| from fastai.vision.all import * |
|
|
| learn = load_learner('export2.pkl') |
|
|
| labels = learn.dls.vocab |
| def predict(img): |
| img = PILImage.create(img).resize((132, 132)) |
| pred,pred_idx,probs = learn.predict(img) |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} |
|
|
| |
| import gradio as gr |
|
|
| title = "Pet Breed Classifier" |
| description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces." |
|
|
| examples = ['cat2.jpg','dog1.jpg','cat3.jpg','gat1.jpeg'] |
|
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| |
| 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).launch() |
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