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