Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

YOLOv7 EfficientNMS - Num Classes #50

Open
levipereira opened this issue Jul 26, 2023 · 0 comments
Open

YOLOv7 EfficientNMS - Num Classes #50

levipereira opened this issue Jul 26, 2023 · 0 comments

Comments

@levipereira
Copy link

levipereira commented Jul 26, 2023

I am currently working on integrating YOLOv7 with DeepStream and Triton Server. I have been using the NvDsInferParseCustomEfficientNMS function from /opt/nvidia/deepstream/deepstream-6.1/sources/libs/nvdsinfer_customparser/nvdsinfer_custombboxparser.cpp in my setup.

Deepstream / Triton Server - YOLOv7

Now, I'm looking to transition to the implementation provided by NVIDIA in the repository https://github.com/NVIDIA-AI-IOT/yolo_deepstream/tree/main/deepstream_yolo/nvdsinfer_custom_impl_Yolo. However, I noticed that the code in this repository has a hardcoded value NUM_CLASSES_YOLO, which is not present in NvDsInferParseCustomEfficientNMS function.

static const int NUM_CLASSES_YOLO = 80;
#define OBJECTLISTSIZE 25200
#define BLOCKSIZE  1024
thrust::device_vector<NvDsInferParseObjectInfo> objects_v(OBJECTLISTSIZE);

extern "C" bool NvDsInferParseCustomYoloV7_cuda( 

As I have multiple YOLOv7 models with primary and secondary inference, I am concerned about having to compile a separate NvDsInferParseCustomYoloV7_cuda for each model.

Could you kindly advise if there is a way to avoid compiling individual NvDsInferParseCustomYoloV7_cuda for each model and instead make it more dynamic or configurable to support multiple models?

Thank you for your assistance and guidance. Any help you can provide will be greatly appreciated.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant