5 Commits

Include renames

Author	SHA1	Message	Date
3 people	b2a7e992c9	Request FP16 TensorRT engine for ONNX detector with device Tensorrt (#24923) ... * Request FP16 TensorRT engine for ONNX detector with device Tensorrt get_ort_providers only enables trt_fp16_enable when requires_fp16 is passed, and the ONNX detector never passed it, so device: Tensorrt always built an FP32 engine. USE_FP16=False still disables FP16. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * Make TensorRT FP16 opt-in via USE_FP16 only Drop the unused requires_fp16 parameter from get_ort_providers and decide trt_fp16_enable from the USE_FP16 environment variable alone, defaulting to false. Revert the ONNX detector change and document USE_FP16=true for device: Tensorrt. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * Drop the TensorRT docs line The stock image ships only the TensorRT runtime, not the builder libraries needed to create engines, so the instructions were misleading. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>	2026-11-09 09:46:25 -07:00
Nicolas MowenandGitHub	d7bb780ff8	Upgrade to ROCm 10.1 (#24708) ... * Update to ROCm 10.1 * Update docs for new setup	2026-10-18 12:13:32 -05:00
Josh HawkinsandGitHub	b79e043976	Reduce idle CPU from thread pools (#24652) ... * reduce idle cpu from onnxruntime and opencv thread pools ONNX Runtime's intra-op threads kept spinning for about 1 s after every run, so a CPU enrichment called once a second or more kept most cores busy. On a 16 thread machine, arcface at one call per second used 9.4 s of CPU per call with ~360 ms latency. Enrichment sessions on the CPU execution provider now set `session.intra_op.allow_spinning` to 0, which drops that to 1.9 s with no latency change. Detector sessions and GPU providers are unchanged, since disabling spinning doubled yolov9-t latency on CPU (12 to 23 ms). The output and embeddings processes now run OpenCV single threaded, like the camera tracking process. A 4 camera birdseye redraw at 1080p drops from 13.7 to 4.0 ms of CPU, and the full frame conversion in the enrichment processors from 23 to 2.7 ms, each adding about 1 ms of wall time. * test that only cpu enrichment sessions disable ort spinning * patch out the neural engine in the spinning test	2026-10-13 07:46:55 -06:00
Nick RogersandGitHub	c959df32c9	Apple Silicon Macs via lighter: ONNX detector on the Neural Engine and media engine decode (#24453) ... * Run ONNX models on a Mac's Neural Engine through lighter's plugin provider lighter's lighter.sh/ane device places an ONNX Runtime plugin execution provider in the container. When it is present, the ONNX session setup registers it once and opens sessions on its Neural Engine device, the same place CUDA, ROCm and OpenVINO are chosen, so the onnx detector (and any model that is not pinned to the CPU) runs there with no configuration. The hardware probe reports it as an onnx unit. * docs: hardware decode on an Apple Silicon Mac under lighter A community section on the video decoding page: lighter's lighter.sh/video device, hwaccel_args -c:v h264_v4l2m2m, and why the Raspberry Pi presets decode a single-stream camera in software. The detector docs link to it. * docs: set the lighter decoder per camera when codecs are mixed * docs: the ONNX detector on a Mac's Neural Engine under lighter * Format the Neural Engine provider setup * Fall back to the default providers when the Neural Engine cannot load a model * Apple Silicon ffmpeg presets for lighter's media engine, recommended when it is present	2026-09-24 15:37:32 -06:00
Josh HawkinsandNicolas Mowen	70ce193e09	Improve System Health pane (#24188) ... * build out system health pane * tweaks * fixes * fix notice link so it opens the correct camera * tweak language	2026-09-12 07:30:04 -06:00