Over the past few months, we’ve been exploring ways to streamline the process of compiling YOLO models for Hailo hardware.
Today, doing this locally requires setting up toolchains, cloning repositories, managing dependencies, and aligning everything with the right environment (a process that can be time-consuming and error-prone).
So, we built something better.
Introducing the DeGirum Cloud Compiler—now in early access. This browser-based tool lets you compile YOLO models into a Hailo-optimized .hef format in just a few clicks. No local setup, no complex configurations.
Just upload your PyTorch checkpoint and get a compiled model, often in under 10 minutes. You can test it instantly in your browser with no additional steps.
All you need is a DeGirum AI Hub account to get started.
What it supports
- YOLOv8 and YOLO11
- Model sizes: n, s, m, l, x
- Tasks including:
- Object detection
- Image classification
- Semantic segmentation
- Oriented bounding box detection
- Keypoint estimation
- Dynamic input resolutions
- Optimized C++ postprocessing integrated via DeGirum PySDK
- Browser-based testing, no downloads required
- Fast compile times (often under 2 minutes)
You’ll benefit from this tool if you:
- Want to bypass complex toolchains
- Need to convert PyTorch YOLO models directly to Hailo-compatible .hef files
- Are experimenting with different model sizes or resolutions
- Prefer validating your model performance immediately before deploying