Create app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+import face_recognition
+
+def face_match(file1, file2, threshold):
+    try:
+        # Load the images
+        image1 = face_recognition.load_image_file(file1)
+        image2 = face_recognition.load_image_file(file2)
+
+        # Encode the faces
+        encodings1 = face_recognition.face_encodings(image1)
+        encodings2 = face_recognition.face_encodings(image2)
+
+        if len(encodings1) == 0 and len(encodings2) == 0:
+            return {"error": "No faces detected in both images."}
+        elif len(encodings1) == 0:
+            return {"error": "No face detected in the first image."}
+        elif len(encodings2) == 0:
+            return {"error": "No face detected in the second image."}
+
+        # Use the first face encoding from each image
+        face_encoding1 = encodings1[0]
+        face_encoding2 = encodings2[0]
+
+        # Calculate the distance
+        distance = face_recognition.face_distance([face_encoding1], face_encoding2)[0]
+
+        # Determine match status
+        match_status = "match" if distance <= threshold else "no_match"
+
+        return {
+            "status": match_status,
+            "distance": round(distance, 4),
+            "threshold": threshold
+        }
+
+    except Exception as e:
+        print(e)
+        return {"error": f"Unexpected error: {str(e)}"}
+
+iface = gr.Interface(
+    fn=face_match,
+    inputs=[
+        gr.Image(type="filepath", label="Image 1"),
+        gr.Image(type="filepath", label="Image 2"),
+        gr.Number(value=0.6, label="Threshold")
+    ],
+    outputs="json",
+    title="Face Match App",
+    description="Upload two images and set a threshold to check if the faces match."
+)
+
+iface.launch(server_name="0.0.0.0")