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| − | + | A collection of different datasets. Some of these were made by members of Game Upscale, whereas others are premade from other sources. | |
| + | |||
| + | |||
| + | =Datasets= | ||
| + | |||
| + | ==Realistic== | ||
| + | {| class="wikitable sortable" | ||
| + | |- | ||
| + | ! Dataset Name | ||
| + | ! Author | ||
| + | ! Cost | ||
| + | ! License | ||
| + | ! Image Amount - Size | ||
| + | ! Description | ||
| + | ! Samples | ||
| + | ! Date Posted | ||
| + | |||
| + | |- | ||
| + | | [http://data.vision.ee.ethz.ch/cvl/DIV2K/DIV2K_train_HR.zip DIV2K] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 0.8K | ||
| + | | 800 HQ real-world images | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://mega.nz/file/SL5jwYSR#nkVWxRMazz1QO72338ZEl1Ts0BLJjtYFxr9Ne-jmf7A Nomos2k] | ||
| + | | musl | ||
| + | | Free | ||
| + | | | ||
| + | | 2536 | ||
| + | | Raw images were processed on rawtherapee using prebayer deconvolution, AMaZe and AP1 color space. Sources: Adobe-MIT-5k, RAISE, FFHQ, DIV2K, DIV8k, Flickr2k, Rawsamples, SignatureEdits, Hasselblad raw samples and Unsplash. KernelGAN was trained using DLIP on all images, with scale 4x and up to 5k iter, instead of 3k. Hopefully it increases the accuracy of kernels. All files are provided on "kernelgan" folder. Note: in order to use it on traiNNer, you have to give dataroot_kernels path, along with enabling realistic under the resizing presets. I encourage everyone to give it a try and, if possible, mirror the dataset. For now it was made available on MEGA, but I plan to mirror it on other solutions. I've also made available my selected noise patches. They were extracted from multiple images "in the wild", with unknown degradation: | ||
| + | [https://mega.nz/file/WSZjjYRI#jgJYQTxJQyJjW5cbDJdUte0szfOpyeiDRrWmMzIkxZ0 Noise Patches] | ||
| + | | [https://cdn.discordapp.com/attachments/579685650824036387/904201202546380820/nomos2k.mp4 Video Sample] | ||
| + | | 2021-10-30 | ||
| + | |||
| + | |||
| + | |- | ||
| + | | [https://drive.google.com/drive/folders/1hnpOBK_olECyXitS7mRpGwn7PWzKuVP4?usp=sharing ESRGAN_GroundTextures (Ground)] | ||
| + | | tldr_coder#6919 | ||
| + | | Free | ||
| + | | Unknown | ||
| + | | 760 (training ready set) and ~150 for the non-processed set. - 873mb Compressed | ||
| + | | Photos taken outdoors, some google searching for high quality images too, most under public licenses as far as I know... Outdoor ground textures. Focus on grass, dirt and rocks. These are the training and validation images used to train the GroundTextures model. I don't have all the original images anymore though. | ||
| + | | | ||
| + | | 2022-1-27 | ||
| + | |||
| + | |- | ||
| + | | [https://data.csail.mit.edu/graphics/fivek/ MIT-Adobe FiveK (MIT5k)] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 5k | ||
| + | | We collected 5,000 photographs taken with SLR cameras by a set of different photographers. They are all in RAW format; that is, all the information recorded by the camera sensor is preserved. We made sure that these photographs cover a broad range of scenes, subjects, and lighting conditions. We then hired five photography students in an art school to adjust the tone of the photos. Each of them retouched all the 5,000 photos using a software dedicated to photo adjustment (Adobe Lightroom) on which they were extensively trained. We asked the retouchers to achieve visually pleasing renditions, akin to a postcard. The retouchers were compensated for their work. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://mega.nz/file/RI1XySbb#rq8oOhZ8k4rohW8jgQRc-CpB0JnPiXbuTHx_nrMpgW0 Zalando RAW HQ Cloth Images] | ||
| + | | wyk | ||
| + | | Free | ||
| + | | | ||
| + | | 76K (there are some duplicates, but they have the same names, so it is simple to remove them) | ||
| + | | Contains cloth like images. It could be used to train stylegan, for example. | ||
| + | | | ||
| + | | 2021-11-04 | ||
| + | |||
| + | |||
| + | |- | ||
| + | | [https://mega.nz/file/KGxSlKqB#zhPLlqlUKkdQdt5yUkZ5HZYcHxjNRmeKPbuWX7CVbL4 Mountains] | ||
| + | | Joey | ||
| + | | Free | ||
| + | | | ||
| + | | 648 (sourced via random places on the internet) | ||
| + | | Originally compiled this for attempting to upscale the infamous mountain image :mountains:. Unfortunately, that didn't end up working. However, it might be useful for realistic SR as well. It took me quite a while to compile all of these, so hopefully it helps someone. | ||
| + | | | ||
| + | | 2021-11-05 | ||
| + | |||
| + | |- | ||
| + | | [https://mega.nz/file/FUszmQiS#PjYQLLVvrywmfROfFG6qcoRkcgUUiZkjdSMMUWelP-g ASOS mix images] | ||
| + | | wyk | ||
| + | | Free | ||
| + | | | ||
| + | | 20,992 (webp, 7.6 GB) | ||
| + | | Could be good to train stylegan or fabric resolution enhancements models | ||
| + | | | ||
| + | | 2021-11-06 | ||
| + | |||
| + | |||
| + | REDS dataset is released under [https://creativecommons.org/licenses/by/4.0/ CC BY 4.0] license | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://yingqianwang.github.io/Flickr1024/ Flickr1024] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 2.048k | ||
| + | | Flickr1024 is a large stereo dataset, which consists of 1024 high-quality images pairs and covers diverse scenarios. This dataset can be employed for stereo image super-resolution (SR). | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://cv.snu.ac.kr/research/EDSR/Flickr2K.tar Flickr2K] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | ? | ||
| + | | Huge dataset that is being used to train a lot of models. | ||
| + | | | ||
| + | | | ||
| + | |} | ||
| + | |||
| + | ==Video Games== | ||
| + | |||
| + | {| class="wikitable sortable" | ||
| + | |- | ||
| + | ! Dataset Name | ||
| + | ! Author | ||
| + | ! Cost | ||
| + | ! License | ||
| + | ! Image Amount - Size | ||
| + | ! Description | ||
| + | ! Samples | ||
| + | ! Date Posted | ||
| + | |||
| + | |- | ||
| + | | [https://drive.google.com/drive/folders/1x3nYsgqRJ9S41metj9Vc7J5UaNVPjECB?usp=sharing Kim2091's 8k Video Game Dataset] | ||
| + | | [[User:Kim2091|Kim2091]] | ||
| + | | Free with Limitations | ||
| + | | Just credit the dataset if used, and do not reupload unless permission is granted | ||
| + | | 1663 8k frames | ||
| + | | Games captured: Battlefield 1, Fallout 4, GRIP, Just Cause 3, Need for Speed Most Wanted 2012, Remember Me, Tomb Raider 2013, and Wolfenstein: The New Order | ||
| + | |||
| + | GTA V is already captured and will be added later | ||
| + | | [https://cdn.discordapp.com/attachments/903415274521374750/996574179111477248/075-nfsmw3.png Sample 1] | ||
| + | | 2022-07-28 | ||
| + | |||
| + | |- | ||
| + | | [http://www.mohamedaly.info/datasets/caltech-games Caltech Game Covers] [https://web.archive.org/web/20100718155155/https://www.vision.caltech.edu/malaa/datasets/caltech-games/caltech-games.zip Mirror] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 11.4K | ||
| + | | Found a dataset of game covers, but there's a ton of duplicates. If I can figure out how to parse the text files and remove the dupes, I'll upload the trimmed down version. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://quixel.com/megascans/library Quixel Megascans] | ||
| + | | Quixel | ||
| + | | Limited Free | ||
| + | | | ||
| + | | 9.89K | ||
| + | | Discover a world of unbounded creativity. Explore a massive asset library, and Quixel’s powerful tools, plus free in-depth tutorials and resources. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://drive.google.com/file/d/1XLSYFJQ34NliwQn2CA9bJXa7rjYhXy19/view?usp=sharing WorldTex] | ||
| + | | JosephtheKP#3750 | ||
| + | | Free | ||
| + | | N/A (I do not own any of the images provided) | ||
| + | | 200 Images - 4.83GB | ||
| + | | video game env textures. this is a dataset i compiled rather quickly that i have no use for now, all the images are very high quality and almost entirely blur free | ||
| + | | | ||
| + | | 2021-12-26 | ||
| + | |} | ||
| + | |||
| + | ==Video== | ||
| + | {| class="wikitable sortable" | ||
| + | |- | ||
| + | ! Dataset Name | ||
| + | ! Author | ||
| + | ! Cost | ||
| + | ! License | ||
| + | ! Image Amount - Size | ||
| + | ! Description | ||
| + | ! Samples | ||
| + | ! Date Posted | ||
| + | |||
| + | |- | ||
| + | | [http://toflow.csail.mit.edu/ Vimeo-90k] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 89.8k | ||
| + | | This dataset consists of 89,800 video clips downloaded from vimeo.com, which covers large variety of scenes and actions. It is designed for the following four video processing tasks: temporal frame interpolation, video denoising, video deblocking, and video super-resolution. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://seungjunnah.github.io/Datasets/reds.html REDS Dataset] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | ? | ||
| + | | This is the Realistic and Dynamic Scenes dataset for video deblurring and super-resolution. Train and validation subsets are publicly available. Downloads are available via Google Drive and SNU CVLab server. | ||
| + | |||
| + | REDS dataset is released under [https://creativecommons.org/licenses/by/4.0/ CC BY 4.0] license | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://mega.nz/file/tZhVzCTT#DtE42x2NYSYerrcj79CE2sS-yhWHn-iq-wKAUY_HnoY VHS Part 1] [https://mega.nz/file/Vw8zzIhS#J4y9_hqQ2b0spZratZU-RqIqfxXoQHBhtzSxbKnRAo4 VHS Part 2] [https://mega.nz/file/Fkx3CS5L#21BxaUFt9c7f6Nu-ASFcsm1dc01Gdu3R8yjKA3GffMU LRx3] | ||
| + | | Redswag Scalliwag#4629 | ||
| + | | Free | ||
| + | | N/A (I do not own any of the images provided) | ||
| + | | 3128 4k movie frames, 3128(x3) VHS frames - 37.3GB total | ||
| + | | Sharpening and denoising VHS footage. Used for my VHS Sharpen 1x model, hopefully someone can find this useful or make an even better model than mine. | ||
| + | | https://cdn.discordapp.com/attachments/905446120333930566/937602167852892220/example.png | ||
| + | | 2022-1-31 | ||
| + | |} | ||
| + | |||
| + | ==Books== | ||
| + | {| class="wikitable sortable" | ||
| + | |- | ||
| + | ! Dataset Name | ||
| + | ! Author | ||
| + | ! Cost | ||
| + | ! License | ||
| + | ! Image Amount - Size | ||
| + | ! Description | ||
| + | ! Samples | ||
| + | ! Date Posted | ||
| + | |||
| + | |- | ||
| + | | [https://www.reddit.com/r/DHExchange/comments/ay0w3c/s_highres_scans_of_gustave_dor%C3%A9s_1866_bible/ Gustave Doré's 1866 Bible Illustrations] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 0.241K | ||
| + | | High-Res Scans of Gustave Doré's 1866 Bible Illustrations | ||
| + | | | ||
| + | | | ||
| + | |} | ||
| + | |||
| + | ==Drawn Content and Anime== | ||
| + | {| class="wikitable sortable" | ||
| + | |- | ||
| + | ! Dataset Name | ||
| + | ! Author | ||
| + | ! Cost | ||
| + | ! License | ||
| + | ! Image Amount - Size | ||
| + | ! Description | ||
| + | ! Samples | ||
| + | ! Date Posted | ||
| + | |||
| + | |- | ||
| + | | [https://www.gwern.net/Danbooru2018 Danbooru2018] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 3330K | ||
| + | | Danbooru2018 is a large-scale anime image database with 3.33m+ images annotated with 99.7m+ tags; it can be useful for machine learning purposes such as image recognition and generation. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://github.com/bloc97/SYNLA-Dataset SYNLA] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | ~2k | ||
| + | | This dataset is designed to simulate complex line art. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://drive.google.com/open?id=1f25paYZvzULHsBRIjrqcVWTjiekupZQP falcoon300] | ||
| + | | LyonHrt and falcoon | ||
| + | | Free | ||
| + | | | ||
| + | | 1.233K | ||
| + | | LyonHrt: As it has been mentioned, here is the almost complete works of falcoon, as used in the falcoon300 model, this has a selection of 1233 images from original source, I should add there are some scantly clad woman, so nsfw lol. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |} | ||
| + | |||
| + | |||
| + | |||
| + | ==Various== | ||
| + | {| class="wikitable sortable" | ||
| + | |- | ||
| + | ! Dataset Name | ||
| + | ! Author | ||
| + | ! Cost | ||
| + | ! License | ||
| + | ! Image Amount - Size | ||
| + | ! Description | ||
| + | ! Samples | ||
| + | ! Date Posted | ||
| + | |||
| + | |- | ||
| + | | [https://stock.adobe.com/ Adobe Stock] | ||
| + | | Adobe | ||
| + | | $29.99+/Month | ||
| + | | | ||
| + | | "Millions" | ||
| + | | Stock photos, royalty-free images, graphics, vectors & videos | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://www.pexels.com/ Pexels] | ||
| + | | Pexels/Various | ||
| + | | Free | ||
| + | | | ||
| + | | Unknown | ||
| + | | Free stock photos you can use everywhere. ✓ Free for commercial use ✓ No attribution required | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://www.poliigon.com/ Poliigon] | ||
| + | | | ||
| + | | $16+/Month | ||
| + | | | ||
| + | | 3.069K | ||
| + | | | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://www.textures.com/ Textures.com] | ||
| + | | | ||
| + | | Limited Free | ||
| + | | | ||
| + | | 134.872K | ||
| + | | Textures for 3D, Graphic Design and Photoshop 15 Free downloads every day! | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [https://texturehaven.com/ texturehaven] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 0.133K | ||
| + | | 100% Free High Quality Textures for Everyone | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [http://texturelib.com/ texturelib] | ||
| + | | | ||
| + | | Limited Free | ||
| + | | | ||
| + | | 6.605K | ||
| + | | Library of quality high resolution textures. Free for personal and commercial use. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [http://toflow.csail.mit.edu/ Vimeo-90k] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 89.8k | ||
| + | | This dataset consists of 89,800 video clips downloaded from vimeo.com, which covers large variety of scenes and actions. It is designed for the following four video processing tasks: temporal frame interpolation, video denoising, video deblocking, and video super-resolution. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [http://toflow.csail.mit.edu/ Triplet (for temporal frame interpolation)] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 73.171K | ||
| + | | The triplet dataset consists of 73,171 3-frame sequences with a fixed resolution of 448 x 256, extracted from 15K selected video clips from [http://toflow.csail.mit.edu/ Vimeo-90k]. This dataset is designed for temporal frame interpolation. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |- | ||
| + | | [http://toflow.csail.mit.edu/ Septuplets] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 91.701K | ||
| + | | The septuplet dataset consists of 91,701 7-frame sequences with fixed resolution 448 x 256, extracted from 39K selected video clips from [http://toflow.csail.mit.edu/ Vimeo-90k]. This dataset is designed to video denoising, deblocking, and super-resolution. | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |||
| + | |- | ||
| + | | [https://drive.google.com/drive/folders/16PIViLkv4WsXk4fV1gDHvEtQxdMq6nfY outdoor scene training] | ||
| + | | | ||
| + | | Free | ||
| + | | | ||
| + | | 8.137K | ||
| + | | outdoor scene training is huge, just the first file has 2,187 pictures (8,137 total) | ||
| + | | | ||
| + | | | ||
| + | |||
| + | |} | ||
| + | |||
| + | |||
| + | ==Other sources lists== | ||
| + | If you have some time consider adding them to this list here. | ||
| + | [http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm] | ||
| + | [https://caffe2.ai/docs/datasets.html https://caffe2.ai/docs/datasets.html] | ||
| + | [https://pastebin.com/vU7P8Vmi https://pastebin.com/vU7P8Vmi] | ||
Latest revision as of 00:02, 2 October 2022
A collection of different datasets. Some of these were made by members of Game Upscale, whereas others are premade from other sources.
Contents
Datasets
Realistic
| Dataset Name | Author | Cost | License | Image Amount - Size | Description | Samples | Date Posted | ||
|---|---|---|---|---|---|---|---|---|---|
| DIV2K | Free | 0.8K | 800 HQ real-world images | ||||||
| Nomos2k | musl | Free | 2536 | Raw images were processed on rawtherapee using prebayer deconvolution, AMaZe and AP1 color space. Sources: Adobe-MIT-5k, RAISE, FFHQ, DIV2K, DIV8k, Flickr2k, Rawsamples, SignatureEdits, Hasselblad raw samples and Unsplash. KernelGAN was trained using DLIP on all images, with scale 4x and up to 5k iter, instead of 3k. Hopefully it increases the accuracy of kernels. All files are provided on "kernelgan" folder. Note: in order to use it on traiNNer, you have to give dataroot_kernels path, along with enabling realistic under the resizing presets. I encourage everyone to give it a try and, if possible, mirror the dataset. For now it was made available on MEGA, but I plan to mirror it on other solutions. I've also made available my selected noise patches. They were extracted from multiple images "in the wild", with unknown degradation: | Video Sample | 2021-10-30
| |||
| ESRGAN_GroundTextures (Ground) | tldr_coder#6919 | Free | Unknown | 760 (training ready set) and ~150 for the non-processed set. - 873mb Compressed | Photos taken outdoors, some google searching for high quality images too, most under public licenses as far as I know... Outdoor ground textures. Focus on grass, dirt and rocks. These are the training and validation images used to train the GroundTextures model. I don't have all the original images anymore though. | 2022-1-27 | |||
| MIT-Adobe FiveK (MIT5k) | Free | 5k | We collected 5,000 photographs taken with SLR cameras by a set of different photographers. They are all in RAW format; that is, all the information recorded by the camera sensor is preserved. We made sure that these photographs cover a broad range of scenes, subjects, and lighting conditions. We then hired five photography students in an art school to adjust the tone of the photos. Each of them retouched all the 5,000 photos using a software dedicated to photo adjustment (Adobe Lightroom) on which they were extensively trained. We asked the retouchers to achieve visually pleasing renditions, akin to a postcard. The retouchers were compensated for their work. | ||||||
| Zalando RAW HQ Cloth Images | wyk | Free | 76K (there are some duplicates, but they have the same names, so it is simple to remove them) | Contains cloth like images. It could be used to train stylegan, for example. | 2021-11-04
| ||||
| Mountains | Joey | Free | 648 (sourced via random places on the internet) | Originally compiled this for attempting to upscale the infamous mountain image :mountains:. Unfortunately, that didn't end up working. However, it might be useful for realistic SR as well. It took me quite a while to compile all of these, so hopefully it helps someone. | 2021-11-05 | ||||
| ASOS mix images | wyk | Free | 20,992 (webp, 7.6 GB) | Could be good to train stylegan or fabric resolution enhancements models | 2021-11-06
|
||||
| Flickr1024 | Free | 2.048k | Flickr1024 is a large stereo dataset, which consists of 1024 high-quality images pairs and covers diverse scenarios. This dataset can be employed for stereo image super-resolution (SR). | ||||||
| Flickr2K | Free | ? | Huge dataset that is being used to train a lot of models. |
Video Games
| Dataset Name | Author | Cost | License | Image Amount - Size | Description | Samples | Date Posted |
|---|---|---|---|---|---|---|---|
| Kim2091's 8k Video Game Dataset | Kim2091 | Free with Limitations | Just credit the dataset if used, and do not reupload unless permission is granted | 1663 8k frames | Games captured: Battlefield 1, Fallout 4, GRIP, Just Cause 3, Need for Speed Most Wanted 2012, Remember Me, Tomb Raider 2013, and Wolfenstein: The New Order
GTA V is already captured and will be added later |
Sample 1 | 2022-07-28 |
| Caltech Game Covers Mirror | Free | 11.4K | Found a dataset of game covers, but there's a ton of duplicates. If I can figure out how to parse the text files and remove the dupes, I'll upload the trimmed down version. | ||||
| Quixel Megascans | Quixel | Limited Free | 9.89K | Discover a world of unbounded creativity. Explore a massive asset library, and Quixel’s powerful tools, plus free in-depth tutorials and resources. | |||
| WorldTex | JosephtheKP#3750 | Free | N/A (I do not own any of the images provided) | 200 Images - 4.83GB | video game env textures. this is a dataset i compiled rather quickly that i have no use for now, all the images are very high quality and almost entirely blur free | 2021-12-26 |
Video
| Dataset Name | Author | Cost | License | Image Amount - Size | Description | Samples | Date Posted |
|---|---|---|---|---|---|---|---|
| Vimeo-90k | Free | 89.8k | This dataset consists of 89,800 video clips downloaded from vimeo.com, which covers large variety of scenes and actions. It is designed for the following four video processing tasks: temporal frame interpolation, video denoising, video deblocking, and video super-resolution. | ||||
| REDS Dataset | Free | ? | This is the Realistic and Dynamic Scenes dataset for video deblurring and super-resolution. Train and validation subsets are publicly available. Downloads are available via Google Drive and SNU CVLab server.
REDS dataset is released under CC BY 4.0 license |
||||
| VHS Part 1 VHS Part 2 LRx3 | Redswag Scalliwag#4629 | Free | N/A (I do not own any of the images provided) | 3128 4k movie frames, 3128(x3) VHS frames - 37.3GB total | Sharpening and denoising VHS footage. Used for my VHS Sharpen 1x model, hopefully someone can find this useful or make an even better model than mine. | https://cdn.discordapp.com/attachments/905446120333930566/937602167852892220/example.png | 2022-1-31 |
Books
| Dataset Name | Author | Cost | License | Image Amount - Size | Description | Samples | Date Posted |
|---|---|---|---|---|---|---|---|
| Gustave Doré's 1866 Bible Illustrations | Free | 0.241K | High-Res Scans of Gustave Doré's 1866 Bible Illustrations |
Drawn Content and Anime
| Dataset Name | Author | Cost | License | Image Amount - Size | Description | Samples | Date Posted |
|---|---|---|---|---|---|---|---|
| Danbooru2018 | Free | 3330K | Danbooru2018 is a large-scale anime image database with 3.33m+ images annotated with 99.7m+ tags; it can be useful for machine learning purposes such as image recognition and generation. | ||||
| SYNLA | Free | ~2k | This dataset is designed to simulate complex line art. | ||||
| falcoon300 | LyonHrt and falcoon | Free | 1.233K | LyonHrt: As it has been mentioned, here is the almost complete works of falcoon, as used in the falcoon300 model, this has a selection of 1233 images from original source, I should add there are some scantly clad woman, so nsfw lol. |
Various
| Dataset Name | Author | Cost | License | Image Amount - Size | Description | Samples | Date Posted |
|---|---|---|---|---|---|---|---|
| Adobe Stock | Adobe | $29.99+/Month | "Millions" | Stock photos, royalty-free images, graphics, vectors & videos | |||
| Pexels | Pexels/Various | Free | Unknown | Free stock photos you can use everywhere. ✓ Free for commercial use ✓ No attribution required | |||
| Poliigon | $16+/Month | 3.069K | |||||
| Textures.com | Limited Free | 134.872K | Textures for 3D, Graphic Design and Photoshop 15 Free downloads every day! | ||||
| texturehaven | Free | 0.133K | 100% Free High Quality Textures for Everyone | ||||
| texturelib | Limited Free | 6.605K | Library of quality high resolution textures. Free for personal and commercial use. | ||||
| Vimeo-90k | Free | 89.8k | This dataset consists of 89,800 video clips downloaded from vimeo.com, which covers large variety of scenes and actions. It is designed for the following four video processing tasks: temporal frame interpolation, video denoising, video deblocking, and video super-resolution. | ||||
| Triplet (for temporal frame interpolation) | Free | 73.171K | The triplet dataset consists of 73,171 3-frame sequences with a fixed resolution of 448 x 256, extracted from 15K selected video clips from Vimeo-90k. This dataset is designed for temporal frame interpolation. | ||||
| Septuplets | Free | 91.701K | The septuplet dataset consists of 91,701 7-frame sequences with fixed resolution 448 x 256, extracted from 39K selected video clips from Vimeo-90k. This dataset is designed to video denoising, deblocking, and super-resolution. |
| |||
| outdoor scene training | Free | 8.137K | outdoor scene training is huge, just the first file has 2,187 pictures (8,137 total) |
Other sources lists
If you have some time consider adding them to this list here. http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm https://caffe2.ai/docs/datasets.html https://pastebin.com/vU7P8Vmi