example.env

# Parameters for the yolov8 ROS 2 package. Copy this file to `yolov8.env` and edit.
# After editing, REBUILD with `make build` so the new env file lands in install/yolov8/share/yolov8/.
#
# Build-time options (TENSORRT_DIR, CUDA arch, OpenCV version) are NOT read from this file —
# they are passed to `make` / exported in your shell. See README.md sections "Installation" and
# "Building" for details.

# Process niceness for the inference node (0 = highest priority, 19 = lowest).
NICE_LEVEL=11

# ONNX model filename relative to install/yolov8/share/yolov8/models/.
ONNX_MODEL="batch4-542_731.onnx"

# Comma-separated list of camera topics. Must contain exactly BATCH_SIZE entries.
# The node subscribes to <topic><CAMERA_TOPIC_SUFFIX>.
CAMERA_TOPICS="/vimba_front,/vimba_left,/vimba_right,/vimba_rear"
CAMERA_TOPIC_SUFFIX="/image"

# TensorRT engine batch size. Must match the ONNX model's batch dimension AND the number of
# entries in CAMERA_TOPICS above.
BATCH_SIZE=4

# Comma-separated class names matching the model's class ids in order.
# Must contain at least as many entries as the model's number of classes.
CLASS_NAMES="car"

# Maximum rate (Hz) at which buffered camera frames are flushed to the network
# if not all topics produced a frame in the current window.
CAMERA_BUFFER_HZ=30

# Visualization toggles.
VISUALIZE_MASKS=true
ENABLE_ONE_CHANNEL_MASK=true
VISUALIZE_ONE_CHANNEL_MASK=true

# Inference precision: FP32, FP16, or INT8.
PRECISION=FP16
# Required only when PRECISION=INT8.
CALIBRATION_DATA_DIRECTORY=""

# Detection / segmentation thresholds.
PROBABILITY_THRESHOLD=0.25
NMS_THRESHOLD=0.65
TOP_K=100

# Segmentation prototype mask dimensions (must match the ONNX model's output1 shape).
SEG_CHANNELS=32
SEG_H=160
SEG_W=160
SEGMENTATION_THRESHOLD=0.5