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Download app.py from tsambo/Demo_Image_classifier: direct link, hf CLI and curl.
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https://huggingface.co/spaces/tsambo/Demo_Image_classifier/resolve/main/app.py
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curl -L -o app.py https://huggingface.co/spaces/tsambo/Demo_Image_classifier/resolve/main/app.py
672 Bytes
| import streamlit as st | |
| from transformers import pipeline | |
| from transformers import BeitFeatureExtractor, BeitForImageClassification | |
| from PIL import Image | |
| import requests | |
| pipeline = pipeline(task = "image-classification", model = "microsoft/beit-base-patch16-224-pt22k-ft22k") | |
| st.title("Predict the class of an image") | |
| file_name = st.file_uploader("Upload an image here") | |
| if file_name is not None: | |
| col1, col2 = st.columns(2) | |
| image = Image.open(file_name) | |
| col1.image(image, use_column_width=True) | |
| predictions = pipeline(image) | |
| col2.header("Probabilities") | |
| for p in predictions: | |
| col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%") | |