| 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() |
