app.py

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

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

# %% chickli.ipynb 2
#!pip install fastbook
import fastbook
from fastbook import *
#!pip install fastai
from fastai.vision.widgets import *
#!pip install gradio
import gradio as gr

import IPython
from IPython.display import display
from PIL import Image

def search_images(term, max_images=50):
    print(f"Searching for '{term}'")
    return search_images_ddg(term, max_images)

# %% chickli.ipynb 3
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath
#plt = platform.system()
#if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath

learn = load_learner('model.pkl')

breeds = ('Labrador Retrievers','German Shepherds','Golden Retrievers','French Bulldogs','Bulldogs','Beagles','Poodles','Rottweilers','Chihuahua')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    #return dict(zip(breeds, map(float,probs)))
    return "This is " + pred

image = gr.components.Image()
label = gr.components.Label()

examples = ['dog.jpg','labrador.jpeg','dunno.jpg']

for x in examples:
    Image.open(x)

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