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app.py

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+# AUTOGENERATED! DO NOT EDIT! File to edit: 02d_deployment.ipynb.
+
+# %% auto 0
+__all__ = ['uname', 'dsname', 'url', 'model_root', 'model_repo', 'learn', 'examples', 'labels', 'article', 'demo', 'predict']
+
+# %% 02d_deployment.ipynb 13
+from huggingface_hub import from_pretrained_fastai
+from fastai.vision.all import *
+import gradio as gr
+
+# %% 02d_deployment.ipynb 18
+uname = "rahuketu86"
+dsname = "PandemicSafety"
+url = "https://zealmaker.com/curations/courses/fastai_dl1/02d_deployment"
+model_root = f"Model-{dsname}"
+model_repo = f"{uname}/{model_root}"; model_repo
+learn = from_pretrained_fastai(model_repo)
+
+# %% 02d_deployment.ipynb 23
+examples = list(get_image_files(".").map(lambda e : str(e))); examples
+
+# %% 02d_deployment.ipynb 25
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    return dict(zip(labels, map(float, probs)))
+
+# %% 02d_deployment.ipynb 26
+article="<p style='text-align: center'><a href='https://zealmaker.com/curations/courses/fastai_dl1/02d_deployment' target='_blank'>zealmaker.com</a></p>"
+demo = gr.Interface(fn=predict, 
+                    inputs=gr.inputs.Image(shape=(512, 512)), 
+                    outputs=gr.outputs.Label(num_top_classes=2),
+                    title = dsname,
+                    article=article,
+                    interpretation='default',
+                    examples = examples,
+                    enable_queue=True
+                   );demo
+demo.launch()