Update app.py

app.py

@@ -1,134 +1,51 @@
 import os
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 os.system('/usr/local/bin/python -m pip install --upgrade pip')
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 os.system("pip install opencv-python")
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 os.system("pip install pillow")
 
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-os.system("pip install rembg")
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 import gradio as gr
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 import cv2
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 import numpy as np
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 from PIL import Image
 
+def remove_background(img):
+    # Load the image
+    img = cv2.imread(img)
 
-from io import BytesIO
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-import rembg
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-from rembg import remove
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-def inference(img):
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-   input_img = cv2.imread(img)
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-   output = remove(input_img[:, :, [2,1,0]])
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-   return output
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+    # Define the initial mask
+    mask = np.zeros(img.shape[:2], dtype=np.uint8)
+    bgdModel = np.zeros((1, 65), np.float64)
+    fgdModel = np.zeros((1, 65), np.float64)
 
+    # Define the rectangle for the GrabCut algorithm
+    rect = (50, 50, img.shape[1]-100, img.shape[0]-100)
 
+    # Run the GrabCut algorithm
+    cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)
 
+    # Get the final mask
+    mask2 = np.where((mask==2)|(mask==0), 0, 1).astype('uint8')
 
+    # Multiply the image with the mask to remove the background
+    img = img * mask2[:, :, np.newaxis]
 
+    return img
 
 def inference(img):
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-   input_img = cv2.imread(img)
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-   gray = cv2.cvtColor(input_img, cv2.COLOR_BGR2GRAY)
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+   output = remove_background(img)
+   gray = cv2.cvtColor(output, cv2.COLOR_BGR2GRAY)
    edges = cv2.Canny(gray, 50, 150)
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    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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-   silhouette = np.zeros_like(input_img)
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+   silhouette = np.zeros_like(output)
    cv2.drawContours(silhouette, contours, -1, (255, 255, 255), 1)
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    return silhouette
 
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-# Crear interfaz de usuario con Gradio
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 gr.Interface(
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    inference,
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    gr.inputs.Image(type="filepath", label="Input"),
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    gr.outputs.Image(type="numpy", label="Output"),
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    title="Convertir a silueta",
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    description="Ingresa una imagen para convertirla a silueta",
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    article="",
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    css="Footer {visibility: hidden}"
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 ).launch()
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