| __all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] |
|
|
| from fastai.vision.all import * |
| import gradio as gr |
|
|
| learn = load_learner('mountain.pkl') |
|
|
| categories = ('bird', 'lizard', 'pine', 'squirrel', 'wildflower') |
| def classify_image(img): |
| pred, idx, probs = learn.predict(img) |
| return dict(zip(categories, map(float, probs))) |
|
|
| image=gr.Image(height = 192, width = 192) |
| label = gr.Label() |
| examples = ['01f2342f-ab5d-4b2b-bc12-2ca4b29a3da1.jpg','0d49e603-c5a4-42de-919e-a7860041f2e3.jpg', |
| '01e0f45d-00b7-4017-b6c8-7b639e519af2.jpg','033e0f96-8f50-4347-b950-c46c3d5e1ace.jpg', |
| '04707503-3266-4048-8084-c141a56c458d.jpg'] |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) |
| intf.launch(inline=False) |
