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mookkanvas
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•
6009e45
1
Parent(s):
cf4cf1c
Create app.py
Browse files
app.py
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import pandas as pd
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from PIL import Image
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import streamlit as st
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from transformers import pipeline
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pipeline = pipeline(task="image-classification", model="nateraw/vit-age-classifier")
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def predict(image):
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predictions = pipeline(image)
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return {p["label"]: p["score"] for p in predictions}
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def main():
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st.title("Age Classification From Image")
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with st.form("my_form"):
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uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "jpeg", "png"])
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if uploaded_file is not None:
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# Display the uploaded image
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image = Image.open(uploaded_file)
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st.image(image, caption="Your uploaded Image", use_column_width=True)
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clicked = st.form_submit_button("Press to predict")
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if clicked:
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results = predict(image)
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k = []
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v = []
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for key, value in results.items():
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value = round(value*100,2)
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v.append(value)
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k.append(key)
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vp = [str(item) + '%' for item in v]
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result = k[0]
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st.success('The predicted age is {}'.format(result))
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df = pd.DataFrame({'Prediction': k,'Accuracy':vp})
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st.dataframe(df,hide_index=True)
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if __name__ == "__main__":
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main()
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