GFPGAN Xintao
Browse files
app.py
CHANGED
@@ -5,7 +5,7 @@ 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("
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clientSuperface = Client("leonelhs/superface")
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clientZeroScratches = Client("leonelhs/ZeroScratches")
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clientDeoldify = Client("leonelhs/deoldify")
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@@ -23,8 +23,8 @@ def download(file):
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return list(Path(file).iterdir())
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def gfpgan_face(image):
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return clientGFPGAN.predict(image,
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def enhance_face(image, upsampler, face_enhancer, scale):
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@@ -45,7 +45,7 @@ def enhance_light(image):
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def zero_background(image, new_bgr=None):
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# return clientZeroBackground.predict(image, new_bgr, api_name="/predict")[0]
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# Fixme: cant find predict
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return clientZeroBackground.predict(image, new_bgr, fn_index=0)[1]
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@@ -81,7 +81,7 @@ with gr.Blocks(title="Face Shine") as app:
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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
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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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@@ -106,6 +106,13 @@ with gr.Blocks(title="Face Shine") as app:
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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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@@ -115,22 +122,15 @@ with gr.Blocks(title="Face Shine") as app:
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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',
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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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btn_eraser.click(zero_scratches, inputs=[img_input], outputs=[img_output])
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btn_color.click(colorize_photo, inputs=[img_input], outputs=[img_output])
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btn_light.click(enhance_light, inputs=[img_input], outputs=[img_output])
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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("Xintao/GFPGAN")
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clientSuperface = Client("leonelhs/superface")
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clientZeroScratches = Client("leonelhs/ZeroScratches")
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clientDeoldify = Client("leonelhs/deoldify")
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return list(Path(file).iterdir())
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def gfpgan_face(image, version, scale):
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return clientGFPGAN.predict(image, version, scale, fn_index=0)[0]
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def enhance_face(image, upsampler, face_enhancer, scale):
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def zero_background(image, new_bgr=None):
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# return clientZeroBackground.predict(image, new_bgr, api_name="/predict")[0]
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# Fixme: cant find predict function by name
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return clientZeroBackground.predict(image, new_bgr, fn_index=0)[1]
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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 faces")
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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.TabItem("Settings", id=2):
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with gr.Accordion("Image restoration settings", open=False):
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enhancer = gr.Dropdown([
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'v1.2',
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'v1.3',
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'v1.4',
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'RestoreFormer'],
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type="value", value='RestoreFormer', label='GFPGAN face restoration algorithm',
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info="version")
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restorer = gr.Dropdown([
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'RealESRGAN_x2plus',
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'RealESRGAN_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',
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label='Real-ESRGAN image restoration algorithm', info="version", visible=False)
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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], outputs=[img_output, text_logger])
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btn_hires.click(gfpgan_face, inputs=[img_input, enhancer, rescale], outputs=[img_output])
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btn_eraser.click(zero_scratches, inputs=[img_input], outputs=[img_output])
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btn_color.click(colorize_photo, inputs=[img_input], outputs=[img_output])
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btn_light.click(enhance_light, inputs=[img_input], outputs=[img_output])
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