I looked at the Geometry preview and the COCO depth JSONL for SenseNova-Vision-Corpus-50M before committing disk space. The preview parquet has 300 rows: 192 depth, 108 normal. Each row pairs a photo with a target map plus a prompt and reply. The COCO JSONL is about 32 MB and 77,870 lines of paths to COCO 2017 photos and generated depth maps. The prompt comes in seven wordings, and several warn it shouldn’t look like a segmentation mask.
The paper says another model, MoGe-2, generated or densified those depth and normal targets. Part of the boxes and OCR came out of the Rex-Omni labeling pipeline.
The release is 50 million examples, not 50 million unique images, since one photo can show up in multiple tasks. The archive of generated maps is about 8.7 TB in 406 parts, no photos inside. The JSONLs keep relative paths, so you get the photos from the 40-odd source datasets yourself, and some want an account or approval.
License is CC BY-NC 4.0 on the HF card, plus each source’s own terms.
Has anyone pulled a single folder like coco2017/depth out of the split archive without downloading all 406 parts?
submitted by /u/Swimming_Fly_4321
[link] [comments]
