Update app.py

app.py

@@ -36,14 +36,12 @@ with open("list.dat", 'rb') as f:
 model = load_learner("model.pkl")
 
 def predict(img):
-    logging.warning(f"{img.dtype}")
+    logging.warning(f"{type(image)}")
     try:
         logging.warning(f"Shape: {img.shape}")
     except AttributeError:
         logging.warning(f"Size: {img.size}")
     pred, idx, probs = model.predict(img)
-    logging.debug(f"{type(probs)}")
-    logging.debug(f"{type(probs[0])}")
     dict1 = dict(zip(categories, map(float, probs.numpy())))
     dict1 = dict(sorted(dict1.items(), key=lambda item : item[1]))
     output = {key:dict1[key] for key in list(dict1.keys())[-3:]}