Add application file

app.py

@@ -0,0 +1,44 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../fastai_lesson_2_bearsInference_colab.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'image', 'label', 'examples', 'intf', 'classify_image']
+
+# %% ../fastai_lesson_2_bearsInference_colab.ipynb 1
+#Imports
+
+import numpy as np # linear algebra
+import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
+
+#hide
+[ -e /content ] 
+pip install -Uqq fastbook
+
+import fastbook
+fastbook.setup_book()
+
+#hide
+from fastbook import *
+from fastai.vision.widgets import *
+
+#pip install fastai
+
+# %% ../fastai_lesson_2_bearsInference_colab.ipynb 3
+from fastai.vision.all import *
+import gradio as gr
+
+# %% ../fastai_lesson_2_bearsInference_colab.ipynb 12
+learn = load_learner('/bearClassifier.pkl')
+
+# %% ../fastai_lesson_2_bearsInference_colab.ipynb 15
+def classify_image(img):
+  pred,idx,probs = learn.predict(img)
+  return dict(zip(categories, map(float,probs)))
+
+# %% ../fastai_lesson_2_bearsInference_colab.ipynb 18
+#create gradio interface
+image = gr.inputs.Image(shape=(128,128))
+label = gr.outputs.Label()
+examples = ['grizzlyBearA.jpg', 'blackBearA.jpg', 'teddyBearA.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples )
+intf.launch(inline=False)

bearClassifier.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1be36bf5fd08a4ed7e9d5d3fcddb0093865015c2e11fdd67df91d8f708dd2c08
+size 46981023