Implement image classification feature using FastAI in Gradio app

app.py

@@ -1,9 +1,18 @@
 import gradio as gr
+from fastai.vision.all import load_learner, get_image_files
 
+learn = load_learner('resnet18_bearclassifier.pkl')
 
-def greet(name):
-    return "Hello " + name + "!!"
+# gradio UI
 
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def classify_image(img):
+    categories = ['brown', 'polar']
+    _, _, probability = learn.predict(img)
+    return dict(zip(categories, map(float, probability)))
+
+
+app = gr.Interface(fn=classify_image, inputs='image',
+                   outputs='label', examples=list(get_image_files('valid')))
+app.launch()
+classify_image('images.jpg')

resnet18_bearclassifier.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:00bce8ac5b8c770c019669f9a92fea24b99c1742d0b8d3eeae852d898040cc01
+size 46965914