CROAK Installer

> 🐸 CROAK - Computer Recognition Orchestration Agent Kit

The official installer and CLI for CROAK, an agentic framework for object detection model development.

Quick Start

``bash


Install from npm

npx croak-cv init

Or install globally

npm install -g croak-cv
croak init
`

What is CROAK?

CROAK is an open-source agentic framework that guides you through the entire object detection pipeline:

- Data Preparation - Scan, validate, and prepare your datasets
- Annotation - Integration with vfrog.ai for professional labeling
- Training - Guided model training with GPU support (local or Modal.com)
- Evaluation - Comprehensive model analysis and diagnostics
- Deployment - Deploy to cloud (vfrog.ai) or edge (TensorRT/ONNX)

CLI Commands

| Command | Description |
|---------|-------------|
| croak init | Initialize CROAK in current directory |
| croak doctor | Check environment and dependencies |
| croak upgrade | Upgrade to latest version |
| croak help | Show help |

$3

Initializes a new CROAK project with interactive configuration:

`bash
croak init
`

Options:
- -y, --yes - Skip prompts, use defaults
- --name - Set project name
- --no-vfrog - Skip vfrog.ai integration
- --no-modal - Skip Modal.com GPU setup

What it creates:

`
your-project/
├── .croak/
│ ├── config.yaml # Project configuration
│ ├── pipeline-state.yaml # Pipeline progress tracking
│ ├── agents/ # Agent definitions
│ ├── workflows/ # Workflow specifications
│ ├── knowledge/ # Knowledge base
│ └── contracts/ # Handoff contracts
├── data/
│ ├── raw/ # Raw images
│ └── processed/ # Processed datasets
├── training/
│ ├── configs/ # Training configurations
│ ├── scripts/ # Training scripts
│ └── experiments/ # Experiment outputs
├── evaluation/
│ └── reports/ # Evaluation reports
└── deployment/
└── edge/ # Edge deployment packages
`

$3

Checks your environment for compatibility:

`bash
croak doctor
`

Checks performed:
- Python 3.10+ installation
- Required Python packages (ultralytics, torch, etc.)
- NVIDIA GPU availability
- Modal.com configuration
- vfrog.ai API key
- Git installation

Options:
- --fix - Attempt to fix issues automatically

$3

Upgrades CROAK to the latest version:

`bash
croak upgrade
`

Options:
- --check - Check for updates without installing

Requirements

- Node.js 18.0.0 or higher
- Python 3.10 or higher
- Git (recommended)
- NVIDIA GPU (optional - can use Modal.com for cloud GPU)

Environment Variables

| Variable | Description | Required |
|----------|-------------|----------|
| VFROG_API_KEY | vfrog.ai API key for annotation | For annotation |
| MODAL_TOKEN_ID | Modal.com token (set via modal setup) | For cloud GPU |

Configuration

After initialization, edit .croak/config.yaml to customize:

`yaml
version: "1.0"

project:
name: "my-detection-project"
task_type: "detection"

training:
framework: "ultralytics"
architecture: "yolov8s"
epochs: 100
batch_size: 16

compute:
provider: "modal" # or "local"
gpu_type: "T4"

tracking:
backend: "mlflow" # or "wandb"
`

Next Steps After Init

1. Add your images to data/raw/

2. Scan your data:
`bash
croak scan
`

3. Prepare your dataset:
`bash
croak prepare
`

4. Train your model:
`bash
croak train
`

5. Evaluate results:
`bash
croak evaluate
`

6. Deploy:
`bash
croak deploy
`

Troubleshooting

$3

Ensure Python 3.10+ is installed and in your PATH:

`bash
python3 --version
`

$3

1. Verify the key at https://vfrog.ai/settings/api
2. Ensure the environment variable is set:
`bash
echo $VFROG_API_KEY
`

$3

CROAK will automatically use Modal.com for cloud GPU training. Run:

`bash
pip install modal
modal setup
``

Links

- Documentation: https://github.com/vfrog-ai/croak
- Issues: https://github.com/vfrog-ai/croak/issues
- vfrog.ai: https://vfrog.ai

License

MIT License - see LICENSE for details.

---

🐸 CROAK — by vfrog.ai