app and model

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+def is_cat(x): return x[0].isupper()
+
+learn = load_learner('export.pkl')
+
+categories = ('apple','banana','beetroot','bell pepper','cabbage','capsicum','carrot','cauliflower','chili pepper','corn','cucumber','eggplant','garlic','ginger','grapes','jalepeno','kiwi','lemon','lettuce','mango','onion','orange','paprika','pear','peas','pineapple','pomegranate','potato','raddish','soy beans','spinach','sweetcorn','sweetpotato','tomato','turnip','watermelon')
+
+def classify_images(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+image = gr.Image(type="pil")
+label = gr.Label()
+
+intf = gr.Interface(fn=classify_images, inputs=image, outputs=label)
+intf.launch(inline=False)

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:79b5e58a7b90b10b68b7215e2b499f469210cab3dec8d8620c864964df4df86d
+size 47092164

requirements.txt

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+fastai
+scikit-image