x

app.py

@@ -7,7 +7,7 @@ learn = load_learner('watersports.pkl')
 categories = learn.dls.vocab
 
 def classify_image(img):
-    logging.warning('Watch out!')  # will print a message to the console
+    logging.warning('Watch out!!!')  # will print a message to the console
     print('Classifying: ', img)
     pred,idx,probs = learn.predict(img)
     return( dict(zip(categories, map(float,probs))))
@@ -19,10 +19,6 @@ You need to **\<Clear\>** before dragging next image.  Other images can be dragg
     "examples": [f'{EXAMPLES_PATH}/{f.name}' for f in EXAMPLES_PATH.iterdir()],
     "examples_per_page": "100"
 }                   
-                      
-title = "Which Watersport? Compare your guess to the machine inferencing.y"
-description = "Click an image and click submit. Drag an image into the classifier.  Take a close look and guess it yourself, before hitting **\<Submit\>**. \n \
-You need to **\<Clear\>** before dragging next image.  Other images can be dragged directly from google search."
 
 iface = gr.Interface(fn=classify_image, 
             inputs=gr.inputs.Image(shape=(192,192)),