Deploy app

app.py

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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_chestXrayCPU"
+
+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 = [
+    'IM-0071-0001.jpeg',
+    'IM-0091-0001.jpeg',
+    'NORMAL2-IM-0249-0001.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)

requirements.txt

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+fastai
+toml