Comments (1)
TrailNet Caffe model was originally trained in Caffe using FP32 precision.
The model is used by our ROS node which uses TensorRT to load and optimize it for fast inference.
The target precision FP16/FP32 is selected based on user-provided parameters, see launch files for more details
from redtail.
Related Issues (20)
- camera image not received for gscam kind camera in trailnet_debug_gscam.launch/trailnet_debug_zed_gscam.launch
- stereoDNN resnet18 test fails HOT 2
- gscam problem with no video shown, even not shown in rqt-image window, not even gst-launch on host machine HOT 1
- tx2 onboard connection with px4 flushed by apm not connected even with mavros HOT 11
- gscam donot stream on nano,but do stream on tx2
- lateral offset dataset
- Failed with error code 1 in /tmp/pip-build-U_9LbZ/numpy/
- Extended Redtail implementation for Arducopter HOT 7
- Training Resnet18_2D
- Error Loading TensorRT plan for ResNet-18_2D HOT 1
- Testing in Simulator
- Takeoff Mode Initiated Mid-air when starting px4_controller node in Navigate Mode HOT 2
- Unable to complete build_redtail_image.sh script HOT 3
- clarification on difference between visionworks and redtail? HOT 1
- Dataset used for training HOT 2
- The segmentation effect in your video HOT 1
- Jetpack 4.4 caffe_ros node Assertion failed HOT 3
- 2.4 GHz range cut due to Jetson RF noise HOT 6
- Could not find a configuration file for package "OpenCV"
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from redtail.