| import gradio as gr |
| from fastai.vision.all import * |
|
|
|
|
| learn = load_learner('model (1).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 = "Winx Club" |
| description = "Classifier for Winx Club fairies." |
| examples = ['bloom.jpg', 'stella.jpg', 'layla2.png', 'musa.jpg', 'tecna.jpg', 'flora2.png'] |
| interpretation='default' |
| enable_queue=True |
|
|
| gr.Interface( |
| fn=predict, |
| inputs=gr.Image(), |
| outputs=gr.Label(num_top_classes=2), |
| title=title, |
| description=description, |
| examples=examples, |
| ).launch() |
| iface.launch() |
|
|
