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feat: Update CC-3DT++.
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‎README.md‎

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<!-- pypi-strip -->
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<picture>
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<!-- /pypi-strip -->
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<img alt="vis4d" src="https://dl.cv.ethz.ch/vis4d/vis4d_logo.svg" width="400">
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<img alt="vis4d" src="docs/source/_static/vis4d_logo.svg" width="400">
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<!-- pypi-strip -->
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</picture>
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<!-- /pypi-strip -->

‎scripts/eval_nusc/README.md‎

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# nuScenes 3D Detection and Tracking Evaluation
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This folder contains the code and python environment to run nuScenes 3D detection and tracking evaluation locally.
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### Installation
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- Python: 3.6
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```bash
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pip install -r nusc.txt
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```
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### Run
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- $WORK_DIR is your output folder which contains the prediction json file.
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- $VERSION is `mini` or `trainval` to select mini or validation split.
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```bash
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bash eval_nusc.sh $WORK_DIR $VERSION
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```

‎scripts/eval_nusc/eval_nusc.py‎

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"""nuScenes evaluation pipeline for Vis4D."""
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import argparse
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import os
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import json
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from nuscenes import NuScenes
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from nuscenes.eval.detection.evaluate import NuScenesEval
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from nuscenes.eval.detection.config import config_factory
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from nuscenes.eval.tracking.evaluate import TrackingEval as track_eval
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from nuscenes.eval.tracking.utils import print_final_metrics
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from nuscenes.eval.tracking.data_classes import TrackingConfig, TrackingMetrics
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from nuscenes.eval.common.config import config_factory as track_configs
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def parse_arguments() -> argparse.Namespace:
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"""Parse arguments."""
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parser = argparse.ArgumentParser(description="Vis4D for nuScenes eval.")
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parser.add_argument(
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"--input",
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"-i",
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help=("Path to save nuScenes format dection / tracking results."),
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)
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parser.add_argument(
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"--version",
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"-v",
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choices=["v1.0-trainval", "v1.0-test", "v1.0-mini"],
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help="NuScenes dataset version to convert.",
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)
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parser.add_argument(
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"--dataroot",
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"-d",
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help="NuScenes dataset root.",
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)
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parser.add_argument(
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"-m",
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"--mode",
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default="tracking",
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choices=["tracking", "detection"],
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help="Conversion mode: detection or tracking.",
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)
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return parser.parse_args()
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def eval_detection(
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version: str,
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dataroot: str,
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output_dir: str,
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result_path: str,
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eval_set: str,
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) -> None:
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"""Evaluate detection results."""
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nusc = NuScenes(version=version, dataroot=dataroot, verbose=True)
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nusc_eval = NuScenesEval(
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nusc,
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config=config_factory("detection_cvpr_2019"),
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result_path=result_path,
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eval_set=eval_set,
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output_dir=output_dir,
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verbose=True,
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)
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_ = nusc_eval.main(render_curves=False)
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def eval_tracking(
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version: str, output_dir: str, result_path: str, root: str, eval_set: str
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) -> None:
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"""Evaluate tracking results."""
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nusc_eval = track_eval(
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config=track_configs("tracking_nips_2019"),
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result_path=result_path,
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eval_set=eval_set,
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output_dir=output_dir,
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verbose=True,
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nusc_version=version,
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nusc_dataroot=root,
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)
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_ = nusc_eval.main()
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def evaluate(
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version: str,
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dataroot: str,
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mode: str,
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output_dir: str,
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result_path: str,
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root: str,
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) -> None:
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"""nuScenes evaluation."""
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if "mini" in version:
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eval_set = "mini_val"
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else:
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eval_set = "val"
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if mode == "tracking":
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eval_tracking(version, output_dir, result_path, root, eval_set)
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else:
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eval_detection(version, dataroot, output_dir, result_path, eval_set)
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def print_metric_summary(metric_summary_path: str) -> None:
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"""Print metric summary."""
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with open(metric_summary_path, "r") as f:
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metrics = json.load(f)
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cfg = TrackingConfig.deserialize(metrics["cfg"])
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tm = TrackingMetrics(cfg=cfg)
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tm.add_runtime(metrics["eval_time"])
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tm.label_metrics = metrics["label_metrics"]
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print_final_metrics(metrics)
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if __name__ == "__main__":
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"""Main."""
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args = parse_arguments()
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if args.mode == "detection":
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metric = "detect_3d"
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else:
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metric = "track_3d"
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evaluate(
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args.version,
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args.dataroot,
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args.mode,
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args.input,
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os.path.join(args.input, f"{metric}_predictions.json"),
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args.dataroot,
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)

‎scripts/eval_nusc/eval_nusc.sh‎

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#!/usr/bin/env bash
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work_dir=$1
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version=$2
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# 3D Detection Evaluation
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python eval_nusc.py \
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--input $work_dir/detect_3d \
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--version v1.0-${version} \
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--dataroot data/nuscenes \
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--mode detection
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# 3D Tracking Evaluation
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python eval_nusc.py \
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--input $work_dir/track_3d \
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--version v1.0-${version} \
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--dataroot=data/nuscenes \
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--mode tracking

‎scripts/eval_nusc/nusc.txt‎

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argon2-cffi==21.3.0
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argon2-cffi-bindings==21.2.0
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async-generator==1.10
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attrs==22.2.0
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backcall==0.2.0
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bleach==4.1.0
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cachetools==4.2.4
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certifi==2021.5.30
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cffi==1.15.1
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comm==0.1.4
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cycler==0.11.0
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dataclasses==0.8
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decorator==5.1.1
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defusedxml==0.7.1
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descartes==1.1.0
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entrypoints==0.4
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fire==0.5.0
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importlib-metadata==4.8.3
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importlib-resources==5.4.0
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ipykernel==5.5.6
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ipython==7.16.3
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ipython-genutils==0.2.0
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ipywidgets==7.8.1
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jedi==0.17.2
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Jinja2==3.0.3
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joblib==1.1.1
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jsonschema==3.2.0
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jupyter==1.0.0
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jupyter-client==7.1.2
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jupyter-console==6.4.3
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jupyter-core==4.9.2
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jupyterlab-pygments==0.1.2
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jupyterlab-widgets==1.1.7
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kiwisolver==1.3.1
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MarkupSafe==2.0.1
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matplotlib==3.3.4
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mistune==0.8.4
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motmetrics==1.1.3
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nbclient==0.5.9
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nbconvert==6.0.7
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nbformat==5.1.3
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nest-asyncio==1.5.8
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notebook==6.4.10
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numpy==1.19.5
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nuscenes-devkit==1.1.10
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opencv-python==4.5.4.58
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packaging==21.3
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pandas==1.1.5
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pandocfilters==1.5.0
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parso==0.7.1
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pexpect==4.9.0
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pickleshare==0.7.5
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Pillow==8.4.0
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prometheus-client==0.17.1
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prompt-toolkit==3.0.36
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ptyprocess==0.7.0
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pycocotools==2.0.7
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pycparser==2.21
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Pygments==2.14.0
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pyparsing==3.1.1
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pyquaternion==0.9.9
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pyrsistent==0.18.0
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python-dateutil==2.8.2
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pytz==2023.3.post1
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pyzmq==25.1.2
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qtconsole==5.2.2
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QtPy==2.0.1
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scikit-learn==0.24.2
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scipy==1.5.4
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Send2Trash==1.8.2
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Shapely==1.8.5
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six==1.16.0
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termcolor==1.1.0
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terminado==0.12.1
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testpath==0.6.0
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threadpoolctl==3.1.0
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tornado==6.1
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tqdm==4.64.1
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traitlets==4.3.3
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typing_extensions==4.1.1
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wcwidth==0.2.13
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webencodings==0.5.1
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widgetsnbextension==3.6.6
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zipp==3.6.0

‎vis4d/engine/flag.py‎

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from .parser import DEFINE_config_file
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# TODO: Currently this does not allow to load multpile config files.
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# Would be nice to extend functionality to chain multiple config files using
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# e.g. --config=model_1.py --config=loader_args.py
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# or --config=my_config.py --config.train_dl=different_dl.py
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# TODO: Support resume from folder and load config directly from it.
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_CONFIG = DEFINE_config_file("config", method_name="get_config")
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_GPUS = flags.DEFINE_integer("gpus", default=0, help="Number of GPUs")
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_CKPT = flags.DEFINE_string("ckpt", default=None, help="Checkpoint path")
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_RESUME = flags.DEFINE_bool("resume", default=False, help="Resume training")
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_SHOW_CONFIG = flags.DEFINE_bool(
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"print-config", default=False, help="If set, prints the configuration."
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)
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_SWEEP = DEFINE_config_file("sweep", method_name="get_sweep")
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_SLURM = flags.DEFINE_bool(
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"slurm", default=False, help="If set, setup slurm running jobs."
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)
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_VIS = flags.DEFINE_bool(
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"vis",
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default=False,
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"_CKPT",
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"_RESUME",
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"_SHOW_CONFIG",
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"_SWEEP",
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"_SLURM",
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"_VIS",
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]

‎vis4d/engine/run.py‎

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if not vis and isinstance(callback, VisualizerCallback):
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rank_zero_info(
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f"{callback.visualizer} is not used."
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f"{callback.visualizer} is not used. "
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"Please set --vis=True to use it."
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)
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continue

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