Create Abouttheproject

Abouttheproject

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+# ToxiScan
+
+ToxiScan is a Hugging Face Space application that classifies images as toxic or non-toxic using a pre-trained Vision Transformer (ViT) model from Hugging Face. Built with Streamlit, it provides a user-friendly interface for uploading images and viewing classification results.
+
+## Features
+- **Image Upload:** Users can upload images (JPG, PNG, JPEG) via the Streamlit frontend.
+- **Toxic Classification:** Leverages a pre-trained ViT model (`google/vit-base-patch16-224`) to predict if an image is toxic or non-toxic.
+- **Results Display:** Shows the prediction label (Toxic/Non-Toxic), confidence scores, and a bar chart visualization.
+- **Deployment:** Hosted entirely on Hugging Face Spaces.
+
+## Project Structure
+- **`app.py`**: Main Streamlit application that handles the frontend and backend logic.
+- **`utils.py`**: Helper functions for image processing and prediction with ViT.
+- **`requirements.txt`**: Lists Python dependencies for the project.
+- **`data/`**: Optional folder with `train/` and `test/` subfolders as placeholders for a dataset (not required for basic functionality).
+- **`toxic_classifier.pth`** (optional): Fine-tuned model weights for accurate toxic detection (upload separately).
+
+## How It Works
+1. **Upload:** Users upload an image through the Streamlit interface.
+2. **Processing:** The app uses a pre-trained ViT model to process the image.
+3. **Prediction:** The model outputs a binary classification (toxic or non-toxic) with confidence scores.
+4. **Display:** Results are shown with the uploaded image, prediction label, confidence percentages, and a bar chart.
+
+## Setup on Hugging Face
+1. **Create Space:**
+   - Name: `ToxiScan`
+   - SDK: `Streamlit`
+   - Visibility: Public or Private
+2. **Upload Files:**
+   - Push all files via Git (see deployment steps below).
+3. **Fine-tuning (Optional):**
+   - Fine-tune the ViT model locally with a toxic/non-toxic dataset and upload `toxic_classifier.pth`.
+
+## Deployment Steps
+```bash
+# On your local machine
+git init
+git add .
+git commit -m "Initial ToxiScan setup with Streamlit"
+git remote add origin https://huggingface.co/spaces/JanviMl/ToxiScan
+git push https://JanviMl:hf_<your-token>@huggingface.co/spaces/JanviMl/ToxiScan main