cpu=True

app.py

@@ -6,12 +6,12 @@ import pathlib, os
 classes = ['rock', 'paper', 'scissors'] # c0, c1, c2
 
 def classify_image(img, model):
-    # if os.name == 'nt': # workaround for Windows
-    #     pathlib.PosixPath = pathlib.WindowsPath 
-    # if os.name == 'posix': # workaround for Linux
-    #         pathlib.WindowsPath = pathlib.PosixPath 
+    if os.name == 'nt': # workaround for Windows
+        pathlib.PosixPath = pathlib.WindowsPath 
+    if os.name == 'posix': # workaround for Linux
+            pathlib.WindowsPath = pathlib.PosixPath 
 
-    learn = load_learner(model)
+    learn = load_learner(model, cpu=True)
     pred,idx,probs = learn.predict(img)
     return dict(zip(classes, map(float, probs)))