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
DIGITS DetectNet (detection)
- 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
- DIGITS - SegNet
- Jetpack 3.3
- TensorRT 4.0
Clone jetson_tensorrt into your catkin_ws/src folder and run catkin_make