Hi,
There's a problem，I use the ssdJacintoNetV2 which is Ti provided Object detect net.
In the identification of traffic signs, one kind of images often make mistakes, resulting in low identification errors.
just show as blow. The left image is belong to the speed limit signs, which I need to recognize in my task, but the right image is very similar to the left，which not in my task. How can I strengthen my training for this situation？The right image is not marked in my sample.
1、Can I use subclass attributes to reinforce the training of the sample?
2、We want to get a good result of vehicle identification at night，For ssdJacintoNetV2 networks, I need to separate night vehicles into another one category or a subcategory，or just in the car category without subdivision？
typedef struct
{
uint32_t objTag;
uint32_t objType;
uint32_t objSubType;
uint32_t xPos;
uint32_t yPos;
uint32_t objWidth;
uint32_t objHeight;
float objScore;
float objScale;
float reserved0;
float reserved1;
float reserved2;
} TI_OD_objectDescriptor;
