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Deepstream real-time instance segmentation

Real-time instance segmentation

Youtube link: Real-time instance segmentation

Support model

  • YOLOv5-Seg
  • YOLOv7-Seg

Prerequisites

Getting started

Convert model to engine file

Build custom parser

  • cd nvdsinfer_customparser
  • make

Run

  • bash ./run.sh

Docker

Get cuda version number

  • docker run -v ${PWD}:/app/ -w /app --rm --gpus all -it nvcr.io/nvidia/deepstream:6.0.1-devel bash -c 'nvcc deviceQuery.cpp -o deviceQuery && ./deviceQuery'

  • Modify DGPU_ARCHS in docker compose

  • Example (DGPU_ARCHS=75):

Run

  • build: docker-compose build

  • up: docker-compose up

  • Output video in outputs folder

Benchmark

Test on T4

Model FPS mAPval
0.5:0.95 (Box)
mAPval
0.5:0.95 (Mask)
YOLOv5n 247.97 0.27 0.234
YOLOv5s 183.77 0.372 0.317
YOLOv5m 119.58 0.445 0.373
YOLOv5l 85.80 0.484 0.401
YOLOv5x 54.04 0.502 0.415
YOLOv7-Seg 84.12 0.49 0.406
YOLOv7-Seg-Dev 84.59 0.505 0.414
YOLOv7x-Seg 60.29 0.511 0.421