oneformer_ade20k is None: |
| from annotator.oneformer import OneformerADE20kDetector |
| model_oneformer_ade20k = OneformerADE20kDetector() |
| result = model_oneformer_ade20k(img) |
| return [result] |
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| model_content_shuffler = None |
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| def content_shuffler(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_content_shuffler |
| if model_content_shuffler is None: |
| from annotator.shuffle import ContentShuffleDetector |
| model_content_shuffler = ContentShuffleDetector() |
| result = model_content_shuffler(img) |
| return [result] |
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| model_color_shuffler = None |
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| def color_shuffler(img, res): |
| img = resize_image(HWC3(img), res) |
| global model_color_shuffler |
| if model_color_shuffler is None: |
| from annotator.shuffle import ColorShuffleDetector |
| model_color_shuffler = ColorShuffleDetector() |
| result = model_color_shuffler(img) |
| return [result] |
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|
| block = gr.Blocks().queue() |
| with block: |
| with gr.Row(): |
| gr.Markdown("## Canny Edge") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| low_threshold = gr.Slider(label="low_threshold", minimum=1, maximum=255, value=100, step=1) |
| high_threshold = gr.Slider(label="high_threshold", minimum=1, maximum=255, value=200, step=1) |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=canny, inputs=[input_image, resolution, low_threshold, high_threshold], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## HED Edge") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=hed, inputs=[input_image, resolution], outputs=[gallery]) |
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|
| with gr.Row(): |
| gr.Markdown("## Pidi Edge") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=pidi, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## MLSD Edge") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| value_threshold = gr.Slider(label="value_threshold", minimum=0.01, maximum=2.0, value=0.1, step=0.01) |
| distance_threshold = gr.Slider(label="distance_threshold", minimum=0.01, maximum=20.0, value=0.1, step=0.01) |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=mlsd, inputs=[input_image, resolution, value_threshold, distance_threshold], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## MIDAS Depth") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=midas, inputs=[input_image, resolution], outputs=[gallery]) |
|
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|
|
| with gr.Row(): |
| gr.Markdown("## Zoe Depth") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=zoe, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Normal Bae") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=normalbae, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Openpose") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| hand_and_face = gr.Checkbox(label='Hand and Face', value=False) |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=openpose, inputs=[input_image, resolution, hand_and_face], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Lineart Anime") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=lineart_anime, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Lineart") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| coarse = gr.Checkbox(label='Using coarse model', value=False) |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=lineart, inputs=[input_image, resolution, coarse], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Uniformer Segmentation") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=uniformer, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Oneformer COCO Segmentation") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=oneformer_coco, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Oneformer ADE20K Segmentation") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=640, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=oneformer_ade20k, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Content Shuffle") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=content_shuffler, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
| with gr.Row(): |
| gr.Markdown("## Color Shuffle") |
| with gr.Row(): |
| with gr.Column(): |
| input_image = gr.Image(source='upload', type="numpy") |
| resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64) |
| run_button = gr.Button(label="Run") |
| with gr.Column(): |
| gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto") |
| run_button.click(fn=color_shuffler, inputs=[input_image, resolution], outputs=[gallery]) |
|
|
|
|
| block.launch(server_name='0.0.0.0') |
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|
