网络的输入、输出如下:
Performance
Inputs
- name: "data" , shape: [1x3x60x60] - An input image in [1xCxHxW] format. Expected color order is BGR.
Outputs
Output layer names in Inference Engine format:
- name: "angle_y_fc", shape: [1, 1] - Estimated yaw (in degrees).
- name: "angle_p_fc", shape: [1, 1] - Estimated pitch (in degrees).
- name: "angle_r_fc", shape: [1, 1] - Estimated roll (in degrees).
Output layer names in Caffe* format:
- name: "fc_y", shape: [1, 1] - Estimated yaw (in degrees).
- name: "fc_p", shape: [1, 1] - Estimated pitch (in degrees).
- name: "fc_r", shape: [1, 1] - Estimated roll (in degrees).
Each output contains one float value that represents value in Tait-Bryan angles (yaw, pitch or roll).
很显然,网络最终层有3个输出(三个欧拉角),所以代码更改如下:
1 angle_y_fc = next(em_it) # yaw 2 angle_p_fc = next(em_it) # pitch 3 angle_r_fc = next(em_it) # roll
另外三个欧拉角的是有取值范围的
Metric | Value |
---|---|
Supported ranges | YAW [-90,90], PITCH [-70,70], ROLL [-70,70] |
GFlops | 0.105 |
MParams | 1.911 |
Source framework | Caffe* |