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YOLOv6-Improved

Implementation of YOLOv6 paper:

What's New In This Repository

  • [2024.02.12] Replace BACKBONE to lightweight models: ShuffleNetv2, GHostNet, MobileNetv3
  • [2024.03.11] Update NECK to GolD-Neck
  • [2024.04.09] Improved RepVGGBlock, get ACBlock [3×3][1×3][3×1][1×1]
  • [2024.04.11] Improved Structure, get RepC2f
  • [2024.04.15] Update RepOptimizer to adapt to ACBlock

Benchmark (To Be Updated...)

Model Size mAPval
0.5:0.95
SpeedT4
trt fp16 b1
(fps)
SpeedT4
trt fp16 b32
(fps)
Params
(M)
FLOPs
(G)
YOLOv6-N 640 37.5 779 1187 4.7 11.4
YOLOv6-S 640 45.0 339 484 18.5 45.3
YOLOv6-M 640 50.0 175 226 34.9 85.8
YOLOv6-L 640 52.8 98 116 59.6 150.7
YOLOv6-N6 1280 44.9 228 281 10.4 49.8
YOLOv6-S6 1280 50.3 98 108 41.4 198.0
YOLOv6-M6 1280 55.2 47 55 79.6 379.5
YOLOv6-L6 1280 57.2 26 29 140.4 673.4

About

YOLOv6: a single-stage object detection framework dedicated to industrial applications.

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  • Python 6.7%
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