Upload app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import pathlib
+temp = pathlib.PosixPath
+pathlib.PosixPath = pathlib.WindowsPath
+
+examples = ["apple.jpg", "avocado.jpg", 
+        "mixed_fruit.jpg", 
+        "nectarine.jpg", "passion_fruit.jpg", 
+        "peach.jpg"]
+title = "A fruit classification app"
+description = "A fruit classficiation app using fastai and a pretrained-Resnet50 model."
+
+learn = load_learner("model.pkl")
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+gr_interface = gr.Interface(fn=predict, 
+                    inputs = gr.inputs.Image(shape = (512, 512)), 
+                    outputs = gr.outputs.Label(num_top_classes = 3),
+                    title = title,description=description,
+                    examples = examples
+                    )
+    
+gr_interface.launch(share=True)