| # %% | |
| #/default_exp app | |
| # %% | |
| #/export | |
| from turtle import title | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| title = "Image Classifier" | |
| description = "An image classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces" | |
| def is_cat(x): return x[0].isupper() | |
| # %% | |
| #/export | |
| learn = load_learner('model.pkl') | |
| # %% | |
| #/export | |
| categories = ('Dog','Cat') | |
| def classify_image(img): | |
| pred,idx,probs = learn.predict(img) | |
| return dict(zip(categories,map(float,probs))) | |
| # %% | |
| classify_image('dog.jpeg') | |
| # %% | |
| #/export | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label() | |
| examples = ['dog.jpeg','cat.jpeg', 'dunno.jpeg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label,examples=examples) | |
| intf.launch(inline=False) | |