Create app.py

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from face_recognition_system import FaceRecognitionSystem
+import os
+import tempfile
+
+# Initialize the face recognition system
+face_system = FaceRecognitionSystem()
+
+def process_image(image, confidence_threshold=0.5, similarity_threshold=2.0):
+    """Process a single image and return the annotated result"""
+    # Convert from RGB (Gradio) to BGR (OpenCV)
+    image_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    
+    # Update thresholds
+    face_system.confidence_threshold = confidence_threshold
+    face_system.similarity_threshold = similarity_threshold
+    
+    # Process the frame
+    processed_frame = face_system.process_frame(image_bgr)
+    
+    # Convert back to RGB for display
+    return cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB)
+
+def add_face(image, name):
+    """Add a new face to the database"""
+    if not name.strip():
+        return "Error: Please enter a name"
+    
+    # Convert from RGB (Gradio) to BGR (OpenCV)
+    image_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    
+    if face_system.add_face_to_database(name, image_bgr):
+        return f"Successfully added {name} to database"
+    return "Failed to add face to database"
+
+# Create the Gradio interface
+with gr.Blocks(title="Face Recognition System") as demo:
+    gr.Markdown("# Face Recognition System")
+    gr.Markdown("Upload an image to detect and recognize faces, or add new faces to the database.")
+    
+    with gr.Tab("Recognize Faces"):
+        with gr.Row():
+            with gr.Column():
+                input_image = gr.Image(label="Input Image", type="numpy")
+                confidence_slider = gr.Slider(
+                    minimum=0.1, 
+                    maximum=1.0, 
+                    value=0.5, 
+                    step=0.1, 
+                    label="Confidence Threshold"
+                )
+                similarity_slider = gr.Slider(
+                    minimum=0.5, 
+                    maximum=5.0, 
+                    value=2.0, 
+                    step=0.1, 
+                    label="Similarity Threshold"
+                )
+                detect_btn = gr.Button("Detect Faces")
+            
+            with gr.Column():
+                output_image = gr.Image(label="Output Image")
+    
+    with gr.Tab("Add New Face"):
+        with gr.Row():
+            with gr.Column():
+                new_face_image = gr.Image(label="Face Image", type="numpy")
+                name_input = gr.Textbox(label="Name")
+                add_btn = gr.Button("Add Face to Database")
+            
+            with gr.Column():
+                result_text = gr.Textbox(label="Result")
+    
+    # Set up event handlers
+    detect_btn.click(
+        fn=process_image,
+        inputs=[input_image, confidence_slider, similarity_slider],
+        outputs=output_image
+    )
+    
+    add_btn.click(
+        fn=add_face,
+        inputs=[new_face_image, name_input],
+        outputs=result_text
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()