Create app.py

app.py

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+import cv2
+import numpy as np
+import gradio as gr
+from PIL import Image
+
+def detect_shapes(image):
+    """
+    Detect shapes in an image and return the annotated result
+    """
+    # Convert PIL Image to OpenCV format
+    img = np.array(image)
+    img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+    
+    # Create a copy for drawing contours
+    img_contour = img.copy()
+    
+    # Convert to grayscale
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    
+    # Apply Gaussian blur
+    blur = cv2.GaussianBlur(gray, (5, 5), 1)
+    
+    # Edge detection
+    edges = cv2.Canny(blur, 50, 150)
+    
+    # Find contours
+    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    
+    shapes_detected = []
+    
+    # Process each contour
+    for cnt in contours:
+        area = cv2.contourArea(cnt)
+        if area > 500:  # Filter small contours
+            # Approximate contour to polygon
+            epsilon = 0.02 * cv2.arcLength(cnt, True)
+            approx = cv2.approxPolyDP(cnt, epsilon, True)
+            
+            # Get bounding rectangle
+            x, y, w, h = cv2.boundingRect(approx)
+            
+            # Determine shape based on number of vertices
+            nb_sommets = len(approx)
+            shape = "Indéfini"
+            
+            if nb_sommets == 3:
+                shape = "Triangle"
+            elif nb_sommets == 4:
+                ratio = w / float(h)
+                shape = "Carré" if 0.95 < ratio < 1.05 else "Rectangle"
+            elif nb_sommets > 6:
+                shape = "Cercle"
+            
+            # Draw contour and label
+            cv2.drawContours(img_contour, [approx], 0, (0, 255, 0), 2)
+            cv2.putText(img_contour, shape, (x, y - 10), 
+                       cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+            
+            shapes_detected.append({
+                'shape': shape,
+                'vertices': nb_sommets,
+                'area': int(area),
+                'position': f"({x}, {y})"
+            })
+    
+    # Convert back to RGB for display
+    img_contour = cv2.cvtColor(img_contour, cv2.COLOR_BGR2RGB)
+    
+    # Create summary text
+    summary = f"Détecté {len(shapes_detected)} forme(s):\n"
+    for i, shape_info in enumerate(shapes_detected, 1):
+        summary += f"{i}. {shape_info['shape']} - {shape_info['vertices']} sommets - Aire: {shape_info['area']} pixels\n"
+    
+    return img_contour, summary
+
+# Create Gradio interface
+def create_interface():
+    with gr.Blocks(title="Détecteur de Formes Géométriques", theme=gr.themes.Soft()) as interface:
+        gr.Markdown("# 🔍 Détecteur de Formes Géométriques")
+        gr.Markdown("Téléchargez une image pour détecter et identifier les formes géométriques (triangles, carrés, rectangles, cercles)")
+        
+        with gr.Row():
+            with gr.Column():
+                input_image = gr.Image(
+                    type="pil", 
+                    label="📸 Image d'entrée",
+                    height=400
+                )
+                
+                detect_btn = gr.Button(
+                    "🔍 Détecter les formes", 
+                    variant="primary",
+                    size="lg"
+                )
+                
+                gr.Markdown("### Instructions:")
+                gr.Markdown("""
+                - Téléchargez une image contenant des formes géométriques
+                - Les formes doivent être suffisamment grandes (aire > 500 pixels)
+                - Fonctionne mieux avec des formes aux contours nets
+                - Supporte: triangles, carrés, rectangles, cercles
+                """)
+            
+            with gr.Column():
+                output_image = gr.Image(
+                    label="🎯 Formes détectées", 
+                    height=400
+                )
+                
+                output_text = gr.Textbox(
+                    label="📊 Résumé de détection",
+                    lines=8,
+                    max_lines=15
+                )
+        
+        # Examples section
+        gr.Markdown("### 📝 Exemples")
+        gr.Examples(
+            examples=[
+                # You can add example images here if you have them
+                # ["path/to/example1.jpg"],
+                # ["path/to/example2.jpg"],
+            ],
+            inputs=input_image,
+            label="Cliquez sur un exemple pour le tester"
+        )
+        
+        # Event handlers
+        detect_btn.click(
+            fn=detect_shapes,
+            inputs=input_image,
+            outputs=[output_image, output_text]
+        )
+        
+        input_image.change(
+            fn=detect_shapes,
+            inputs=input_image,
+            outputs=[output_image, output_text]
+        )
+    
+    return interface
+
+# Launch the app
+if __name__ == "__main__":
+    interface = create_interface()
+    interface.launch(
+        share=True,
+        server_name="0.0.0.0",
+        server_port=7860
+    )