normalizing results

app.py

@@ -81,11 +81,16 @@ def preprocess(image):
     return img_array
   
 def predict_image(image):
-    pred = model.predict(preprocess(image))
+    # pred = model.predict(preprocess(image))
+    # results = {}
+    # for row in pred:
+    #     for idx, item in enumerate(row):
+    #         results[labels[idx]] = float(item)
+    predictions = model.predict(preprocess(image))
+    scores = tf.nn.softmax(predictions[0])
     results = {}
-    for row in pred:
-        for idx, item in enumerate(row):
-            results[labels[idx]] = float(item)
+    for idx, res in enumerate(scores):
+        results[labels[idx]] = float(res)
     return results
 
 # generate img input and text label output