This model presents a vehicle attributes classification algorithm for a traffic analysis scenario.
Metric | Value |
---|---|
Car pose | Front facing cars |
Occlusion coverage | <50% |
Min object width | 72 pixels |
Supported colors | White, gray, yellow, red, green, blue, black |
Supported types | Car, bus, truck, van |
GFlops | 0.126 |
MParams | 0.626 |
Source framework | Caffe* |
blue | gray | yellow | green | black | white | red | |
---|---|---|---|---|---|---|---|
**blue** | **79.53** | 4.32 | 0.62 | 6.41 | 6.54 | 2.47 | 0.12 |
**gray** | 2.53 | **78.01** | 0 | 1.36 | 1.18 | 16.74 | 0.18 |
**yellow** | 0 | 13.9 | **54.01** | 11.21 | 0 | 10.7 | 10.16 |
**green** | 3.79 | 1.52 | 1.52 | **83.33** | 6.06 | 3.03 | 0.76 |
**black** | 0.85 | 1.92 | 0 | 0.32 | **96.1** | 0.74 | 0.07 |
**white** | 1.45 | 10.86 | 0.17 | 2.53 | 0.08 | **84.83** | 0.08 |
**red** | 0.89 | 0.3 | 2.18 | 2.18 | 0.3 | 1.88 | **92.27** |
Color average accuracy: 81.15 %
car | van | truck | bus | |
---|---|---|---|---|
**car** | **98.26** | 0.56 | 0.98 | 0.2 |
**van** | 3.72 | **89.16** | 6.15 | 0.97 |
**track** | 1.71 | 2.46 | **94.27** | 1.56 |
**bus** | 7.94 | 3.8 | 19.69 | **68.57** |
Type average accuracy: 87.56 %
input
, shape: [1x3x72x72] - An input image in following format [1xCxHxW], where: - C - number of channels - H - image height - W - image width
Expected color order: BGR.
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