“This is the 18th day of my participation in the First Challenge 2022. For details: First Challenge 2022”

  • πŸŽ‰ statement: as one of the bloggers in AI field, ❀️ lives up to your time and your ❀️

    • ❀️ column: AI field data resource collation ❀️ [Effectively reject fake data]

    πŸ‘‹ Follow me πŸ‘‹, Get more fun AI, charge πŸš€ πŸš€

    πŸ“• DIV2K

    DIV2K: The dataset has 1000 hd images (2K resolution), of which 800 are for training, 100 are for verification and 100 are for testing.

    • The following figure
    • For regular SR training, we will need to download X2, X3, X4, X8 and the original train and Validation data

    Data distribution:

    Download link:

    • data.vision.ee.ethz.ch/cvl/DIV2K/

    Updated 2022-1-22

    Recently, I bought a service and built a small cloud disk, which can be used to share a small amount of data with your friends

    At present, it is limited to, DIV2K data set, friends who have difficulty downloading from the official website, can add friends of the blogger to ask for it

    • 🍊 Computer vision, superpartition reconstruction, master/doctor communication, correct opening mode

    πŸ“— Flickr2K datasets

    Flickr2K:

    • HR: 2650 PNG images, including people, animals and landscapes
    • Flickr2K_LR_bicubic: X2, X3, X4, currently X8 is missing

    Download link:

    • CV. Snu. Ac. Kr/research/ED…
    • Copying the link to the browser will start the download directly, and the data size is 20GB;
    • Is this sharing very practical?

    πŸ“— Flickr2K Cloud disk download way

    If Flickr2K datasets, http://cv.snu.ac.kr/research/EDSR/Flickr2K.tar, a friend to download very slow

    You can search for the same name of this blog public number, public number background, reply 20201212 to get exclusive cloud disk download link

    20201212
Copy the code
    • When I unpacked 20G, I found a folder with 4 G Flickr2K_LR_unknown files that were useless, so I removed it; Collated data subcontracted and shared to the cloud disk;

    πŸš€πŸš€ So far the gold digging platform has created the following classic blog post πŸš€πŸš€

    Computer vision field, classic blog post

    • 🍊 Use AI to convert photos of good friends into pencil sketches — 🍊2020 U2Net🍊

    • 🍊 NiceGAN environment to build, style migration (with source) | 【 2020 】 CVPR

    • 🍊 multi-stage progressive image restoration – go rain, denoising, fuzzy – effective tutorial (with source) | 【 2021 】 CVPR

    • 🍊 Image inpainting Based on Deep Learning – A Review

    • 🍊 graduation thesis, academic paper writing basic skills and experience – one read

    • 🍊 LaTeX2021 formula preparation, graphic installation, detailed tutorial, a read

    AI learning, deep learning environment building: an understanding

    • 🍊 # Ubuntu install CUDa11.2 for current users

    • 🍊 # Linux and Windows setup PIP image source – the most practical machine learning library download acceleration setup

    • 🍊 # Specify the GPU to run and train Python programs, deep learning single card, multi-card training GPU Settings

    • 🍊 # Install Pytorch and Torchvision in Cuda10.0 for Linux

    • 🍊 # Read SSH password login, public key authentication login

    • Install JDK 11: configure the JAVA_HOME environment variable

    πŸš€πŸš€ Mexic AI

  • πŸŽ‰ as one of the bloggers with the most dry goods in the field of AI, ❀️ lives up to his time and qing ❀️
  • ❀️ If the article is helpful to you, like, comment encourage bloggers every minute to seriously create