Update app.py

app.py

@@ -1,43 +1,134 @@
 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
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 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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 def inference(img):
-    img = Image.open(img)
-    img = np.array(img)
-    input_img = cv2.imread(img)
-    output = remove(input_img[:, :, [2,1,0]])
-    gray = cv2.cvtColor(output, cv2.COLOR_BGR2GRAY)
-    edges = cv2.Canny(gray, 50, 150)
-    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    silhouette = np.zeros_like(output)
-    cv2.drawContours(silhouette, contours, -1, (255, 255, 255), 1)
-    return silhouette
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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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+   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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+   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(
-    inference, 
-    gr.inputs.Image(type="filepath", label="Input"), 
-    gr.outputs.Image(type="numpy", label="Output"),
-    title="Convertir a silueta",
-    description="Ingresa una imagen para convertirla a silueta",
-    article="",
-    css="Footer {visibility: hidden}"
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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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