app.py

# 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()