Rename qpp.py to app.py

app.py

@@ -0,0 +1,36 @@
+import streamlit as st
+from transformers import pipeline, AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+
+# Title of the web app
+st.title("NSFW Image Detection with Hugging Face")
+
+# Description
+st.write("""
+This is a simple web application that uses a Hugging Face model to detect NSFW content in images.
+Upload an image and the model will classify whether it contains NSFW content.
+""")
+
+# Upload image
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Display the uploaded image
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Load the model and processor
+    processor = AutoImageProcessor.from_pretrained("Falconsai/nsfw_image_detection")
+    model = AutoModelForImageClassification.from_pretrained("Falconsai/nsfw_image_detection")
+
+    # Use the pipeline for image classification
+    pipe = pipeline("image-classification", model=model, feature_extractor=processor)
+
+    # Classify the image
+    with st.spinner('Classifying...'):
+        results = pipe(image)
+    
+    # Display the classification results
+    st.write("Classification Results:")
+    for result in results:
+        st.write(f"Label: {result['label']}, Score: {result['score']:.4f}")