| from fastai.vision.all import * |
| import gradio as gr |
| def is_cat(x): return x[0].isupper() |
|
|
|
|
| learn = load_learner('model.pkl') |
|
|
| categories = ('Dog', 'Cat') |
| def predict(img): |
| img = PILImage.create(img) |
| pred,pred_idx,probs = learn.predict(img) |
| return {categories[i]: float(probs[i]) for i in range(len(categories))} |
|
|
| title = "Dog Cat Classifier" |
| description = "A pet classifier trained a Pets dataset. Created as a demo using Gradio and HuggingFace Spaces." |
|
|
| article="<p style='text-align: center'><a href='https://Solab5.github.io' target='_blank'>Morris Twinomugisha</a></p>" |
| examples = ['dog.jpg', 'cat.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,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch(share='') |
