| #| export | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_cat(x): return x[0].isupper() | |
| #| export | |
| learn = load_learner('model.pkl') | |
| #| export | |
| categories = ('Dog', 'Cat') | |
| def classify_images(img): | |
| #'Is it a car?', 'Is it a car? but as zero or one', 'probabillity of [dog, cat]' | |
| pred, idx, probs = learn.predict(img) | |
| #return dictionary | |
| #zip together the categories and the | |
| #turn probs to float | |
| return dict(zip(categories, map(float, probs))) | |
| examples = ['dog.jpg', 'cat.jpg', 'catdog.jpg', 'he-s-a-catdog-or-dogcat.jpeg'] | |
| intf = gr.Interface( | |
| fn=classify_images, | |
| inputs=gr.Image(type="pil", image_mode="RGB", height=192, width=192), | |
| outputs=gr.Label(), | |
| examples=examples | |
| ) | |
| intf.launch() | |