Updated predict function.

app.py

@@ -51,7 +51,6 @@ food_info = {
 }
 
 def predict(my_image):
-
     image = Image.fromarray(my_image.astype('uint8'))
 
     pipe = pipeline("image-classification", 
@@ -60,33 +59,14 @@ def predict(my_image):
     
     pred = pipe(image)
     
-    plt.imshow(image)
-    plt.title(pred[0]['label'].replace('_', ' ').title())
-    plt.axis(False)
-    plt.show()
-
-    print(f"Predicted the above image as a {pred[0]['label'].replace('_', ' ').title()} with {pred[0]['score']*100:.2f}% confidence")
-    
-    run = True
-    while run:
-
-        inp = input('Is the prediction correct?')
-        if inp.lower() == 'yes':
-            print(f"""
-{food_info[pred[0]['label'].replace('_', ' ').title()]['Description']}
-
-Info: {food_info[pred[0]['label'].replace('_', ' ').title()]['Calories and Health Info']}""")
-            run = False
-        elif inp.lower() == 'no':
-            print(f"""
-The image could be a {pred[1]['label'].replace('_', ' ').title()}, with a {pred[1]['score']*100:.2f}% confidence,
-The image could be a {pred[2]['label'].replace('_', ' ').title()}, with a {pred[2]['score']*100:.2f}% confidence,
-The image could be a {pred[3]['label'].replace('_', ' ').title()}, with a {pred[3]['score']*100:.2f}% confidence,
-Or the image could be a {pred[4]['label'].replace('_', ' ').title()}, with a {pred[4]['score']*100:.2f}% confidence,
-                   """)
-            run = False
-        else:
-            print('Please respond as yes or no')
+    res = {}
+    for i in pred:
+        res[i['label'].replace('_', ' ').title()] = round(i['score'])
+    return res, food_info[pred[0]['label'].replace('_', ' ').title()]['Description'],food_info[pred[0]['label'].replace('_', ' ').title()]['Calories and Health Info']
 
-iface = gr.Interface(fn=predict, inputs="image", outputs="image")
+iface = gr.Interface(fn=predict,
+                    inputs='image',
+                    outputs=[gr.Label(num_top_classes=5, label="Predictions"), 
+                             gr.Text(label='Description'),
+                             gr.Text(label='Calories and Health Info')])
 iface.launch()