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| import gradio as gr | |
| from annotator.util import resize_image, HWC3 | |
| model_canny = None | |
| 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] | |
| model_hed = None | |
| 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] | |
| model_pidi = None | |
| 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] | |
| model_mlsd = None | |
| 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] | |
| model_midas = None | |
| 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] | |
| model_zoe = None | |
| 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] | |
| model_normalbae = None | |
| 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] | |
| model_openpose = None | |
| 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] | |
| model_uniformer = None | |
| 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] | |
| model_lineart_anime = None | |
| 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] | |
| model_lineart = None | |
| 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] | |
| model_oneformer_coco = None | |
| 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] | |
| model_oneformer_ade20k = None | |
| 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] | |
| model_content_shuffler = None | |
| 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] | |
| model_color_shuffler = None | |
| 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] | |
| 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]) | |
| 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]) | |
| 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') | |