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| import gradio as gr | |
| from fastai.vision.all import * | |
| import skimage | |
| import pickle | |
| learn = load_learner('snackdetector.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 = "Dutch Snack Detector" | |
| description = "Dutch Snack Detector: Detect your Dutch snack and enjoy" | |
| article = "Snacks can be found everywhere in the Netherlands as they are often sold at stands as street food and as appetisers in bars and restaurants. This classifier is tied to savoury snacks which you most often find in Dutch snackbars. It ranges from the famous frikandel till the lesser -locally- known knoeperd" | |
| examples = ['frikandel.jpg','kroket.jpg','bitterballen.jpg'] | |
| interpretation='default' | |
| enable_queue=True | |
| gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(224, 224)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,theme='seafoam',examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch() |