fast.ai 2.7.11 update

app.py

@@ -3,7 +3,7 @@
 
 
 
-__all__ = ['install', 'learn', 'categories', 'classify_image', 'image', 'label', 'examples', 'intf', 'classify_image_url', 'intf_text_url']
+__all__ = ['install', 'learn', 'categories', 'classify_image', 'classify_image_url', 'image', 'label', 'examples', 'intf', 'intf_text_url']
 
 
 
@@ -51,8 +51,26 @@ categories = ('amateur', 'stock')
 #add probs to UI somewhere
 
 def classify_image(img):
-    pred,idx,probs = learn.predict(img)
+    tens = tensor(img) #fix apparently needed after fastai 2.7.11 released
+    pred,idx,probs = learn.predict(tens)
     return dict(zip(categories, map(float,probs)))
+
+from fastdownload import download_url
+import os
+
+def classify_image_url(url_text):
+    try:
+        dest = 'temp.jpg'
+        download_url(url_text, dest, show_progress=False)
+        im = Image.open(dest)
+        img = im.to_thumb(256,256)
+        #resize_images(dest, max_size=400, dest=dest)
+        os.remove(dest)
+        return classify_image(img)
+    except:
+        # in case there is any error, invalid URL or invalid image, etc., not sure how Gradio will handle a runtime exception so catching it to be safe
+        return { categories[0]: 0.0, categories[1]: 0.0 }
+
     
     
 image     = gr.inputs.Image(shape=(192, 192))
@@ -74,25 +92,6 @@ intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=exa
 # intf.launch(inline=False)
 
 
-
-from fastdownload import download_url
-from fastai.vision.all import *
-import os
-
-
-def classify_image_url(url_text):
-    try:
-        dest = 'temp.jpg'
-        download_url(url_text, dest, show_progress=False)
-        im = Image.open(dest)
-        img = im.to_thumb(256,256)
-        #resize_images(dest, max_size=400, dest=dest)
-        os.remove(dest)
-        return classify_image(img)
-    except:
-        # in case there is any error, invalid URL or invalid image, etc., not sure how Gradio will handle a runtime exception so catching it to be safe
-        return { categories[0]: 0.0, categories[1]: 0.0 }
-
 intf_text_url = gr.Interface(fn=classify_image_url, inputs="text", outputs=gr.outputs.Label())#, examples=example_urls)
 # intf_text_url.launch(inline=False)