| import gradio as gr |
| from fastai.vision.all import * |
| import skimage |
|
|
| learn = load_learner('export.pkl') |
|
|
| labels = learn.dls.vocab |
| def predict(img): |
| img = PILImage.create(img) |
| pred,pred_idx,probs = learn.predict(img) |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} |
|
|
| title = "Clasificación de imágenes" |
| description = "Demo para el clasificador construido en la práctica 1." |
| article="<p style='text-align: center'><a href='https://ap2122.github.io/aprendizajeprofundo2122/practica/2022/01/10/practica1-clasificacion-imagenes.html' target='_blank'>Blog post</a></p>" |
| examples = ['building.jpg','sea.jpg','forest.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=False) |
|
|
