Getting Started with the Hailo Model Zoo

October 13, 2024

The Hailo Model Zoo is your one-stop solution for high-performance deep learning applications. By providing pre-trained models that can be fine-tuned and executed on Hailo devices, it enables developers to build applications that harness the power of AI. In this article, we will walk you through how to get started with the Hailo Model Zoo.

System Requirements

Before diving in, ensure your environment meets the necessary requirements:

Understanding the Hailo Model Zoo

The Hailo Model Zoo stores various pre-trained models in formats like ONNX and TensorFlow, along with Hailo Executable Format (HEF) files that facilitate efficient execution on Hailo hardware. Think of it as a supermarket where each aisle is stocked with models trained for different tasks, like classification, object detection, and segmentation. Instead of having to bake everything from scratch (train the model from the ground up), you can take a ready-made cake (pre-trained model) from the shelf and customize it to your taste (retrain it with your dataset).

Quick Start Guide

To jumpstart your journey, follow these steps:

Clone the Hailo Model Zoo repository:

git clone https://github.com/hailo-ai/hailo_model_zoo.git

Navigate to the directory and install the dependencies:
```
cd hailo_model_zoo; pip install -e .
```
Optionally, install HailoRT if required for running on Hailo-8.
Run the Hailo Model Zoo to print out the information of a model, such as MobileNet-v1:
```
hailomz info mobilenet_v1
```

Retraining Models

If you’d like to tailor a model to your own data, Hailo provides detailed retraining instructions. This gives you the ability to retrain models that were originally trained on internal datasets, effectively giving you the power to customize.

Troubleshooting Installation Issues

If you encounter issues during installation, consider the following troubleshooting steps:

Double-check that all dependencies are correctly installed and compatible with each other.
Ensure you are in the correct virtual environment before running installation commands.
Consult the Hailo support for specific errors you may be facing.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

By following these guidelines, you’ll be well on your way to leveraging the capabilities of the Hailo Model Zoo to create high-performance AI applications.