Update app.py

app.py

@@ -246,7 +246,7 @@ def predict(img):
 
     if len(faces) == 0:
 
-        img = img.resize(48, 48)
+        img = img.resize(12, 12)
 
         pred_emotion, pred_emotion_idx, probs_emotion = learn_emotion.predict(array(grayscale(img)))
     
@@ -255,12 +255,12 @@ def predict(img):
         emotions = {learn_emotion_labels[i]: float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
         sentiments = {learn_sentiment_labels[i]: float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
 
-        output = [img.resize((48, 48)), emotions, sentiments, None, None, None, None, None, None]
+        output = [img.resize((12, 12)), emotions, sentiments, None, None, None, None, None, None]
     
     else: # Max 3 for now
         for face in faces[:3]:
             
-            img = face.resize((48, 48))
+            img = face.resize((12, 12))
 
             pred_emotion, pred_emotion_idx, probs_emotion = learn_emotion.predict(array(grayscale(img)))
     
@@ -338,13 +338,13 @@ examples = ['happy1.jpg', 'happy2.jpg', 'angry1.png', 'angry2.jpg', 'neutral1.jp
 
 gr.Interface(fn = predict, 
              inputs = gr.Image(), 
-             outputs = [gr.Image(shape=(24, 24), label='Person 1'), 
+             outputs = [gr.Image(shape=(12, 12), label='Person 1'), 
                         gr.Label(label='Emotion - Person 1'), 
                         gr.Label(label='Sentiment - Person 1'),
-                        gr.Image(shape=(24, 24), label='Person 2'), 
+                        gr.Image(shape=(12, 12), label='Person 2'), 
                         gr.Label(label='Emotion - Person 2'), 
                         gr.Label(label='Sentiment - Person 2'),
-                        gr.Image(shape=(24, 24), label='Person 3'), 
+                        gr.Image(shape=(12, 12), label='Person 3'), 
                         gr.Label(label='Emotion - Person 3'), 
                         gr.Label(label='Sentiment - Person 3'),], #gr.Label(),
              title = title,