Run Isaac ROS Foundationpose on custom dataset with ground truth segmentations
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- docker
- Domain
- computer-vision, robotics
Research direction
Start with the isaac_ros_foundationpose.launch.py entry point and the documented input topics: pose_estimation/image, pose_estimation/depth_image, pose_estimation/segmentation, and pose_estimation/camera_info. Reproduce the launch using the listed TensorRT engines and static-image scripts, then trace whether the node receives synchronized inputs; the issue is done when it produces pose output or reports a clear input/configuration error.
Written by the indexing model from the issue text.
Description
Hello! I've been trying to run Foundationpose for Isaac following the tutorial for Isaac 3.1 on a custom dataset, using the Isaac Docker image with tag aarch64-ros2_humble on a Jetson with Jetpack 6.2. I was able to run the examples using the rosbag successfully after converting the score, refine models to TensorRT engines but I am having trouble running the node for my dataset. More specifically, I am running the commands below (they are all executed in the same docker container spawned with ${ISAAC_ROS_WS}/src/isaac_ros_common/scripts/run_dev.sh) :
- Run realsense camera:
ros2 launch realsense2_camera rs_launch.py rgb_camera.profile:=640x480x30 depth_module.profile:=640x480x30 - Run foundationpose ros node:
ros2 launch isaac_ros_foundationpose isaac_ros_foundationpose.launch.py refine_engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationpose/refine_trt_engine.plan score_engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationpose/score_trt_engine.plan mesh_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/IndustryShapes/textured_models/obj_000001/obj_000001.obj texture_path:=${ISAAC_ROS_WS}/isaac_ros_assets/IndustryShapes/textured_models/obj_000001/texture.png launch_rviz:=true - Run a script to remap camera_info topic
/camera/color/camera_infoto/pose_estimation/camera_info. - Run a script to stream static images to the topics that foundationpose subscribes to, according to the documentation. More specifically I publish the RGB to
pose_estimation/image, the depth image topose_estimation/depth_image, and the ground truth mask topose_estimation/segmentation(so I am not currently using DETR or any other detector/segmentation model).
Also the origin frame of the 3D mesh of my object is at the center of the mesh, as instructed. And I can see that the rgb, depth, segmentation topics are published correctly, as their visualizations on rviz are what I expect. However, I am not getting any pose (or error for that matter), on rviz or in any of the output topics (/output, pose_estimation/pose_matrix_output). Could anyone please indicate what I could be missing?
- Dominant language
- C++
- Stars
- 517
- Forks
- 57
- PR merge metrics
- No merged PRs in 30d
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
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First steps
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- Open a pull request that references the issue number.
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License clarification — vendored nvdiffrast sources in isaac_ros_pose_estimation (Apache-2.0)May be free again @yuanknv claimed this 47 days ago, and no pull request is open. Openverify to close
NVIDIA-ISAAC-ROS/isaac_ros_pose_estimation#98 · 2 comments · 2 assignees ·
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Not getting the same result as offline foundationposeMay be free again @yuanknv claimed this 174 days ago, and no pull request is open. Opencoming soon!
NVIDIA-ISAAC-ROS/isaac_ros_pose_estimation#95 · 8 comments · 1 assignee ·
All issues in NVIDIA-ISAAC-ROS/isaac_ros_pose_estimation
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