https://github.com/joaobraganca555/extractionanalysistool
Cloud-based tool for multimedia data extraction and analysis, focusing on influencer content. Utilizes YOLOv8 for object/logo detection, Whisper.AI for speech recognition, and EasyOCR for OCR. Includes sentiment analysis with a scalable microservice architecture for content monitoring.
https://github.com/joaobraganca555/extractionanalysistool
aws-s3 content-monitor docker easyocr fastapi image-classification logo-detection microservices multimedia-data-analysis object-detection ocr python rabbitmq sentiment-analysis speech-recognition streamlit whisper yolov8
Last synced: 2 months ago
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Cloud-based tool for multimedia data extraction and analysis, focusing on influencer content. Utilizes YOLOv8 for object/logo detection, Whisper.AI for speech recognition, and EasyOCR for OCR. Includes sentiment analysis with a scalable microservice architecture for content monitoring.
- Host: GitHub
- URL: https://github.com/joaobraganca555/extractionanalysistool
- Owner: joaobraganca555
- Created: 2024-10-14T23:19:07.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-03-10T20:53:44.000Z (3 months ago)
- Last Synced: 2025-03-10T21:34:22.896Z (3 months ago)
- Topics: aws-s3, content-monitor, docker, easyocr, fastapi, image-classification, logo-detection, microservices, multimedia-data-analysis, object-detection, ocr, python, rabbitmq, sentiment-analysis, speech-recognition, streamlit, whisper, yolov8
- Language: Jupyter Notebook
- Homepage:
- Size: 4.65 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# ExtractionAnalysisTool
Cloud-based tool for multimedia data extraction and analysis, focusing on influencer content. Utilizes YOLOv8 for object/logo detection, Whisper.AI for speech recognition, and EasyOCR for OCR. Includes sentiment analysis with a scalable microservice architecture for content monitoring.
## System Architecture & Services Description
| **Service** | **Functionality** | **Task** |
|----------------------------|---------------------------------------------------|------------------------------------------------------------|
| yolo-service | Object Detection | Detect objects in images and video frames |
| yolo-cls-service | Image Classification | Classify images into categories |
| yolo-logo-service | Logo Detection | Detect specific logos in media |
| whisper-service | Speech Recognition | Convert audio to text |
| ocr-service | Optical Character Recognition | Extract text from images and video frames |
| sentiment-service | Sentiment Analysis | Analyse the sentiment of extracted text |
| upload-service | Upload Files | API for uploading files and trigger coordinator |
| coordinator-service | Manage services | Controls and manage services |
| result-service | Stores Data | API for storing service results |
## Application Video
Watch the demo of the application in action: [Video Link](https://github.com/user-attachments/assets/c564dffb-e532-435d-ac4a-fcef40f3129f)
## How to Run the Application
To run the **ExtractionAnalysisTool** locally, follow these steps:
### Prerequisites
- Ensure you have **Docker** and **Docker Compose** installed on your machine.
- You will need an **AWS S3 Bucket**. Update the `.env.example` file with your S3 credentials before proceeding.
### Steps to Run:
1. **Clone the repository**:
```bash
git clone https://github.com/joaobraganca555/ExtractionAnalysisTool.git
cd ExtractionAnalysisTool
2. **Prepare the .env file**:
- Rename .env.example to .env:
```bash
mv .env.example .env
- Add your AWS S3 Bucket credentials and any other necessary configurations to the .env file.
3. **Build the Docker containers**:
```bash
docker-compose build
4. **Start the services**:
```bash
docker-compose up
5. Once the containers are up, the tool will be running, and you can start interacting with it. Use the ports provided the docker compose file.
## Publications
This tool is based on prior research work published in the following articles:
| **Title** | **Conference** | **Publisher** | **Date** | **Pages** | **Link** |
|-----------|--------------|--------------|----------|----------|----------|
| Unveiling the Secrets: In-Depth Analysis of YouTube Video Data and Metadata Extraction | ISAmI 2024 – 15th International Symposium on Ambient Intelligence | Springer Nature | 27 Feb 2025 | pp. 14–24 | [Springer Link](https://link.springer.com/chapter/10.1007/978-3-031-83117-1_2) |
| Unveiling the Secrets: In-Depth Analysis of YouTube Video Data and Metadata Extraction | ISAmI 2024 – 15th International Symposium on Ambient Intelligence | Springer Nature | 27 Feb 2025 | pp. 287–296 | [Springer Link](https://link.springer.com/chapter/10.1007/978-3-031-83117-1_27) |