| |
| |
| """Build the PandaSet sample of bevformer-p150 from the public-data workflow's redistributable PandaSet sample |
| (``research/bevformer/public_data/shippable/pandaset_019_f30-40``; CC BY 4.0 + PandaSet Dataset Terms). |
| |
| It does NOT ship yet: the user has not approved PandaSet-derived samples (PLAN.md 6.3, research/DATASETS.md N5), so |
| the default destination is the git-ignored ``staging_samples_pandaset/`` of the bundle checkout (``--dest code`` |
| writes into ``code/tt_bevformer`` once it may ship; ``staging_samples_pandaset/README.md`` has the swap-in steps). |
| |
| Writes ``<dest>/samples/pandaset_019/`` (the 18 unchanged JPEGs, LICENSE.txt, SHA256SUMS), |
| ``<dest>/samples/pandaset_019_f{30,35,40}.json`` (one request manifest per frame: the six images, the frame's |
| calibration inline -- each camera's camera -> LIDAR_TOP transform at its own timestamp and the 1920x1080 K --, the |
| stream with the ego pose, and the CAN dynamics in the training layout) and the static calibration preset |
| ``<dest>/calib/pandaset_019.json`` (frame 30's transforms). Workspace tool: needs the research data. |
| |
| python3 code/scripts/make_samples.py [--src <shippable dir>] [--dest staging|code] |
| """ |
| from __future__ import annotations |
|
|
| import argparse |
| import hashlib |
| import json |
| import shutil |
| from pathlib import Path |
|
|
| HERE = Path(__file__).resolve().parent |
| PKG = HERE.parent / "tt_bevformer" |
| DEFAULT_SRC = Path("/home/ubuntu/experiments/tt-models/research/bevformer/public_data/shippable/pandaset_019_f30-40") |
| CAMS = ["CAM_FRONT", "CAM_FRONT_RIGHT", "CAM_FRONT_LEFT", "CAM_BACK", "CAM_BACK_LEFT", "CAM_BACK_RIGHT"] |
| ATTRIBUTION = ("Contains data from PandaSet (Scale AI and Hesai), https://pandaset.org, licensed under CC BY 4.0 and the " |
| "PandaSet Dataset Terms (pandaset_019/LICENSE.txt). Changes: JPEG files renamed to the network camera " |
| "slots (bytes unchanged); calibration and ego motion converted to the BEVFormer input contract " |
| "(research/bevformer/public_data README section 2). Scale AI and Hesai do not endorse this work. Cite: " |
| "P. Xiao et al., PandaSet: Advanced Sensor Suite Dataset for Autonomous Driving, ITSC 2021.") |
|
|
|
|
| def sha256(path: Path) -> str: |
| return hashlib.sha256(path.read_bytes()).hexdigest() |
|
|
|
|
| def main() -> int: |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--src", type=Path, default=DEFAULT_SRC) |
| ap.add_argument("--dest", choices=["staging", "code"], default="staging") |
| a = ap.parse_args() |
| global PKG |
| if a.dest == "staging": |
| PKG = HERE.parents[1] / "staging_samples_pandaset" |
| meta = json.loads((a.src / "sample.json").read_text()) |
| if meta["camera_order"] != CAMS: |
| raise SystemExit(f"unexpected camera order {meta['camera_order']}") |
| dst = PKG / "samples" / "pandaset_019" |
| (dst / "images").mkdir(parents=True, exist_ok=True) |
| shutil.copyfile(a.src / "LICENSE.txt", dst / "LICENSE.txt") |
| sums = [] |
| for fr in meta["frames"]: |
| f = int(fr["pandaset_frame"]) |
| for cam in CAMS: |
| src = a.src / fr["images"][cam]["file"] |
| if sha256(src) != fr["images"][cam]["sha256"]: |
| raise SystemExit(f"{src}: sha256 differs from sample.json") |
| out = dst / "images" / f"f{f}_{cam}.jpg" |
| shutil.copyfile(src, out) |
| sums.append(f"{sha256(out)} images/{out.name}") |
| sums.append(f"{sha256(dst / 'LICENSE.txt')} LICENSE.txt") |
| (dst / "SHA256SUMS").write_text("\n".join(sums) + "\n") |
|
|
| for i, fr in enumerate(meta["frames"]): |
| f = int(fr["pandaset_frame"]) |
| cb = fr["can_bus_abs"] |
| cams = {cam: {"intrinsics": fr["K_1920x1080"][k], "T_ref_from_camera": fr["T_lidar_cam"][k]} |
| for k, cam in enumerate(CAMS)} |
| manifest = { |
| "_doc": (f"BEVFormer sample request: PandaSet sequence 019 frame {f} (6 cameras, 1920x1080 JPEG, unmodified " |
| "bytes; the node resizes them to 1600x900 and this port rescales K). model(**tt_bevformer." |
| "load_sample(path)) once the API runs; the calibration is the frame's own (each camera's camera -> " |
| "LIDAR_TOP transform at its camera timestamp: the node's per-camera ego-motion compensation), the " |
| "stream carries the ego pose and the 'ego' block the CAN dynamics in BEVFormer's training layout " |
| "(derived from the poses and the GPS, research/bevformer/public_data README section 2). Frames 30, " |
| "35, 40 form one sequence 0.5 s apart, history reset at frame 30. " + ATTRIBUTION), |
| "frame": f, |
| "images": {cam: f"pandaset_019/images/f{f}_{cam}.jpg" for cam in CAMS}, |
| "calibration": {"frame_id": "LIDAR_TOP", "image_size": [1920, 1080], "scale_intrinsics": True, |
| "cameras": cams}, |
| "stream": {"id": "pandaset_019", "reset": i == 0, "timestamp_s": fr["lidar_timestamp_s"], |
| "T_world_from_ego": fr["ego2global"]}, |
| "ego": {"accel": cb[7:10], "rotation_rate": cb[10:13], "velocity": cb[13:16]}, |
| "camera_stamps_s": fr["camera_timestamps_s"], |
| "image_bgr_sha256_1600x900": fr["image_bgr_sha256_1600x900"], |
| } |
| (PKG / "samples" / f"pandaset_019_f{f}.json").write_text(json.dumps(manifest, indent=1) + "\n") |
|
|
| f0 = meta["frames"][0] |
| preset = { |
| "_doc": ("Calibration preset of the PandaSet sequence 019 sample: per camera the intrinsics of the " |
| "1920x1080 image AS SENT (rescaled to the node's 1600x900, scale_intrinsics=true) and " |
| "T_ref_from_camera = camera optical frame -> the network's virtual nuScenes LIDAR_TOP (frame_id " |
| "LIDAR_TOP; PandaSet pose axes x right / y forward, 1.84 m above the road), taken at frame 30 (static " |
| "rig approximation: the per-frame manifests carry each frame's time-compensated transforms). " |
| + ATTRIBUTION), |
| "frame_id": "LIDAR_TOP", |
| "image_size": [1920, 1080], |
| "scale_intrinsics": True, |
| "cameras": {cam: {"intrinsics": f0["K_1920x1080"][k], "T_ref_from_camera": f0["T_lidar_cam"][k]} |
| for k, cam in enumerate(CAMS)}, |
| } |
| (PKG / "calib").mkdir(exist_ok=True) |
| (PKG / "calib" / "pandaset_019.json").write_text(json.dumps(preset, indent=1) + "\n") |
| print(f"wrote {dst} ({len(sums)} files), 3 manifests, calib/pandaset_019.json") |
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| raise SystemExit(main()) |
|
|
