add examples
Browse files- .gitignore +4 -0
- app.py +69 -48
- requirements.txt +1 -1
.gitignore
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.idea/
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.idea/
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backs/
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gray/
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lowres/
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scratch/
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app.py
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import gradio as gr
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from gradio_client import Client
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clientGFPGAN = Client("leonelhs/GFPGAN")
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clientSuperface = Client("leonelhs/superface")
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clientZeroBackground = Client("leonelhs/ZeroBackground")
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clientFaceParser = Client("leonelhs/faceparser")
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def gfpgan_face(image):
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return x
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footer = r"""
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<center>
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<p>This App is running on a CPU, help us to upgrade a GPU or just give us a <a href='https://github.com/leonelhs/face-shine' target='_blank'>Github ⭐</a></p>
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<center><span>[email protected]</span></center>
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"""
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with gr.Blocks() as app:
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gr.Request()
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with gr.Row():
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gr.HTML("<center><h1>Face Shine</h1></center>")
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with gr.
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with gr.
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with gr.
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with gr.
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gr.
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with gr.
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btn_hires.click(enhance_face, inputs=[img_input, restorer, enhancer, rescale],
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outputs=[img_output, text_logger])
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with gr.Row():
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gr.HTML(footer)
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app.launch(share=False, debug=True, enable_queue=True)
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import zipfile
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from pathlib import Path
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import gradio as gr
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from gradio_client import Client
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from huggingface_hub import hf_hub_download
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clientGFPGAN = Client("leonelhs/GFPGAN")
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clientSuperface = Client("leonelhs/superface")
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clientZeroBackground = Client("leonelhs/ZeroBackground")
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clientFaceParser = Client("leonelhs/faceparser")
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REPO_ID = "leonelhs/faceshine"
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def download(file):
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file_zip = hf_hub_download(repo_id=REPO_ID, filename=file + ".zip")
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with zipfile.ZipFile(file_zip, "r") as zip_ref:
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zip_ref.extractall(file)
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return list(Path(file).iterdir())
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def gfpgan_face(image):
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return x
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def active_first():
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return gr.Tabs.update(selected=0)
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footer = r"""
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<center>
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<p>This App is running on a CPU, help us to upgrade a GPU or just give us a <a href='https://github.com/leonelhs/face-shine' target='_blank'>Github ⭐</a></p>
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<center><span>[email protected]</span></center>
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"""
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with gr.Blocks(title="Face Shine") as app:
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with gr.Row():
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gr.HTML("<center><h1>Face Shine</h1></center>")
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with gr.Tabs() as tabs:
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with gr.TabItem("Photo restorer", id=0):
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with gr.Row():
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with gr.Column(scale=1):
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btn_hires = gr.Button(value="Enhance resolution")
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btn_eraser = gr.Button(value="Erase scratches")
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btn_color = gr.Button(value="Colorize photo")
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btn_light = gr.Button(value="Enhance light")
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with gr.Accordion("New background", open=False):
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img_newbgr = gr.Image(label="Left empty for a transparent background", type="filepath")
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btn_newbgr = gr.Button(value="Clear background")
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with gr.Column(scale=4):
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with gr.Row():
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img_input = gr.Image(label="Input", type="filepath")
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img_output = gr.Image(label="Result", type="filepath", interactive=False)
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with gr.Row():
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gr.ClearButton([img_input, img_output, img_newbgr], variant="stop")
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btn_swap = gr.Button(value="Swap images", variant="primary")
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with gr.TabItem("Examples", id=1):
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gr.Examples(examples=download("lowres"), inputs=[img_input], label="Low resolution")
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gr.Examples(examples=download("gray"), inputs=[img_input], label="Gray scale")
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gr.Examples(examples=download("scratch"), inputs=[img_input], label="Scratched")
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gr.Examples(examples=download("backs"), inputs=[img_newbgr], label="Backgrounds")
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gr.Button(value="Ok", variant="primary").click(active_first, None, tabs)
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with gr.TabItem("Settings", id=2):
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with gr.Accordion("Image restoration settings", open=False):
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restorer = gr.Dropdown([
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'RealESRGAN_x2plus',
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'RealESRGAN_x4plus',
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'RealESRNet_x4plus',
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'AI-Forever_x2plus',
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'AI-Forever_x4plus',
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'RealESRGAN_x4plus_anime_6B',
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'realesr-animevideov3',
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'realesr-general-x4v3'],
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type="value", value='RealESRGAN_x4plus', label='General restoration algorithm', info="version")
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enhancer = gr.Dropdown([
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'No additional face process',
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'GFPGANv1.2',
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'GFPGANv1.3',
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'GFPGANv1.4',
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'RestoreFormer'],
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type="value", value='No additional face process', label='Special face restoration algorithm',
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info="version")
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rescale = gr.Dropdown(["1", "2", "3", "4"], type="value", value="2", label="Rescaling factor")
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with gr.Accordion("Logs info", open=False):
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text_logger = gr.Textbox(label="login", lines=5, show_label=False)
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gr.Button("Save settings")
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btn_hires.click(enhance_face, inputs=[img_input, restorer, enhancer, rescale],
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outputs=[img_output, text_logger])
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with gr.Row():
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gr.HTML(footer)
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app.launch(share=False, debug=True, enable_queue=True, show_error=True)
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requirements.txt
CHANGED
@@ -1 +1 @@
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gradio
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gradio~=3.35.2
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