| --- |
| pretty_name: Ego-Exo4D develop (1-3 min takes, moving-object masks, metric depth) |
| task_categories: |
| - depth-estimation |
| - image-segmentation |
| tags: |
| - egocentric |
| - ego-exo4d |
| - aria |
| - metric-depth |
| - moving-object-segmentation |
| --- |
| |
| # Ego-Exo4D develop |
|
|
| The 1,659 Ego-Exo4D v2 takes of 60-180 s that have Aria RGB, both Aria SLAM videos and MPS calibration (44.1 h), |
| with the raw files needed to compute depth, moving-object masks for all of them, and per-frame metric depth for |
| 615 of them. Code that produced the masks and the depth, and runs on this folder as it is: |
| https://github.com/XuweiyiChen/vlm_3d_tracking_annotator/tree/egoexo4d_depth/egoexo4d_depth |
| |
| ## Layout |
| |
| ``` |
| takes.json Ego-Exo4D v2 take metadata (all takes of the release) |
| takes/<take>/frame_aligned_videos/ |
| <aria>_214-1.mp4 Aria RGB, 30 fps, 1408x1408 fisheye (stored turned 90 degrees) |
| <aria>_1201-1.mp4, <aria>_1201-2.mp4 Aria SLAM left / right |
| cam01.mp4 ... exo GoPro videos (only 100 of the takes) |
| takes/<take>/trajectory/ |
| closed_loop_trajectory.csv MPS device poses |
| online_calibration.jsonl MPS online calibration |
| semidense_points.csv.gz, semidense_observations.csv.gz MPS semi-dense point cloud and its observations |
| gopro_calibs.csv exo GoPro calibration |
| captures/<capture>/timesync.csv capture timesync (frame-aligned video frame -> device timestamps) |
| gmos_masks/<take>/ moving-object masks, all 1,659 takes |
| depth_mpsr/<take>.npz metric depth, 615 takes |
| ``` |
| |
| The raw files keep the official Ego-Exo4D v2 layout and names (https://ego-exo4d-data.org). |
|
|
| ## Moving-object masks (`gmos_masks/<take>/`) |
| |
| GMOS run on the whole take at 10 fps, one id per object for the whole take. |
| |
| - `instances.npz`: `instances` uint8 (T, 512, 512), instance id per pixel, 0 = none; `moving` bool (T, max id + 1), |
| GMOS's per-frame motion judgement of each instance (column 0 unused). |
| - `cameras.npz`: `K` (3x3) of the 512x512 view, `frame_ids` (frame index in the 30 fps frame-aligned videos; mask t |
| is video frame 3t), `image_valid` (512x512, inside the lens circle), `fps`, `source_fps`. |
| - `manifest.json`: take, take_uid, camera, activity, task, frames. |
| |
| The view: every 3rd frame of `<aria>_214-1.mp4`, turned upright and rectified to a 512x512 pinhole (focal 0.8 x the |
| calibrated one, the take's middle online-calibration record). |
|
|
| ## Metric depth (`depth_mpsr/<take>.npz`) |
| |
| Per-frame camera z-depth in metres for every pixel of the same 512x512 view (static scene and moving objects), at |
| 10 fps over the longest run of frames that have MPS poses. Static scene: MoGe-3 corrected per frame to the MPS |
| semi-dense points (plane-preserving 4-parameter fit by RANSAC), FoundationStereo on two Aria camera pairs, multi-frame |
| vote and a 1 cm TSDF. Moving objects (all pixels of the GMOS instances): MoGe-3 times a local FoundationStereo ratio, |
| refined by optimizing AllTracker tracks. |
| |
| - `depth`: float32 (N, 512, 512), metres, 0 = no depth. |
| - `frame_ids`: int64 (N,), frame index in the 30 fps frame-aligned videos (mask index = frame_id // 3). |
| - `K`: 3x3 pinhole intrinsics; `T_world_cam`: float32 (N, 4, 4), camera to MPS world (OpenCV axes, metres); |
| `rgb_valid`: (512, 512), pixels inside the RGB fisheye. |
|
|
| ```python |
| import numpy as np |
| d = np.load("depth_mpsr/cmu_bike01_4.npz") |
| i = 0 |
| depth, K, T = d["depth"][i], d["K"], d["T_world_cam"][i] |
| v, u = np.mgrid[:512, :512] |
| points_cam = np.stack([(u - K[0, 2]) / K[0, 0], (v - K[1, 2]) / K[1, 1], np.ones((512, 512))], -1) * depth[..., None] |
| points_world = points_cam @ T[:3, :3].T + T[:3, 3] |
| masks = np.load("gmos_masks/cmu_bike01_4/instances.npz")["instances"][d["frame_ids"][i] // 3] |
| ``` |
|
|
| ## Recomputing |
|
|
| With the code above: `python run.py --data <this folder> --out <output> --take <take>`. To reuse the masks, copy |
| `gmos_masks/<take>/instances.npz` and `cameras.npz` into `<output>/<take>/masks/` and create `<output>/<take>/masks.done`. |
|
|
