Added requiresments

app.py

@@ -10,20 +10,20 @@ import gradio as gr
 def is_cat(x): return x[0].isupper()
 
 # %% ..\lesson2-app.ipynb 4
-#learn = load_learner('model.pkl')
-import pathlib
-posix_backup = pathlib.PosixPath
-try:
-    pathlib.PosixPath = pathlib.WindowsPath
-    learn = load_learner('model.pkl')
-finally:
-    pathlib.PosixPath = posix_backup
+learn = load_learner('model.pkl')
+# import pathlib
+# posix_backup = pathlib.PosixPath
+# try:
+#     pathlib.PosixPath = pathlib.WindowsPath
+#     learn = load_learner('model.pkl')
+# finally:
+#     pathlib.PosixPath = posix_backup
 
-# %% ..\lesson2-app.ipynb 6
-categories = ('Dog','Cat')
-def classify_image(img):
-    pred, idx, probs = learn.predict(img)
-    return dict(zip(categories, map(float,probs)))
+# # %% ..\lesson2-app.ipynb 6
+# categories = ('Dog','Cat')
+# def classify_image(img):
+#     pred, idx, probs = learn.predict(img)
+#     return dict(zip(categories, map(float,probs)))
 
 # %% ..\lesson2-app.ipynb 8
 image = gr.inputs.Image(shape=(192,192))

requirements.txt

@@ -0,0 +1 @@
+fastai