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from huggingface_hub import from_pretrained_fastai
import gradio as gr
from fastai.vision.all import *
repo_id = "Hitomiblood/CnnLearner_resnet34_chestXrayGPU"
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.
lista = [
'NORMAL2-IM-0338-0001.jpeg',
'NORMAL2-IM-0370-0001.jpeg',
'NORMAL2-IM-0374-0001.jpeg',
'person18_virus_49.jpeg',
'person29_virus_64.jpeg',
'person127_bacteria_602.jpeg',
'person128_bacteria_605.jpeg',
]
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Label(num_top_classes=2),examples=lista).launch(share=False)
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