done

app.py

@@ -1,7 +1,22 @@
 import gradio as gr
+from fastai.vision.all import *
 
-def greet(name):
-    return "Hello " + name + "!!"
+def classify_img(img):
+    pred , idx , probs = learn.predict(img)
+    return dict(zip(categories , map(float , probs)))
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+learn = load_learner('bearsfastai/bears_model.pkl')
+
+categories = ( 'black bear','grizzly bear'  , 'teady bear')
+
+
+image = gr.inputs.Image(shape=(194,194))
+label = gr.outputs.Label()
+examples = [
+    'train_data2/teady bear/f8d8000c-1eae-43dc-a06b-58e9e242effd.jpg' , 
+    'train_data2/grizzly bear/1d5e3d53-a4a9-4f19-b1cb-1bed0f95ed66.jpg',
+    'train_data2/black bear/6ea1843c-f6d4-497d-a861-d66ae6b36290.jpg'
+]
+
+intf = gr.Interface(fn = classify_img , inputs = image , outputs = label , examples = examples)
+intf.launch(share = True)

bears_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb1d64e0a426824a80a2e2f59d06d0ae7f5e7e5d5f10651046218d583536aaef
+size 46968801