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app.py

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+import gradio as gr
+from huggingface_hub import from_pretrained_fastai
+
+examples = ["image_1.png", "image_2.png"]
+repo_id = "hugginglearners/grapevine_leaves_classification"
+
+learner = from_pretrained_fastai(repo_id)
+
+def inference(image):
+    label_predict,_,probs = learner.predict(img)
+    return f"This grapevine leave is {label_predict} with {100*probs[torch.argmax(probs)].item():.2f}% probability"
+
+gr.Interface(
+    fn=inference,
+    title="Grapevine leave image classification",
+    description = "Predict which type of grapevine leave belong to Ak, Ala_Idris, Buzgulu, Dimnit, Nazli",
+    inputs="image",
+    examples=examples,
+    outputs=gr.Textbox(label='Prediction'),
+    cache_examples=False,
+    article = "Author: <a href=\"https://huggingface.co/vumichien\">Vu Minh Chien</a>",
+).launch(debug=True, enable_queue=True)