# AUTOGENERATED! DO NOT EDIT! File to edit: ../../A_Practical_Deep_Learning/Untitled.ipynb.

# %% auto 0
__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']

# %% ../../A_Practical_Deep_Learning/Untitled.ipynb 1
from fastai.vision.all import *
import gradio as gr

def is_cat(x): return x[0].isupper()

# %% ../../A_Practical_Deep_Learning/Untitled.ipynb 4
learn = load_learner("model (1).pkl")

# %% ../../A_Practical_Deep_Learning/Untitled.ipynb 6
categories = ('Dog', 'Cat')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))

# %% ../../A_Practical_Deep_Learning/Untitled.ipynb 8
image = gr.components.Image(shape=(192,192))
label = gr.components.Label()
# examples = [r"C:\Users\Kush\Downloads\dog.jpg", r"C:\Users\Kush\Downloads\scared-hamster.jpg", r"C:\Users\Kush\Downloads\Converse Welcomes Baby Keem to the Family.png"]

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label)
intf.launch(inline=False, share=True)

# %%