| --- |
| license: other |
| task_categories: |
| - image-to-image |
| tags: |
| - novel-view-synthesis |
| - autonomous-driving |
| - lidar |
| - multi-view |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # MHDCSM/cv_ds_all |
|
|
| WebDataset-format shards of the autonomous driving novel-view-synthesis dataset. |
|
|
| Splits: |
| - `train-*.tar` — training samples (includes ground-truth target images) |
| - `test-*.tar` — test samples (no targets) |
|
|
| Each tar holds many samples. Per-sample files share a key (the `sample_id`): |
|
|
| | Suffix | Content | |
| |--------|---------| |
| | `meta.json` | camera poses, intrinsics, timestamps, target camera name | |
| | `t0.<cam>.jpg`, `t1.<cam>.jpg` | 6 camera views per timestamp | |
| | `lidar.npz` | dense world-frame point cloud (xyz, intensity) | |
| | `target.<cam>.jpg` | ground-truth target image (train only) | |
|
|
| ## Streaming usage |
|
|
| ```python |
| import webdataset as wds |
| url = "https://huggingface.co/datasets/MHDCSM/cv_ds_all/resolve/main/train-{000000..NNNNNN}.tar" |
| ds = wds.WebDataset(url).decode() |
| for sample in ds: |
| meta = sample["meta.json"] |
| img = sample["t0.front.jpg"] |
| ``` |
|
|
