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| # huggingface运行版本,app.py | |
| import streamlit as st | |
| from transformers import pipeline | |
| from PIL import Image | |
| # Load the age classification pipeline | |
| pipe = pipeline("image-classification", model="nateraw/vit-age-classifier") | |
| def classify_age(image): | |
| """Classifies the age group of the person in the given image.""" | |
| results = pipe(image) | |
| return results | |
| # Streamlit UI | |
| st.title("Age Classification App") | |
| st.write("Upload an image to classify the age group of the person in it.") | |
| uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"]) | |
| if uploaded_file is not None: | |
| image = Image.open(uploaded_file).convert("RGB") | |
| st.image(image, caption="Uploaded Image", use_column_width=True) | |
| st.write("Classifying...") | |
| age_results = classify_age(image) | |
| st.write(f"Predicted Age Range: {age_results[0]['label']}") | |