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import gradio as gr | |
from fastai.vision.all import * | |
import skimage | |
learn = load_learner('itlarni_zoti_klassifikatsiyasi.pkl') | |
labels = learn.dls.vocab | |
def predict(img): | |
img = PILImage.create(img) | |
pred, pred_idx, probs = learn.predict(img) | |
return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
title = 'Dog type Classifier' | |
description = 'A dog type classifier trained on random images from internet with fastai. Created as a demo for Gradio and HuggingFace Spaces.' | |
#examples = ['GrizzlyBearJeanBeaufort.jpg'] | |
gr.Interface(fn = predict, | |
inputs = 'image', | |
outputs = 'label', | |
title = title, | |
description = description | |
#examples = examples | |
).launch() |