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from huggingface_hub import from_pretrained_fastai
import gradio as gr
from fastai.vision.all import *
# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
# repo_id = "islasher/intel-image-classification"
repo_id = "islasher/modelResnet34_blindness_LEARNER"
learner = from_pretrained_fastai(repo_id)
labels = learner.dls.vocab
# Definimos una función que se encarga de llevar a cabo las predicciones
def predict(img):
#img = PILImage.create(img)
pred,pred_idx,probs = learner.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
# Creamos la interfaz y la lanzamos.
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Label(num_top_classes=3),examples=['00cb6555d108.png','059bc89df7f4.png']).launch(share=False)
# gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Label(num_top_classes=3),examples=['10502.jpg','10402.jpg']).launch(share=False) |