Wire up the app with the actual face detection model

app.py

@@ -13,7 +13,16 @@ mp_drawing = mp.solutions.drawing_utils
 demo = gr.Blocks()
 
 def detect_faces(image, model_selection, min_detection_confidence):
-  return {}, image
+  with mp_face_detection.FaceDetection(model_selection=model_selection, min_detection_confidence=min_detection_confidence) as face_detection:
+    results = face_detection.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+    if not results.detections:
+      logger.info('No faces detected')
+      return image, 0
+    logger.info(f"{len(results.detections)} faces detected")
+    annotated_image = image.copy()
+    for detection in results.detections:
+      mp_drawing.draw_detection(annotated_image, detection)
+    return annotated_image, len(results.detections)
 
 with demo:
   gr.Markdown(
@@ -24,7 +33,6 @@ with demo:
 
   with gr.Row():
     with gr.Column():
-      
       gr.Markdown("## Step 1: Configure the model")
       with gr.Group():
         model_selection = gr.Radio(label="Model selection", value=0, choices=[0, 1])
@@ -35,23 +43,18 @@ with demo:
         gr.Textbox(show_label=False, value="Minimum confidence value ([0.0, 1.0]) from the face detection model for the detection to be considered successful.")
 
       gr.Markdown("## Step 2: Select an image")
-      with gr.Tabs():
-        with gr.TabItem(label="Upload an image"):
-          upload_image = gr.Image(label="Input image")
-          gr.Examples(examples=[["examples/01.jpg"]], inputs=[upload_image])
-          upload_image_btn = gr.Button(value="Detect faces")
-        with gr.TabItem(label="Take a photo"):
-          webcam_image = gr.Image(label="Input image", source="webcam")
-          webcam_image_btn = gr.Button(value="Detect faces")
+      upload_image = gr.Image(label="Input image", type="numpy")
+      gr.Examples(examples=[["examples/01.jpg", 1], ["examples/02.jpg", 1], ["examples/03.jpg", 0]], inputs=[upload_image, model_selection])
+      upload_image_btn = gr.Button(value="Detect faces")
 
     with gr.Column():
       gr.Markdown("## Step 3: View the results")
       with gr.Group():
-        raw_results = gr.JSON(label="Raw results")
+        num_faces_detected = gr.Number(label="Number of faces detected", value=0)
         output_image = gr.Image(label="Output image")
 
-    model_config_inputs = [model_selection, min_detection_confidence]
-    outputs = [raw_results, output_image]
-    upload_image_btn.click(fn=detect_faces, inputs=[upload_image, *model_config_inputs], outputs=outputs)
+  model_config_inputs = [model_selection, min_detection_confidence]
+  outputs = [output_image, num_faces_detected]
+  upload_image_btn.click(fn=detect_faces, inputs=[upload_image, *model_config_inputs], outputs=outputs)
 
 demo.launch()