covidapp

app.py

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+import gradio as gr
+from fastai.vision.all import *
+
+learn = load_learner("export_covid.pkl")
+
+labels = learn.dls.vocab
+
+
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+
+title = "Covid Classifier from X-ray Images"
+description = "Covid Classifier from X-ray Image trained with downloaded data from internet. Created as a demo for Gradio and HuggingFace Spaces."
+
+examples = ["COVID-100.png", "COVID-103.png", "normal_5007.png", "normal_5014.png"]
+interpretation = "default"
+enable_queue = True
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=2),
+    title=title,
+    description=description,
+    examples=examples,
+    interpretation=interpretation,
+    enable_queue=enable_queue,
+).launch(share=False)

export_covid.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:23fc9e322e533bb36698b8914460b213e1dbc82696bc66b9b8c55ebf79d76e7f
+size 87510507

requirements.txt

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+fastai
+nltk
+scikit-learn
+pickle