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Upload app.py
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app.py
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import gradio as gr
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from fastai.vision.all import *
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from huggingface_hub import from_pretrained_fastai
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repo_id = "kurianbenoy/paddy_convnext_model"
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learn = from_pretrained_fastai(repo_id)
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labels = learn.dls.vocab
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def predict(img):
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img = PILImage.create(img)
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_pred, _pred_w_idx, probs = learn.predict(img)
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# gradio doesn't support tensors, so converting to float
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labels_probs = {labels[i]: float(probs[i]) for i, _ in enumerate(labels)}
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return labels_probs
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interface_options = {
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"title": "Paddy Doctor",
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"description": "Paddy cultivation requires consistent supervision because several diseases and pests might affect the paddy crops, leading to up to 70% yield loss. This spaces is an online demo to showcase a model build for [real-world Kaggle competition](https://www.kaggle.com/competitions/paddy-disease-classification/overview).",
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"interpretation": "default",
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"layout": "horizontal",
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# Audio from validation file
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"examples": [
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"100098.jpg",
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],
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"allow_flagging": "never",
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}
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demo = gr.Interface(
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fn=predict,
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inputs=gr.inputs.Image(shape=(480, 480)),
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outputs=gr.outputs.Label(num_top_classes=3),
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**interface_options,
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)
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launch_options = {
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"enable_queue": True,
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"share": False,
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}
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demo.launch(**launch_options)
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