mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-12-23 19:11:14 +01:00
35 lines
967 B
Bash
35 lines
967 B
Bash
|
#!/bin/bash
|
||
|
|
||
|
set -euxo pipefail
|
||
|
|
||
|
CUDA_HOME=/usr/local/cuda
|
||
|
LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
|
||
|
OUTPUT_FOLDER=/tensorrt_models
|
||
|
echo "Generating the following TRT Models: ${YOLO_MODELS:="yolov4-tiny-288,yolov4-tiny-416,yolov7-tiny-416"}"
|
||
|
|
||
|
# Create output folder
|
||
|
mkdir -p ${OUTPUT_FOLDER}
|
||
|
|
||
|
# Install packages
|
||
|
pip install --upgrade pip && pip install onnx==1.9.0 protobuf==3.20.3
|
||
|
|
||
|
# Clone tensorrt_demos repo
|
||
|
git clone --depth 1 https://github.com/yeahme49/tensorrt_demos.git /tensorrt_demos
|
||
|
|
||
|
# Build libyolo
|
||
|
cd /tensorrt_demos/plugins && make all
|
||
|
cp libyolo_layer.so ${OUTPUT_FOLDER}/libyolo_layer.so
|
||
|
|
||
|
# Download yolo weights
|
||
|
cd /tensorrt_demos/yolo && ./download_yolo.sh
|
||
|
|
||
|
# Build trt engine
|
||
|
cd /tensorrt_demos/yolo
|
||
|
|
||
|
for model in ${YOLO_MODELS//,/ }
|
||
|
do
|
||
|
python3 yolo_to_onnx.py -m ${model}
|
||
|
python3 onnx_to_tensorrt.py -m ${model}
|
||
|
cp /tensorrt_demos/yolo/${model}.trt ${OUTPUT_FOLDER}/${model}.trt;
|
||
|
done
|