-
- Training images : 3000
- Validation images: 81
- Testing images : 4481
-
Sample numbers of the training data with 8 classes:
Classes Car Van Truck Walker Sitter Rider Tram Misc. Sample number 11379 1197 428 1816 93 671 208 428
-
-
Mean average precision of each class:
Classes Car Van Truck Walker Sitter Rider Tram Misc. Average Precision 73% 35.9% 56.5% 31.5% 0% 30.5% 33.8% 0.3% -
Performance:
-
-
-
Mean average precision of each class:
Classes Car Van Truck Walker Sitter Rider Tram Misc. Average Precision 63.6% 63% 79% 26.7% 19.1% 40.1% 57.5% 50.2% -
Performance:
-
-
-
Mean average precision of each class:
Classes Car Van Truck Walker Sitter Rider Tram Misc. Average Precision 65.7% 60.9% 65.3% 23.5% 15.0% 60.4% 62.9% 59.1% -
Performance:
-
-
-
Mean average precision of each class:
Classes Car Van Truck Walker Sitter Rider Tram Misc. Average Precision 59.6% 39.3% 29.9% 9.1% 0% 10.6% 23.6% 20.0% -
Performance:
-
-
-
Mean average precision of each class:
Classes Car Van Truck Walker Sitter Rider Tram Misc. Average Precision 80.0% 78.4% 86.3% 57.8% 16.5% 67.3% 75.7% 49.1% -
Performance:
-
-
-
Mean average precision of each class:
Classes Vehicle Person Average Precision 75.1% 45.0% -
Performance:
-
-
Performance Table:
Method Total Vehicle Person Run times Enviroment SSD 24.0% 38.5% 6.6% 0.12s GTX 1080ti YOLOv3 32.7% 39.9% 20.6% 0.2s GTX 1080ti YOLOv4 43.8% 62.2% 28.6% 0.38s GTX 1080ti Scaled VOLOv4 47.6% 63.7% 32.9% 0.34s GTX 1080ti Mask R-CNN 58.0% 75.1% 45.0% 3s TPU (Colab) Faster R-CNN 63.6% 73.9% 47.2% 7s GPU (Colab) -
Speed (ms) of processing 1 images versus accuracy (AP) on KITTI dataset:
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent