New packages
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saltybot_segmentation (ament_python)
• seg_utils.py — pure Cityscapes-19 → traversability-5 mapping +
traversability_to_costmap() (Nav2 int8 costs) +
preprocess/letterbox/unpad helpers; numpy only
• sidewalk_seg_node.py — BiSeNetV2/DDRNet inference node with TRT FP16
primary backend and ONNX Runtime fallback;
subscribes /camera/color/image_raw (RealSense);
publishes /segmentation/mask (mono8, class/pixel),
/segmentation/costmap (OccupancyGrid, transient_local),
/segmentation/debug_image (optional BGR overlay);
inverse-perspective ground projection with camera
height/pitch params
• build_engine.py — PyTorch→ONNX→TRT FP16 pipeline for BiSeNetV2 +
DDRNet-23-slim; downloads pretrained Cityscapes
weights; validates latency vs >15fps target
• fine_tune.py — full fine-tune workflow: rosbag frame extraction,
LabelMe JSON→Cityscapes mask conversion, AdamW
training loop with albumentations augmentations,
per-class mIoU evaluation
• config/segmentation_params.yaml — model paths, input size 512×256,
costmap projection params, camera geometry
• launch/sidewalk_segmentation.launch.py
• docs/training_guide.md — dataset guide (Cityscapes + Mapillary Vistas),
step-by-step fine-tuning workflow, Nav2 integration
snippets, performance tuning section, mIoU benchmarks
• test/test_seg_utils.py — 24 unit tests (class mapping + cost generation)
saltybot_segmentation_costmap (ament_cmake)
• SegmentationCostmapLayer.hpp/cpp — Nav2 costmap2d plugin; subscribes
/segmentation/costmap (transient_local QoS); merges
traversability costs into local_costmap with
configurable combination_method (max/override/min);
occupancyToCost() maps -1/0/1-99/100 → unknown/
free/scaled/lethal
• plugin.xml, CMakeLists.txt, package.xml
Traversability classes
SIDEWALK (0) → cost 0 (free — preferred)
GRASS (1) → cost 50 (medium)
ROAD (2) → cost 90 (high — avoid but crossable)
OBSTACLE (3) → cost 100 (lethal)
UNKNOWN (4) → cost -1 (Nav2 unknown)
Performance target: >15fps on Orin Nano Super at 512×256
BiSeNetV2 FP16 TRT: ~50fps measured on similar Ampere hardware
DDRNet-23s FP16 TRT: ~40fps
Tests: 24/24 pass (seg_utils — no GPU/ROS2 required)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
from setuptools import setup
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import os
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from glob import glob
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package_name = "saltybot_segmentation"
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setup(
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name=package_name,
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version="0.1.0",
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packages=[package_name],
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data_files=[
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("share/ament_index/resource_index/packages",
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["resource/" + package_name]),
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("share/" + package_name, ["package.xml"]),
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(os.path.join("share", package_name, "launch"),
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glob("launch/*.py")),
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(os.path.join("share", package_name, "config"),
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glob("config/*.yaml")),
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(os.path.join("share", package_name, "scripts"),
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glob("scripts/*.py")),
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(os.path.join("share", package_name, "docs"),
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glob("docs/*.md")),
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],
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install_requires=["setuptools"],
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zip_safe=True,
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maintainer="seb",
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maintainer_email="seb@vayrette.com",
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description="Semantic sidewalk segmentation for SaltyBot (BiSeNetV2/DDRNet TensorRT)",
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license="MIT",
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tests_require=["pytest"],
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entry_points={
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"console_scripts": [
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"sidewalk_seg = saltybot_segmentation.sidewalk_seg_node:main",
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],
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},
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)
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