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from fastai.vision.all import *
from fastai.text.all import *
from fastai.collab import *
from fastai.tabular.all import *
# import pathlib
# temp = pathlib.PosixPath
# pathlib.PosixPath = pathlib.WindowsPath
import gradio as gr
learn = load_learner('model.pkl')
categories = ('golden', 'not golden')
def classify_img(img):
pred, pred_idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.label(num_top_classes=2)
#examples = ["golden_retriever.jpg", "cat.jpg", "dog.jpg"]
intf = gr.Interface(fn=classify_img, inputs=image, outputs=label)
intf.launch(inline=False) |