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| from PIL import Image | |
| from dotenv import load_dotenv | |
| import streamlit as st | |
| from transformers import pipeline | |
| #pipe = pipeline("image-classification", model="Falconsai/nsfw_image_detection") | |
| st.title("Adult Content Detector") | |
| load_dotenv() | |
| model = pipeline("image-classification", model="Falconsai/nsfw_image_detection") | |
| image_path = st.file_uploader("Choose a image",type=['jpg','jpeg','png']) | |
| if st.button("Checking"): | |
| with st.spinner('Checking Content...'): | |
| img = Image.open(image_path) | |
| result = model(images=img) | |
| nsfw_score = next((item['score'] for item in result if item['label']=='nsfw'),None) | |
| st.write(nsfw_score) | |
| st.subheader(f"Adult Content Probability : {str(round(nsfw_score*100,2))} %") | |
| st.slider("",0,100,int(nsfw_score*100),1) | |
| if nsfw_score>0.1: | |
| st.subheader("Your Content is not safe❌") | |
| st.text("Cannot Display the Image") | |
| else: | |
| st.subheader("Your Content is Safe") | |
| st.image(img) | |