orange¶
A high-performance, GPU-accelerated multi-camera capture, streaming and recording application for Emergent Vision GigE cameras.

Overview¶
orange is built for high-throughput, time-synchronized multi-camera recording. Encoding is GPU-accelerated and scales with the number of GPUs in the host. PTP keeps cameras aligned to sub-frame precision, and a multi-host architecture (one GUI host coordinating any number of headless cam_server nodes over ENet) lets a recording rig scale beyond what a single machine can drive — both in camera count and aggregate pixel rate. Optional TensorRT-based YOLO detection runs on the live streams when a model is provided.
Video demo¶
Features¶
- Multiple cameras streaming
- PTP synchronization
- GPU accelerated encoding (h264, hevc)
- Support mono and color Emergent cameras
- Multi-host capture (one GUI host coordinating several headless
cam_servernodes)
Performance¶
Encoding performance using a single A6000 GPU with 7MP Emergent cameras:

orange distributes per-camera encoding across GPUs (assigned by gpu_id in each camera's config), so total throughput scales with the number of GPUs in the host — adding GPUs is the recommended path to more cameras or higher resolutions.
Where to start¶
- New install: Installation — system requirements, dependencies, build.
- Already built: Configuration → Local mode or Network mode.
- Real-time detection: Real-time detection — train and deploy a YOLOv8 model.
- Multi-camera sync: PTP setup.