NOTE: The deepstream-app
does not support multiple primary GIEs. You can only use one YOLO model as primary GIE and the other YOLO models as secondary GIEs (infering the primary detected object). To use 2 or more YOLO models as primary GIE, you need to use a custom code.
- Directory tree
- Change the YoloLayer plugin version
- Compile the libs
- Edit the config_infer_primary files
- Edit the deepstream_app_config file
- Test
git clone https://github.com/marcoslucianops/DeepStream-Yolo.git
cd DeepStream-Yolo
NOTE: It is important to keep the YOLO model reference (yolov4_
, yolov5_
, yolor_
, etc) in you cfg
and weights
/wts
filenames to generate the engine correctly.
Edit the yoloPlugins.h
file (line 53), in each GIE nvdsinfer_custom_impl_Yolo
folder.
const char* YOLOLAYER_PLUGIN_VERSION {"1"};
To:
const char* YOLOLAYER_PLUGIN_VERSION {"2"};
NOTE: gie2
: version = 2 / gie3
: version = 3 / gie4
: version = 4.
NOTE: Do it for each GIE folder, replacing the GIE folder name (gie1/nvdsinfer_custom_impl_Yolo
).
-
DeepStream 6.1 on x86 platform
CUDA_VER=11.6 make -C gie1/nvdsinfer_custom_impl_Yolo
-
DeepStream 6.0.1 / 6.0 on x86 platform
CUDA_VER=11.4 make -C gie1/nvdsinfer_custom_impl_Yolo
-
DeepStream 6.1 on Jetson platform
CUDA_VER=11.4 make -C gie1/nvdsinfer_custom_impl_Yolo
-
DeepStream 6.0.1 / 6.0 on Jetson platform
CUDA_VER=10.2 make -C gie1/nvdsinfer_custom_impl_Yolo
NOTE: Edit the files according to the model you will use (YOLOv4, YOLOv5, YOLOR, etc).
NOTE: Do it for each GIE folder.
-
Edit the path of the
cfg
fileExample for gie1
custom-network-config=gie1/yolo.cfg
Example for gie2
custom-network-config=gie2/yolo.cfg
-
Edit the gie-unique-id
Example for gie1
gie-unique-id=1
Example for gie2
gie-unique-id=2
-
Edit the process-mode
Example for primary inference engine
process-mode=1
Example for secondary inference engine (infering the primary detected object)
process-mode=2
NOTE: In the secondary inference, we need to set which gie it will use to operate
Add
operate-on-gie-id=1
To operate on specific class ids
operate-on-class-ids=0;1;2
-
Edit batch-size
Example for primary inference engine
batch-size=1
Example for secondary inference engine (infering the primary detected object)
batch-size=16
NOTE: Add the secondary-gie
key after primary-gie
key.
Example for 1 secondary-gie
(2 inferences):
[secondary-gie0]
enable=1
gpu-id=0
gie-unique-id=2
operate-on-gie-id=1
operate-on-class-ids=0
nvbuf-memory-type=0
config-file=gie2/config_infer_primary.txt
Example for 2 secondary-gie
(3 inferences):
[secondary-gie0]
enable=1
gpu-id=0
gie-unique-id=2
operate-on-gie-id=1
operate-on-class-ids=0
nvbuf-memory-type=0
config-file=gie2/config_infer_primary.txt
[secondary-gie1]
enable=1
gpu-id=0
gie-unique-id=3
operate-on-gie-id=1
operate-on-class-ids=0
nvbuf-memory-type=0
config-file=gie3/config_infer_primary.txt
NOTE: Remember to edit primary-gie
key
[primary-gie]
enable=1
gpu-id=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary.txt
To
[primary-gie]
enable=1
gpu-id=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=gie1/config_infer_primary.txt
deepstream-app -c deepstream_app_config.txt
NOTE: During test process, the engine files will be generated in the DeepStream-Yolo folder. When build process is done, for each GIE, move engine file to its respective folder (gie1
, gie2
, etc).