feat:added readme.md

README.md

@@ -1,152 +1,22 @@
-# AI-Contain-Checker
-
-A modular AI content detection system with support for **image classification**, **image edit detection**, **Nepali text classification**, and **general text classification**. Built for performance and extensibility, it is ideal for detecting AI-generated content in both visual and textual forms.
-
-
-## 🌟 Features
-
-### 🖼️ Image Classifier
-
-* **Purpose**: Classifies whether an image is AI-generated or a real-life photo.
-* **Model**: Fine-tuned **InceptionV3** CNN.
-* **Dataset**: Custom curated dataset with **\~79,950 images** for binary classification.
-* **Location**: [`features/image_classifier`](features/image_classifier)
-* **Docs**: [`docs/features/image_classifier.md`](docs/features/image_classifier.md)
-
-### 🖌️ Image Edit Detector
-
-* **Purpose**: Detects image tampering or post-processing.
-* **Techniques Used**:
-
-  * **Error Level Analysis (ELA)**: Visualizes compression artifacts.
-  * **Fast Fourier Transform (FFT)**: Detects unnatural frequency patterns.
-* **Location**: [`features/image_edit_detector`](features/image_edit_detector)
-* **Docs**:
-
-  * [ELA](docs/detector/ELA.md)
-  * [FFT](docs/detector/fft.md )
-  * [Metadata Analysis](docs/detector/meta.md)
-  * [Backend Notes](docs/detector/note-for-backend.md)
-
-### 📝 Nepali Text Classifier
-
-* **Purpose**: Determines if Nepali text content is AI-generated or written by a human.
-* **Model**: Based on `XLMRClassifier` fine-tuned on Nepali language data.
-* **Dataset**: Scraped dataset of **\~18,000** Nepali texts.
-* **Location**: [`features/nepali_text_classifier`](features/nepali_text_classifier)
-* **Docs**: [`docs/features/nepali_text_classifier.md`](docs/features/nepali_text_classifier.md)
-
-### 🌐 English Text Classifier
-
-* **Purpose**: Detects if English text is AI-generated or human-written.
-* **Pipeline**:
-
-  * Uses **GPT2 tokenizer** for input preprocessing.
-  * Custom binary classifier to differentiate between AI and human-written content.
-* **Location**: [`features/text_classifier`](features/text_classifier)
-* **Docs**: [`docs/features/text_classifier.md`](docs/features/text_classifier.md)
-
 ---
-
-## 🗂️ Project Structure
-
-```bash
-AI-Checker/
-│
-├── app.py                  # Main FastAPI entry point
-├── config.py               # Configuration settings
-├── Dockerfile              # Docker build script
-├── Procfile                # Deployment file for Heroku or similar
-├── requirements.txt        # Python dependencies
-├── README.md               # You are here 📘
-│
-├── features/               # Core detection modules
-│   ├── image_classifier/
-│   ├── image_edit_detector/
-│   ├── nepali_text_classifier/
-│   └── text_classifier/
-│
-├── docs/                   # Internal and API documentation
-│   ├── api_endpoints.md
-│   ├── deployment.md
-│   ├── detector/
-│   │   ├── ELA.md
-│   │   ├── fft.md
-│   │   ├── meta.md
-│   │   └── note-for-backend.md
-│   ├── functions.md
-│   ├── nestjs_integration.md
-│   ├── security.md
-│   ├── setup.md
-│   └── structure.md
-│
-├── IMG_Models/             # Saved image classifier model(s)
-│   └── latest-my_cnn_model.h5
-│
-├── notebooks/              # Experimental and debug notebooks
-├── static/                 # Static assets if needed
-└── test.md                 # Test notes
-````
-
+title: Testing AI Contain
+emoji: 🤖
+colorFrom: blue
+colorTo: green
+sdk: docker
+sdk_version: "latest"
+app_file: app.py
+pinned: false
 ---
 
-## 📚 Documentation Links
+# Testing AI Contain
 
-* [API Endpoints](docs/api_endpoints.md)
-* [Deployment Guide](docs/deployment.md)
-* [Detector Documentation](docs/detector/)
+This Hugging Face Space uses **Docker** to run a custom environment for AI content detection.
 
-  * [Error Level Analysis (ELA)](docs/detector/ELA.md)
-  * [Fast Fourier Transform (FFT)](docs/detector/fft.md)
-  * [Metadata Analysis](docs/detector/meta.md)
-  * [Backend Notes](docs/detector/note-for-backend.md)
-* [Functions Overview](docs/functions.md)
-* [NestJS Integration Guide](docs/nestjs_integration.md)
-* [Security Details](docs/security.md)
-* [Setup Instructions](docs/setup.md)
-* [Project Structure](docs/structure.md)
+## How to run locally
 
----
-
-## 🚀 Usage
-
-1. **Install dependencies**
-
-   ```bash
-   pip install -r requirements.txt
-   ```
-
-2. **Run the API**
-
-   ```bash
-   uvicorn app:app --reload
-   ```
-
-3. **Build Docker (optional)**
-
-   ```bash
-   docker build -t ai-contain-checker .
-   docker run -p 8000:8000 ai-contain-checker
-   ```
-
----
-
-## 🔐 Security & Integration
-
-* **Token Authentication** and **IP Whitelisting** supported.
-* NestJS integration guide: [`docs/nestjs_integration.md`](docs/nestjs_integration.md)
-* Rate limiting handled using `slowapi`.
-
----
-
-## 🛡️ Future Plans
-
-* Add **video classifier** module.
-* Expand dataset for **multilingual** AI content detection.
-* Add **fine-tuning UI** for models.
-
----
-
-## 📄 License
+```bash
+docker build -t testing-ai-contain .
+docker run -p 7860:7860 testing-ai-contain
 
-See full license terms here: [`LICENSE.md`](license.md)
+```

READMEs.md

@@ -0,0 +1,152 @@
+# AI-Contain-Checker
+
+A modular AI content detection system with support for **image classification**, **image edit detection**, **Nepali text classification**, and **general text classification**. Built for performance and extensibility, it is ideal for detecting AI-generated content in both visual and textual forms.
+
+
+## 🌟 Features
+
+### 🖼️ Image Classifier
+
+* **Purpose**: Classifies whether an image is AI-generated or a real-life photo.
+* **Model**: Fine-tuned **InceptionV3** CNN.
+* **Dataset**: Custom curated dataset with **\~79,950 images** for binary classification.
+* **Location**: [`features/image_classifier`](features/image_classifier)
+* **Docs**: [`docs/features/image_classifier.md`](docs/features/image_classifier.md)
+
+### 🖌️ Image Edit Detector
+
+* **Purpose**: Detects image tampering or post-processing.
+* **Techniques Used**:
+
+  * **Error Level Analysis (ELA)**: Visualizes compression artifacts.
+  * **Fast Fourier Transform (FFT)**: Detects unnatural frequency patterns.
+* **Location**: [`features/image_edit_detector`](features/image_edit_detector)
+* **Docs**:
+
+  * [ELA](docs/detector/ELA.md)
+  * [FFT](docs/detector/fft.md )
+  * [Metadata Analysis](docs/detector/meta.md)
+  * [Backend Notes](docs/detector/note-for-backend.md)
+
+### 📝 Nepali Text Classifier
+
+* **Purpose**: Determines if Nepali text content is AI-generated or written by a human.
+* **Model**: Based on `XLMRClassifier` fine-tuned on Nepali language data.
+* **Dataset**: Scraped dataset of **\~18,000** Nepali texts.
+* **Location**: [`features/nepali_text_classifier`](features/nepali_text_classifier)
+* **Docs**: [`docs/features/nepali_text_classifier.md`](docs/features/nepali_text_classifier.md)
+
+### 🌐 English Text Classifier
+
+* **Purpose**: Detects if English text is AI-generated or human-written.
+* **Pipeline**:
+
+  * Uses **GPT2 tokenizer** for input preprocessing.
+  * Custom binary classifier to differentiate between AI and human-written content.
+* **Location**: [`features/text_classifier`](features/text_classifier)
+* **Docs**: [`docs/features/text_classifier.md`](docs/features/text_classifier.md)
+
+---
+
+## 🗂️ Project Structure
+
+```bash
+AI-Checker/
+│
+├── app.py                  # Main FastAPI entry point
+├── config.py               # Configuration settings
+├── Dockerfile              # Docker build script
+├── Procfile                # Deployment file for Heroku or similar
+├── requirements.txt        # Python dependencies
+├── README.md               # You are here 📘
+│
+├── features/               # Core detection modules
+│   ├── image_classifier/
+│   ├── image_edit_detector/
+│   ├── nepali_text_classifier/
+│   └── text_classifier/
+│
+├── docs/                   # Internal and API documentation
+│   ├── api_endpoints.md
+│   ├── deployment.md
+│   ├── detector/
+│   │   ├── ELA.md
+│   │   ├── fft.md
+│   │   ├── meta.md
+│   │   └── note-for-backend.md
+│   ├── functions.md
+│   ├── nestjs_integration.md
+│   ├── security.md
+│   ├── setup.md
+│   └── structure.md
+│
+├── IMG_Models/             # Saved image classifier model(s)
+│   └── latest-my_cnn_model.h5
+│
+├── notebooks/              # Experimental and debug notebooks
+├── static/                 # Static assets if needed
+└── test.md                 # Test notes
+````
+
+---
+
+## 📚 Documentation Links
+
+* [API Endpoints](docs/api_endpoints.md)
+* [Deployment Guide](docs/deployment.md)
+* [Detector Documentation](docs/detector/)
+
+  * [Error Level Analysis (ELA)](docs/detector/ELA.md)
+  * [Fast Fourier Transform (FFT)](docs/detector/fft.md)
+  * [Metadata Analysis](docs/detector/meta.md)
+  * [Backend Notes](docs/detector/note-for-backend.md)
+* [Functions Overview](docs/functions.md)
+* [NestJS Integration Guide](docs/nestjs_integration.md)
+* [Security Details](docs/security.md)
+* [Setup Instructions](docs/setup.md)
+* [Project Structure](docs/structure.md)
+
+---
+
+## 🚀 Usage
+
+1. **Install dependencies**
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+2. **Run the API**
+
+   ```bash
+   uvicorn app:app --reload
+   ```
+
+3. **Build Docker (optional)**
+
+   ```bash
+   docker build -t ai-contain-checker .
+   docker run -p 8000:8000 ai-contain-checker
+   ```
+
+---
+
+## 🔐 Security & Integration
+
+* **Token Authentication** and **IP Whitelisting** supported.
+* NestJS integration guide: [`docs/nestjs_integration.md`](docs/nestjs_integration.md)
+* Rate limiting handled using `slowapi`.
+
+---
+
+## 🛡️ Future Plans
+
+* Add **video classifier** module.
+* Expand dataset for **multilingual** AI content detection.
+* Add **fine-tuning UI** for models.
+
+---
+
+## 📄 License
+
+See full license terms here: [`LICENSE.md`](license.md)

readme.md

@@ -1,22 +0,0 @@
----
-title: Testing AI Contain
-emoji: 🤖
-colorFrom: blue
-colorTo: green
-sdk: docker
-sdk_version: "latest"
-app_file: app.py
-pinned: false
----
-
-# Testing AI Contain
-
-This Hugging Face Space uses **Docker** to run a custom environment for AI content detection.
-
-## How to run locally
-
-```bash
-docker build -t testing-ai-contain .
-docker run -p 7860:7860 testing-ai-contain
-
-```