app.py

# AUTOGENERATED! DO NOT EDIT! File to edit: gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb.

# %% auto 0
__all__ = ['learn_inf', 'lbl_pred', 'image', 'label', 'examples', 'intf', 'btn_upload', 'classify_image', 'on_click_classify']

# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 25
from fastai.vision.all import *
import gradio as gr


# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 27
learn_inf = load_learner('bears/export.pkl')

# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 33
lbl_pred = learn_inf.dls.vocab

def classify_image(img):
    img = img.to_thumb(128,128)
    pred,pred_idx,probs = learn_inf.predict(img)
    return dict(zip(lbl_pred, map(float, probs)))

# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 34
image = gr.Image(type="pil")
label = gr.Label()
examples = ['images/black.jpg', 'images/grizzly.jpg', 'images/teddy.jpg']
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False, debug=True)

# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 35
def on_click_classify(change):
    img = PILImage.create(btn_upload.data[-1])
    out_pl.clear_output()
    with out_pl: display(img.to_thumb(128,128))
    pred,pred_idx,probs = learn_inf.predict(img)
    lbl_pred.value = f'Prediction: {pred}; Probability: {probs[pred_idx]:.04f}'

btn_run.on_click(on_click_classify)

# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 36
btn_upload = widgets.FileUpload()

# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 37
VBox([widgets.Label('Select your bear!'),
      btn_upload, btn_run, out_pl, lbl_pred])