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Update app.py
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app.py
CHANGED
@@ -5,7 +5,7 @@ from rembg import new_session, remove
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from PIL import Image
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from io import BytesIO
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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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cv2.imwrite(os.path.join("input.png"), im)
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@@ -22,6 +22,7 @@ def inference(file, mask, model, alpha_influence, segmentation_strength):
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alpha_matting_foreground_threshold=alpha_influence, # Control de influencia del canal alfa
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alpha_matting_background_threshold=1 - alpha_influence, # Control del canal alfa para el fondo
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alpha_matting_erode_size=int(segmentation_strength * 10), # Control de fuerza de segmentación
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session=new_session(model)
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)
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@@ -30,7 +31,7 @@ def inference(file, mask, model, alpha_influence, segmentation_strength):
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return Image.open(BytesIO(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
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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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@@ -62,12 +63,14 @@ gr.Interface(
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),
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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="PIL", 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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from PIL import Image
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from io import BytesIO
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def inference(file, mask, model, alpha_influence, segmentation_strength, smoothing):
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im = cv2.imread(file, cv2.IMREAD_COLOR)
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cv2.imwrite(os.path.join("input.png"), im)
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alpha_matting_foreground_threshold=alpha_influence, # Control de influencia del canal alfa
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alpha_matting_background_threshold=1 - alpha_influence, # Control del canal alfa para el fondo
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alpha_matting_erode_size=int(segmentation_strength * 10), # Control de fuerza de segmentación
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alpha_matting_smoothing=smoothing, # Control de suavizado de bordes de la segmentación
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session=new_session(model)
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)
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return Image.open(BytesIO(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, segmentation strength, and smoothing."
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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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),
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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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gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Smoothing"),
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],
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gr.outputs.Image(type="PIL", 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, 0.5], ["girl.jpg", "Default", "u2net", 0.5, 0.5, 0.5], ["anime-girl.jpg", "Default", "isnet-anime", 0.5, 0.5, 0.5]],
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enable_queue=True
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).launch()
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+
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