| import gradio as gr | |
| from fastai.vision.all import * | |
| import skimage | |
| learn = load_learner('resnet.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 = "Skin Disease Classifier" | |
| description = "A prototype app for classifying common skin diseases, developed with fastai. Created as a demo for Gradio and HuggingFace Spaces." | |
| examples = ['acne.jpg'] | |
| interpretation='default' | |
| enable_queue=True | |
| 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,interpretation=interpretation,enable_queue=enable_queue).launch() |