fast.ai-lesson2 / app.py
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from fastai.vision.all import *
import gradio as gr
#this func is from learner
def is_cat(x): return x[0].isupper()
# #posix path error handler from stack overflow
# import pathlib
# temp = pathlib.PosixPath
# pathlib.PosixPath = pathlib.WindowsPath
learn = load_learner("model.pkl")
categories = ('Dog','Cat')
def classify_image(img):
pred, idx,probs =learn.predict(img)
return dict(zip(categories, map(float,probs)))
image = gr.components.Image(shape = (192,192))
# image = gr.components
label = gr.components.Label()
examples = ['dog.jpg']
intf = gr.Interface(fn = classify_image , inputs = image, outputs=label, examples=examples)
intf.launch(inline = False)