| from fastai.vision.all import * | |
| learn = load_learner('cig_detector_2.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))} | |
| import gradio as gr | |
| title = "Smoking Classifier" | |
| description = "A smoking, not smoking classifier, resnet14 trained with custom dataset using fastai." | |
| examples = ['smoking2.jpg', 'not_smoking.jpg'] | |
| gr.Interface(title=title, description=description, examples=examples,fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch() | |