# AUTOGENERATED! DO NOT EDIT! File to edit: chapt2.ipynb.

# %% auto 0
__all__ = ["learn", "labels", "examples", "demo", "predict"]

import gradio as gr
import skimage
import timm

# %% chapt2.ipynb 14
from fastai.vision.all import *

# %% chapt2.ipynb 15
learn = load_learner("model.pkl")
labels = learn.dls.vocab


def predict(img):
    img = PILImage.create(img)
    pred, pred_idx, probs = learn.predict(img)
    print(pred)
    print(pred_idx)
    print(probs)

    if probs[pred_idx] > 0.88:
        message = f"I am {round((float(probs[pred_idx])*100),4)}% confident that the picture you uploaded is me.  I am a {pred} bear."
    else:
        message = f"Hmm.. I know what a bear looks like, considering...  but do you? Try uploading an image of a bear, thank you."
    # message = "hi"
    return message


# %% chapt2.ipynb 16
examples = ["a_bear.jpg"]

demo = gr.Blocks()

with demo:
    gr.Markdown("Upload an image, preferably an image of a bear...")
    with gr.Row():
        image_input = gr.Image(type="pil", shape=(512, 512), interactive=True)
        text_output = gr.Textbox(
            label="Response from Bear", placeholder="I'm waiting for an image"
        )
    submit_button = gr.Button("Submit")
    clear_button = gr.Button("Clear")

    submit_button.click(predict, inputs=image_input, outputs=text_output)
    clear_button.click(lambda: None, None, image_input)
    clear_button.click(lambda: None, None, text_output)

demo.launch()