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refactor(perception): refactor launch file and add parameter file (autowarefoundation#1336)
* fundamental change Signed-off-by: MasatoSaeki <[email protected]> * style(pre-commit): autofix * change params name Signed-off-by: MasatoSaeki <[email protected]> * remove param Signed-off-by: MasatoSaeki <[email protected]> * integrate model and label path Signed-off-by: MasatoSaeki <[email protected]> * for awsim Signed-off-by: MasatoSaeki <[email protected]> * add comment Signed-off-by: MasatoSaeki <[email protected]> * fix typo Signed-off-by: MasatoSaeki <[email protected]> * change param name Signed-off-by: MasatoSaeki <[email protected]> * chore Signed-off-by: MasatoSaeki <[email protected]> --------- Signed-off-by: MasatoSaeki <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Kenzo Lobos Tsunekawa <[email protected]>
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‎autoware_launch/config/perception/traffic_light_recognition/crosswalk_traffic_light_estimator/crosswalk_traffic_light_estimator.param.yaml

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# Copyright 2023 UCI SORA Lab
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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/**:
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ros__parameters:
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use_last_detect_color: true
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last_detect_color_hold_time: 2.0
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last_colors_hold_time: 1.0

‎autoware_launch/config/perception/traffic_light_recognition/tensorrt_yolox/yolox_traffic_light_detector.param.yaml

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# cspell: ignore semseg
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/**:
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ros__parameters:
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score_threshold: 0.35
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nms_threshold: 0.7
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precision: "fp16" # Operation precision to be used on inference. Valid value is one of: [fp32, fp16, int8].
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calibration_algorithm: "Entropy" # Calibration algorithm to be used for quantization when precision==int8. Valid value is one of: [Entropy, (Legacy | Percentile), MinMax].
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dla_core_id: -1 # If positive ID value is specified, the node assign inference task to the DLA core.
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quantize_first_layer: false # If true, set the operating precision for the first (input) layer to be fp16. This option is valid only when precision==int8.
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quantize_last_layer: false # If true, set the operating precision for the last (output) layer to be fp16. This option is valid only when precision==int8.
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profile_per_layer: false # If true, profiler function will be enabled. Since the profile function may affect execution speed, it is recommended to set this flag true only for development purpose.
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clip_value: 6.0 # If positive value is specified, the value of each layer output will be clipped between [0.0, clip_value]. This option is valid only when precision==int8 and used to manually specify the dynamic range instead of using any calibration.
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preprocess_on_gpu: true # If true, pre-processing is performed on GPU.
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gpu_id: 0 # GPU ID to select CUDA Device
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calibration_image_list_path: "" # Path to a file which contains path to images. Those images will be used for int8 quantization.
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# default params of tensorrt_yolox package, only effective for semseg model
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is_roi_overlap_segment: false
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overlap_roi_score_threshold: 0.3
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is_publish_color_mask: false
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roi_overlay_segment_label:
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UNKNOWN : false
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CAR : false
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TRUCK : false
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BUS : false
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MOTORCYCLE : false
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BICYCLE : false
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PEDESTRIAN : false
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ANIMAL: false

‎autoware_launch/config/perception/traffic_light_arbiter/traffic_light_arbiter.param.yaml renamed to ‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_arbiter/traffic_light_arbiter.param.yaml

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‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_classifier/car_traffic_light_classifier.param.yaml

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/**:
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ros__parameters:
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approximate_sync: false
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precision: fp16
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mean: [123.675, 116.28, 103.53] # It depends on the data on which ML model is trained
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std: [58.395, 57.12, 57.375] # It depends on the data on which ML model is trained
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backlight_threshold: 0.85
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classifier_type: 1
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traffic_light_type: 0

‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_classifier/pedestrian_traffic_light_classifier.param.yaml

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/**:
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ros__parameters:
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approximate_sync: false
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precision: fp16
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mean: [123.675, 116.28, 103.53] # It depends on the data on which ML model is trained
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std: [58.395, 57.12, 57.375] # It depends on the data on which ML model is trained
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backlight_threshold: 0.85
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classifier_type: 1
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traffic_light_type: 1

‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_fine_detector/traffic_light_fine_detector.param.yaml

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/**:
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ros__parameters:
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precision: fp16
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score_thresh: 0.3
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nms_thresh: 0.65
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approximate_sync: false
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gpu_id: 0

‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_map_based_detector/camera6_traffic_light_map_based_detector.param.yaml

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/**:
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ros__parameters:
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max_vibration_pitch: 0.01745329251 # -0.5 ~ 0.5 deg
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max_vibration_yaw: 0.01745329251 # -0.5 ~ 0.5 deg
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max_vibration_height: 0.5 # -0.25 ~ 0.25 m
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max_vibration_width: 0.5 # -0.25 ~ 0.25 m
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max_vibration_depth: 0.5 # -0.25 ~ 0.25 m
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max_detection_range: 200.0
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min_timestamp_offset: -0.3
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max_timestamp_offset: 0.0
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timestamp_sample_len: 0.02
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car_traffic_light_max_angle_range: 40.0
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pedestrian_traffic_light_max_angle_range: 80.0

‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_map_based_detector/camera7_traffic_light_map_based_detector.param.yaml

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/**:
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ros__parameters:
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max_vibration_pitch: 0.01745329251 # -0.5 ~ 0.5 deg
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max_vibration_yaw: 0.01745329251 # -0.5 ~ 0.5 deg
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max_vibration_height: 0.5 # -0.25 ~ 0.25 m
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max_vibration_width: 0.5 # -0.25 ~ 0.25 m
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max_vibration_depth: 0.5 # -0.25 ~ 0.25 m
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max_detection_range: 200.0
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min_timestamp_offset: -0.04
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max_timestamp_offset: 0.0
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timestamp_sample_len: 0.02
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car_traffic_light_max_angle_range: 40.0
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pedestrian_traffic_light_max_angle_range: 80.0

‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_map_based_detector/traffic_light_traffic_light_map_based_detector.param.yaml

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/**:
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ros__parameters:
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max_vibration_pitch: 0.01745329251 # -0.5 ~ 0.5 deg
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max_vibration_yaw: 0.01745329251 # -0.5 ~ 0.5 deg
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max_vibration_height: 0.5 # -0.25 ~ 0.25 m
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max_vibration_width: 0.5 # -0.25 ~ 0.25 m
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max_vibration_depth: 0.5 # -0.25 ~ 0.25 m
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max_detection_range: 200.0
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min_timestamp_offset: -0.3
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max_timestamp_offset: 0.0
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timestamp_sample_len: 0.02
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car_traffic_light_max_angle_range: 40.0
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pedestrian_traffic_light_max_angle_range: 80.0

‎autoware_launch/config/perception/traffic_light_multi_camera_fusion/traffic_light_multi_camera_fusion.param.yaml renamed to ‎autoware_launch/config/perception/traffic_light_recognition/traffic_light_multi_camera_fusion/traffic_light_multi_camera_fusion.param.yaml

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