| import gradio as gr | |
| from fastai.vision.all import * | |
| from fastcore import * | |
| learn = load_learner('kitten.pkl') | |
| classes = learn.dls.vocab | |
| def classify_images(img): | |
| img = PILImage.create(img) | |
| pred,idx,prob = learn.predict(img) | |
| return {classes[i]: float(prob[i]) for i in range(len(classes))} | |
| title = "Cute or Ugly Kitten Classifier" | |
| description = "Upload a kitten and it will tell you if it's ugly or cute! ~Elio." | |
| examples = [['cute kitten.jpg'], ['ugly kitten.jpg']] | |
| iface = gr.Interface(fn=classify_images, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(), title=title, description=description, examples=examples) | |
| iface.launch() | |