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import gradio as gr |
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from fastai.vision.all import * |
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import skimage |
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learn = load_learner('export.pkl') |
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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_idx,probs = learn.predict(img) |
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return {labels[i]: float(probs[i]) for i in range(len(labels))} |
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title = "Pengenalan Ras Hewan Peliharaan Kucing dan Anjing" |
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description = "Selamat Datang di Aplikasi Pengklasifikasi ras Hewan Peliharaan yang di training pada kumpulan data Oxford Pets dengan Fastai :D" |
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article="<p style='text-align: center'><a href='https://wahyupebrianto.github.io/' target='_blank'>Blog post</a></p>" |
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examples = ['cat.jpg'] |
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image = gr.Image(type="pil") |
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label = gr.Label(num_top_classes=3) |
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gr.Interface(fn=predict,inputs=image, |
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outputs=label,title=title, |
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description=description,article=article,examples=examples).launch() |
