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app.py

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+from huggingface_hub import from_pretrained_fastai
+import gradio as gr
+from fastai.vision.all import *
+import os
+
+try:
+    import toml
+except ImportError:
+    os.system('pip install toml')
+    import toml
+
+
+# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
+repo_id = "maviced/chest_xray"
+
+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=['IM-0006-0001.jpeg','person100_bacteria_482.jpeg']).launch(share=False)

requirements.txt

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+fastai