Create app.py

app.py

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+from huggingface_hub import from_pretrained_fastai
+import gradio as gr
+from fastai.vision.all import *
+
+repo_id = "ancebuc/xray-chest-classification"
+
+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=['normal.jpeg','pneumonia.jpeg']).launch(share=False)
+ 
+