YCB-Video dataset Download Mirror (YOLO labels & weights)

The YCB-Video dataset contributed by PoseCNN is based on the YCB dataset. 21 objects are selected, and photographed with an RGBD camera to make 92 videos. The entire data set contains 133827 frames.

21 Objects

The YCB-Video dataset is a little hard to download from Google Drive. Because it only consists of a super large compressed file (256GB) and does not support resumable transmission. Once the download fails, you will face an rate limitation (usually 24 hours) and have to download again from the first byte!😭

So I used sub-volume compression, each file is round 10GB in size with a verifiable hash. Although multi-threaded downloading is still not allowed, at least you can re-download from a sub-volume instead of the whole. Furthermore, I added text labels for YOLO training to each image under the data folder.

YOLO labels

YOLO Demos

yolov4
yolov5

The weights file can be downloaded from here https://github.com/nozomi-sk/ycb_demo

Download Links

  1. (Onedrive) https://1drv.ms/u/s!ArXt0Kjjeh3YoA1p-6b1Pyyj4Lsb?e=G0HCdD
  2. (Original Google Drive) https://drive.google.com/file/d/1if4VoEXNx9W3XCn0Y7Fp15B4GpcYbyYi/view

Hash List

  • MD5 (YCB_dataset.7z.001) = 2938959578526c439fcf305039d771ee
  • MD5 (YCB_dataset.7z.002) = 5ff069313a4b1e80d5a4d49a5143520e
  • MD5 (YCB_dataset.7z.003) = d91401bfe17a58d112005b3d7ce54bee
  • MD5 (YCB_dataset.7z.004) = 03d90d90fca58cb718f7166f308d2b73
  • MD5 (YCB_dataset.7z.005) = d7efe9d3ebadc0e349530013cf2bcdbd
  • MD5 (YCB_dataset.7z.006) = a726108c94cedcf13cc7542d15f48094
  • MD5 (YCB_dataset.7z.007) = 172cef59b5aba068a44964999092c48e
  • MD5 (YCB_dataset.7z.008) = 204d10e89150b94303ea9408590bce1a
  • MD5 (YCB_dataset.7z.009) = d563b4bd3b503714084ecf25776220f0
  • MD5 (YCB_dataset.7z.010) = 42221d4aaf8f766ec43d5591cff9eb8e
  • MD5 (YCB_dataset.7z.011) = 127027a358a62f7174365548911d82eb
  • MD5 (YCB_dataset.7z.012) = a9527c328b11596467bf7c824f78fe54
  • MD5 (YCB_dataset.7z.013) = e74735f6fef230cce28e51be269a7db3
  • MD5 (YCB_dataset.7z.014) = fef10290667ed8770f4a69f68cf2d406
  • MD5 (YCB_dataset.7z.015) = 53ea620a14d222e19e18e276acb37f38
  • MD5 (YCB_dataset.7z.016) = c2e70cbc44a9ec83561e4d8568ed133b
  • MD5 (YCB_dataset.7z.017) = 9585027e3a1b4c419597602cbc6a8405
  • MD5 (YCB_dataset.7z.018) = e8a98ef2781e7acf610178db9f087fce
  • MD5 (YCB_dataset.7z.019) = 574864e2957de06da819352a0a84e752
  • MD5 (YCB_dataset.7z.020) = b7702d60e957744cb87529daf077c22a
  • MD5 (YCB_dataset.7z.021) = 2492ec78e8c761531d31040d44ae5a85
  • MD5 (YCB_dataset.7z.022) = 8e059c0bedde4107fdff67395bbcc77a
  • MD5 (YCB_dataset.7z.023) = 30cd6e0ffb69f6aa5a367d361b949399
  • MD5 (YCB_dataset.7z.024) = dfd92b2b0a5b67ef8bdf2352f18f5bf4
  • MD5 (YCB_dataset.7z.025) = c75e34108ecac57e9a1cd711b0a076e1
  • MD5 (YCB_dataset.7z.026) = a05f01f90d5b9380c1686e5d4ae10588
  • MD5 (YCB_dataset.7z.027) = b9a49dd0e5ef545dd414f7269d9a644c
  • MD5 (YCB_dataset.7z.028) = 1312e78288569cf7eb4cd03046e6e48a
  • MD5 (YCB_dataset.7z.029) = 4c21dfd4b7a8d324807b863d1316599b

9 Comments YCB-Video dataset Download Mirror (YOLO labels & weights)

  1. Debapriya Maji

    Thanks a lot for sharing the dataset in a downloadable way.

    One more point

    I think one information that is missing from the page is how to merge the splits. In order to merge the split after completion of download, run this command:

    7z x -tsplit YCB_dataset.7z.001

    Reply
  2. David

    Hi NOZOMI,

    The download link of the sub-volume compression no longer exists. Can you please send me another link please? I will be grateful if you can share it with me.
    Thank you so much in advance,

    Regards.

    Reply
  3. Benjamin

    Dear Dr. NOZOMI,

    I hope you do not mind me getting in touch. I am a master’s student working on a draft for object recognition. The video results you show on youtube are promising. I wonder if you can share the inference Pytorch code of Yolov5 or the weights of your model. I would be grateful if you could share them with us.

    I am looking forward to your positive reply.

    Yours sincerely.

    Reply
  4. Tekkiri

    Hello,

    Can you provide the weights of your models (yolov4 and yolov5) trained on the YCB-Video dataset? Please. Thank you.

    Reply

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