administrator/frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2026-04-11 09:37:37 +03:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

Don't use GPU for training

Browse Source
This commit is contained in:
Nicolas Mowen 2025-10-31 12:26:18 -06:00
parent 057d44d6a9
commit b4ba2ce7c4
3 changed files with 0 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
docker/tensorrt/requirements-amd64.txt
View File

@ -13,7 +13,6 @@ nvidia_cusolver_cu12==11.6.3.*; platform_machine == 'x86_64'
nvidia_cusparse_cu12==12.5.1.*; platform_machine == 'x86_64'
nvidia_nccl_cu12==2.23.4; platform_machine == 'x86_64'
nvidia_nvjitlink_cu12==12.5.82; platform_machine == 'x86_64'
tensorflow==2.19.*; platform_machine == 'x86_64'
onnx==1.16.*; platform_machine == 'x86_64'
onnxruntime-gpu==1.22.*; platform_machine == 'x86_64'
protobuf==3.20.3; platform_machine == 'x86_64'

1
docs/docs/configuration/custom_classification/object_classification.md
View File

@ -10,7 +10,6 @@ Object classification allows you to train a custom MobileNetV2 classification mo
Object classification models are lightweight and run very fast on CPU. Inference should be usable on virtually any machine that can run Frigate.
Training the model does briefly use a high amount of system resources for about 1–3 minutes per training run. On lower-power devices, training may take longer.
When running the `-tensorrt` image, Nvidia GPUs will automatically be used to accelerate training.
## Classes

1
docs/docs/configuration/custom_classification/state_classification.md
View File

@ -10,7 +10,6 @@ State classification allows you to train a custom MobileNetV2 classification mod
State classification models are lightweight and run very fast on CPU. Inference should be usable on virtually any machine that can run Frigate.
Training the model does briefly use a high amount of system resources for about 1–3 minutes per training run. On lower-power devices, training may take longer.
When running the `-tensorrt` image, Nvidia GPUs will automatically be used to accelerate training.
## Classes