import gradio as gr from fastai.vision.all import * import skimage learn = load_learner('felinos.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))} # cambiar título title = "Clasificador de imágenes" # cambiar descripción description = "Un clasificador de imágenes entrenado sobre resnet18." interpretation='default' enable_queue=True gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=2),title=title,description=description,interpretation=interpretation).launch()