Update app.py

app.py

@@ -7,24 +7,37 @@ from PIL import Image
 
 # Mediapipe face detection setup
 mp_face_detection = mp.solutions.face_detection
+mp_face_mesh = mp.solutions.face_mesh
 mp_drawing = mp.solutions.drawing_utils
+mp_drawing_styles = mp.solutions.drawing_styles
 
-def capture_and_analyze(image):
+def analyze_face_features(image):
     # Convert to BGR for OpenCV compatibility
     image_np = np.array(image)
     image_np = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
 
-    # Run face detection
-    with mp_face_detection.FaceDetection(model_selection=1, min_detection_confidence=0.5) as face_detection:
-        results = face_detection.process(cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB))
-
-        if results.detections:
-            for detection in results.detections:
-                mp_drawing.draw_detection(image_np, detection)
+    # Face Mesh Detection
+    with mp_face_mesh.FaceMesh(static_image_mode=True, max_num_faces=1, refine_landmarks=True, min_detection_confidence=0.5) as face_mesh:
+        results = face_mesh.process(cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB))
+
+        if results.multi_face_landmarks:
+            for face_landmarks in results.multi_face_landmarks:
+                mp_drawing.draw_landmarks(
+                    image=image_np,
+                    landmark_list=face_landmarks,
+                    connections=mp_face_mesh.FACEMESH_TESSELATION,
+                    landmark_drawing_spec=None,
+                    connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_tesselation_style())
+                mp_drawing.draw_landmarks(
+                    image=image_np,
+                    landmark_list=face_landmarks,
+                    connections=mp_face_mesh.FACEMESH_CONTOURS,
+                    landmark_drawing_spec=None,
+                    connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_contours_style())
         else:
-            print("No face detected")
+            print("No facial landmarks detected")
 
-    # Save image temporarily
+    # Save processed image temporarily
     temp_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
     cv2.imwrite(temp_file.name, image_np)
 
@@ -32,9 +45,9 @@ def capture_and_analyze(image):
 
 # Gradio Interface
 iface = gr.Interface(
-    fn=capture_and_analyze,
+    fn=analyze_face_features,
     inputs=gr.Image(label="Upload or Capture a Face Image"),
-    outputs=gr.Image(label="Processed Image with Face Detection")
+    outputs=gr.Image(label="Face Mesh + Features")
 )
 
 iface.launch()