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frigate/docker/tensorrt/requirements-amd64.txt

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Nvidia TensorRT detector (#4718) * Initial WIP dockerfile and scripts to add tensorrt support * Add tensorRT detector * WIP attempt to install TensorRT 8.5 * Updates to detector for cuda python library * TensorRT Cuda library rework WIP Does not run * Fixes from rebase to detector factory * Fix parsing output memory pointer * Handle TensorRT logs with the python logger * Use non-async interface and convert input data to float32. Detection runs without error. * Make TensorRT a separate build from the base Frigate image. * Add script and documentation for generating TRT Models * Add support for TensorRT devcontainer * Add labelmap to trt model script and docs. Cleanup of old scripts. * Update detect to normalize input tensor using model input type * Add config for selecting GPU. Fix Async inference. Update documentation. * Update some CUDA libraries to clean up version warning * Add CI stage to build TensorRT tag * Add note in docs for image tag and model support
2022-12-30 19:53:17 +03:00
# NVidia TensorRT Support (amd64 only)
Upgrade TensorRT to 8.5.3 (#7006) * Update to latest tensorrt (8.6.1) release * Build trt libyolo_layer.so in container * Update tensorrt_models script to convert models from the frigate container * Fix typo in model script * Fix paths to yolo lib and models folder * Add S6 scripts to test and convert specified TensortRT models at startup. Rearrange tensorrt files into a docker support folder. * Update TensorRT documentation to reflect the new model conversion process and minimum HW support. * Fix model_cache path to live in config directory * Move tensorrt s6 files to the correct directory * Fix issues in model generation script * Disable global timeout for s6 services * Add version folder to tensorrt model_cache path * Include TensorRT version 8.5.3 * Add numpy requirement prior to removal of np.bool * This TRT version uses a mixture of cuda dependencies * Redirect stdout from noisy model conversion
2023-07-06 22:20:33 +03:00
--extra-index-url 'https://pypi.nvidia.com'
Update python deps (#15618) * Update opencv * Update cython * Update scikit * Update scipy
2024-12-20 19:48:14 +03:00
cython == 3.0.*; platform_machine == 'x86_64'
Upgrade TensorRT to 8.5.3 (#7006) * Update to latest tensorrt (8.6.1) release * Build trt libyolo_layer.so in container * Update tensorrt_models script to convert models from the frigate container * Fix typo in model script * Fix paths to yolo lib and models folder * Add S6 scripts to test and convert specified TensortRT models at startup. Rearrange tensorrt files into a docker support folder. * Update TensorRT documentation to reflect the new model conversion process and minimum HW support. * Fix model_cache path to live in config directory * Move tensorrt s6 files to the correct directory * Fix issues in model generation script * Disable global timeout for s6 services * Add version folder to tensorrt model_cache path * Include TensorRT version 8.5.3 * Add numpy requirement prior to removal of np.bool * This TRT version uses a mixture of cuda dependencies * Redirect stdout from noisy model conversion
2023-07-06 22:20:33 +03:00
nvidia-cuda-runtime-cu12 == 12.1.*; platform_machine == 'x86_64'
Add missing packages and cleanup ldconfig
2025-06-07 20:07:18 +03:00
nvidia-cublas-cu12==12.6.4.*; platform_machine == 'x86_64'
Update cudnn and onnxruntime (#16332)
2025-02-05 19:00:57 +03:00
nvidia-cudnn-cu12 == 9.5.0.*; platform_machine == 'x86_64'
Simplify tensorrt (#16835) * Remove unneccessary trt wheels build * Cleanup * Try without local cuda * Keep specific cuda libs only * Cleanup * Add newer libcufft * remove target * Include more
2025-02-26 23:39:19 +03:00
nvidia-cufft-cu12==11.*; platform_machine == 'x86_64'
Add missing packages and cleanup ldconfig
2025-06-07 20:07:18 +03:00
nvidia-curand-cu12==10.3.9.*; platform_machine == 'x86_64'
nvidia-cuda-nvrtc-cu12==12.6.*; platform_machine == 'x86_64'
Deps updates (#14556) * Update nvidia deps * Update python deps * Update web deps
2024-10-24 16:48:14 +03:00
onnx==1.16.*; platform_machine == 'x86_64'
Intel updates (#18493) * Update openvino and onnxruntime * Install icd and level-zero-gpu deps from intel directly * Install * Add dep * Fix package install
2025-05-31 00:30:21 +03:00
onnxruntime-gpu==1.22.*; platform_machine == 'x86_64'
Add onnxruntime nvidia providers (#13756)
2024-09-16 04:30:30 +03:00
protobuf==3.20.3; platform_machine == 'x86_64'
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