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