CVAT Data Management Module for Odoo - User Guide
Odoo is a low-code, open-source suite of business tools that simplifies operations with drag-and-drop customization and pre-built modules, making it accessible to users without programming expertise.
This module optimizes CVAT (Computer Vision Annotation Tool) workflows by integrating local data management with CVAT's cloud services. It addresses issues like limited search, poor organization, and lack of local tracking. Compatible with Odoo 16 and later, it is ideal for managing large-scale annotation projects with ease and efficiency.
Installation guide
Refer to the following links for Odoo installation instructions:
- Install from packaged installers
- Directly run Odoo source code
- Install Odoo on Docker environment
- Install Odoo on Docker environment in a simpler way
2. Install Required Packages
Run the following command to install the required packages:
pip install cvat-sdk==2.21.0 aiofiles==24.1.0
3. Install the imageset-cvat Odoo Module
Download and install the module from the following link: Imageset-CVAT Odoo Module
1. Local dataset Management
- Manage local datasets (single-level image folders)
- Automatic file counting and verification
- Dataset integrity checking
2. CVAT Server Integration
- Add and manage multiple CVAT server connections
- Store and secure CVAT credentials
- Test connection functionality
- Checkout (import) CVAT projects
3. CVAT Project Synchronization
- Synchronize project information
- Checkout (import) CVAT tasks
- Submit local dataset for task
- Manage project metadata
4. CVAT Task Integration
- Monitor task status
- Synchronize task information and images
- Track annotation progress
5. CVAT Task Image Tracing
- List and search CVAT task images
- Find corresponding location in local machine
1. Authorization information
To configure volume mapping, Adminstration role is necessary. However, all other operations can be carried out by users assigned to the Odat user group. For a quick start, you can use the pre-defined user account: odat-user@example.com with the password "odatuser$123".
2. Setting Up Volume Mapping (for the case working on Docker Container)
3. Managing Local Dataset
3.1 Create new dataset
3.2 View and edit existing dataset
4. Setting Up CVAT Server
4.1 Create new CVAT Server with credential information
4.2 View and test connection
4.3 Checkout project(s)
5. Manage CVAT project
5.1 List checked out CVAT projects
5.2 Synchronize information from CVAT
5.3 Checkout one CVAT task
5.4 Checkout all CVAT tasks
5.5 Submit new task to CVAT
6. Manage CVAT Tasks
6.1 List submitted/checked out CVAT tasks
6.2 Synchronize CVAT task
7. Browsing CVAT image
7.1 List synchronized CVAT images
7.2 Show details of CVAT image
8. Managing Scheduled Actions
8.1 List scheduled actions
8.2 Show/edit details of scheduled action
Common Issues
- Path mapping errors in Docker environment
- Connection timeout with CVAT server
- File permission issues
Solutions
- Verify Docker volume mappings
- Check CVAT server status and credentials
- Ensure proper file permissions
- Review synchronization logs
Best Practices
- Regularly backup local data
- Maintain consistent folder structure
- Use meaningful names for datasets
- Keep CVAT credentials secure
Changelogs
- Version 1.0.1: Initial distribution with basic functions
Contact
- For technical support or further assistance, please contact system administrator odoocvat2025[at]gmail.com. Or create an issue at https://github.com/wws2003/odoocvat-public/issues