add demo file

gradio/demo.py

@@ -0,0 +1,31 @@
+import mediapipe as mp
+import gradio as gr
+mp_face_mesh = mp.solutions.face_mesh
+
+# Prepare DrawingSpec for drawing the face landmarks later.
+mp_drawing = mp.solutions.drawing_utils 
+drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
+
+# Run MediaPipe Face Mesh.
+
+def inference(image):
+    with mp_face_mesh.FaceMesh(
+        static_image_mode=True,
+        max_num_faces=2,
+        min_detection_confidence=0.5) as face_mesh:
+        # Convert the BGR image to RGB and process it with MediaPipe Face Mesh.
+        results = face_mesh.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+
+        # Draw face landmarks of each face.
+        print(f'Face landmarks of {name}:')
+        if not results.multi_face_landmarks:
+        continue
+        annotated_image = image.copy()
+        for face_landmarks in results.multi_face_landmarks:
+        mp_drawing.draw_landmarks(
+            image=annotated_image,
+            landmark_list=face_landmarks,
+            connections=mp_face_mesh.FACE_CONNECTIONS,
+            landmark_drawing_spec=drawing_spec,
+            connection_drawing_spec=drawing_spec)
+        return annotated_image