Update app.py

app.py

@@ -9,7 +9,7 @@ from PIL import Image
 st.title("Your Emotions? Or Nah?")
 # st.title("Hot Dog? Or Not?")
 
-file_name = st.file_uploader("Upload a photo of your face.")
+file_name = st.file_uploader("Upload a photo of your face")
 # file_name = st.file_uploader("Upload a hot dog candidate image")
 
 if file_name is not None:
@@ -18,18 +18,29 @@ if file_name is not None:
 
     # capture image
     image = Image.open(file_name)
-    # to display in in column 1
+
+    # display image in left column
     col1.image(image, use_column_width=True)
 
-    # capture image data for deepface
+    # capture image data for face analysis
     image_data = np.array(image)
-    # capture predictions from deepface
-    predictions = DeepFace.analyze(image_data, actions=['emotion'])['emotion']
-    # predictions = pipeline(image)
+    # capture predictions from deepface emotion model
+    predictions = DeepFace.analyze(image_data, actions=['emotion'])
+    # ensure only the main prediction object is processed,
+    if len(predictions) > 1:
+        # when more than one face is detected by the backend,
+        faces = [(face, face['region']['w'] * face['region']['h']) for face in predictions]
+        # by using the predictions connected to the largest bounding box
+        new_predictions = sorted(faces, key=lambda x: x[1], reverse=True)[0][0]
+        emotion_dict = new_predictions['emotion']
+    else:
+        emotion_dict = predictions['emotion']
+    # capture desired prediction data
+    emotions = list(emotion_dict.keys())
+    probabilities = list(emotion_dict.values())
 
-    # to display in column 2
+    # display in the right column...
     col2.header("Emotion Probabilities")
-    # for p in predictions:
-    for emotion in predictions:
-        # col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
-        col2.subheader(f"{emotion}")
+    # ...each emotion category and its probability
+    for i in range(len(emotions)):
+        col2.subheader(f"{emotions[i]}: {probabilities[i]:.2f}%")