DIGITS ImageNet (classification)
- classify_nodes.launch runs a classifier trained on ILSVRC2012 with the builtin camera and publishes to /rt_debug
| Param |
Type |
Description |
| image_subscribe_topic |
string |
image topic to run classification on |
| model_path |
string |
absolute path to the model file (.prototxt) |
| weights_path |
string |
absolute path to the weights file (.caffemodel) |
| cache_path |
string |
absolute path to the automatically generated tensorcache file |
| classes_path |
string |
newline delimited list of class descriptions starting at id 0 |
| data_type |
int |
TensorRT data type. 32 for kFLOAT, 16 for kHALF, 8 for kINT8 |
| model_image_depth |
int |
model input image depth / number of channels |
| model_image_width |
int |
model input width in pixels |
| model_image_height |
int |
model input height in pixels |
| threshold |
float |
confidence threshold of classifications, between 0.0 and 1.0 |
| mean1, mean2, mean3 |
float |
ImageNet means |
| Action |
Topic |
Type |
| publish |
classifications |
Classifications |
| subscribe |
image_subscribe_topic |
Image |
# Classification
uint32 id
float32 confidence
string desc
# Classifications
ClassifiedRegionOfInterest[] regions
Header header
- detect_nodes.launch runs pedestrian detection on the builtin camera and publishes to /rt_debug
| Param |
Type |
Description |
| image_subscribe_topic |
string |
image topic to run detections on |
| model_path |
string |
absolute path to the model file (.prototxt) |
| weights_path |
string |
absolute path to the weights file (.caffemodel) |
| cache_path |
string |
absolute path to the automatically generated tensorcache file |
| classes_path |
string |
newline delimited list of class descriptions starting at id 0 |
| data_type |
int |
TensorRT data type. 32 for kFLOAT, 16 for kHALF, 8 for kINT8 |
| model_image_depth |
int |
model input image depth / number of channels |
| model_image_width |
int |
model input width in pixels |
| model_image_height |
int |
model input height in pixels |
| model_stride |
int |
model stride size - this determines size of network outputs |
| threshold |
float |
confidence threshold of detections, between 0.0 and 1.0 |
| mean1, mean2, mean3 |
float |
ImageNet means |
| Action |
Topic |
Type |
| publish |
detections |
ClassifiedRegionsOfInterest |
| subscribe |
image_subscribe_topic |
Image |
# ClassifiedRegionOfInterest
int32 x
int32 y
int32 w
int32 h
uint32 id
float32 confidence
string desc
# ClassifiedRegionsOfInterest
ClassifiedRegionOfInterest[] regions
Header header
Clone jetson_tensorrt into your catkin_ws/src folder and run catkin_make