maviced commited on
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c4abeec
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1 Parent(s): cf70c87

Update app.py

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  1. app.py +11 -8
app.py CHANGED
@@ -1,17 +1,20 @@
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- from fastai.vision.all import *
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  import gradio as gr
 
 
 
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- # Cargamos el learner
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- learn = load_learner('export.pkl')
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- # Definimos las etiquetas de nuestro modelo
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- labels = learn.dls.vocab
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  # Definimos una función que se encarga de llevar a cabo las predicciones
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  def predict(img):
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- img = PILImage.create(img)
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- pred,pred_idx,probs = learn.predict(img)
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  return {labels[i]: float(probs[i]) for i in range(len(labels))}
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  # Creamos la interfaz y la lanzamos.
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- gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Label(num_top_classes=4),examples=['10000.jpg','10007.jpg']).launch()
 
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+ from huggingface_hub import from_pretrained_fastai
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  import gradio as gr
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+ from fastai.vision.all import *
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+
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+
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+ # repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
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+ repo_id = "maviced/intel-image-classification"
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+ learner = from_pretrained_fastai(repo_id)
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+ labels = learner.dls.vocab
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  # Definimos una función que se encarga de llevar a cabo las predicciones
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  def predict(img):
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+ # img = PILImage.create(img)
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+ pred,pred_idx,probs = learner.predict(img)
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  return {labels[i]: float(probs[i]) for i in range(len(labels))}
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  # Creamos la interfaz y la lanzamos.
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+ gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Label(num_top_classes=3),examples=['10000.jpg','10007.jpg']).launch(share=False)