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Update app.py
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app.py
CHANGED
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import gradio as gr
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import os
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import cv2
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import numpy as np
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def inference(file, mask, model, alpha_influence, segmentation_strength):
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im = cv2.imread(file, cv2.IMREAD_COLOR)
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input_path = 'input.png'
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output_path = 'output.png'
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mask_path = 'mask.png'
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with open(input_path, 'rb') as i:
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with open(output_path, 'wb') as o:
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)
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o.write(output)
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m.write(output)
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title = "RemBG"
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description = "Gradio demo for RemBG. To use it, simply upload your image and adjust the alpha influence and segmentation strength."
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article = "<p style='text-align: center;'><a href='https://github.com/danielgatis/rembg' target='_blank'>Github Repo</a></p>"
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output_image = cv2.imread(output_image_path)
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return output_image
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def show_processed_mask(mask_image_path):
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mask_image = cv2.imread(mask_image_path)
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return mask_image
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iface = gr.Interface(
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inference,
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[
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gr.inputs.Image(type="filepath", label="Input"),
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gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Alpha Influence"),
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gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Segmentation Strength"),
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],
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gr.outputs.Image(type="plot", label="Processed Image"),
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gr.outputs.Image(type="plot", label="Processed Mask"),
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],
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title=title,
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description=description,
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article=article,
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examples=[["lion.png", "Default", "u2net", 0.5, 0.5], ["girl.jpg", "Default", "u2net", 0.5, 0.5], ["anime-girl.jpg", "Default", "isnet-anime", 0.5, 0.5]],
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enable_queue=True
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)
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iface.launch()
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import gradio as gr
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import os
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import cv2
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def inference(file, mask, model, alpha_influence, segmentation_strength):
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im = cv2.imread(file, cv2.IMREAD_COLOR)
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input_path = 'input.png'
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output_path = 'output.png'
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with open(input_path, 'rb') as i:
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with open(output_path, 'wb') as o:
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input = i.read()
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output = remove(
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input,
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session=new_session(model),
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only_mask=(True if mask == "Mask only" else False),
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alpha=alpha_influence, # Control de influencia del canal alfa
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bg_color=(0, 0, 0, segmentation_strength) # Control de fuerza de segmentación
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)
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o.write(output)
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return os.path.join("output.png")
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title = "RemBG"
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description = "Gradio demo for RemBG. To use it, simply upload your image and adjust the alpha influence and segmentation strength."
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article = "<p style='text-align: center;'><a href='https://github.com/danielgatis/rembg' target='_blank'>Github Repo</a></p>"
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gr.Interface(
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inference,
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[
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gr.inputs.Image(type="filepath", label="Input"),
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gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Alpha Influence"),
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gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Segmentation Strength"),
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],
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gr.outputs.Image(type="filepath", label="Output"),
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title=title,
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description=description,
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article=article,
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examples=[["lion.png", "Default", "u2net", 0.5, 0.5], ["girl.jpg", "Default", "u2net", 0.5, 0.5], ["anime-girl.jpg", "Default", "isnet-anime", 0.5, 0.5]],
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enable_queue=True
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).launch()
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