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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 funci贸n 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) | |