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Running
| import gradio as gr | |
| from fastai.vision.all import * | |
| learn = load_learner("export.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))} | |
| title = "Bird or Not Classifier" | |
| description = "A bird or not classifier trained with downloaded data from internet. Created as a demo for Gradio and HuggingFace Spaces." | |
| examples = ["bird2.jpg", "forest.jpg", "teddy.jpg"] | |
| interpretation = "default" | |
| enable_queue = True | |
| gr.Interface( | |
| fn=predict, | |
| inputs=gr.inputs.Image(shape=(512, 512)), | |
| outputs=gr.outputs.Label(num_top_classes=2), | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| interpretation=interpretation, | |
| enable_queue=enable_queue, | |
| ).launch() | |