SketchyCOCO dataset

This repository hosts the ShetchyCOCO dataset. Please refer to our CVPR paper for more information: "SketchyCOCO: Image Generation from Freehand Scene Sketches".

SketchyCOCO dataset can be explored by https://sysu-imsl.com/EdgeGAN/dataset.html or https://sysu-imsl.github.io/EdgeGAN/dataset.html.

Overview

• Dataset
• Dataset Augmentation
• Captions of the file structure in the dataset
• Google Drive Hosting
• Baidu Netdisk Hosting
• Optional
• Licensing

Dataset

SketchyCOCO dataset consists of two part:

• Object-level data
  • Object-level data contains $20198(train18869+val1329)$ triplets of {foreground sketch, foreground image, foreground edge map} examples covering 14 classes, $27683(train22171+val5512)$ pairs of {background sketch, background image} examples covering 3 classes.
• Scene-level data
  • Scene-level data contains $14081(train 11265 + val 2816)$ pairs of {foreground image&background sketch, scene image} examples, $14081(train 11265 + val 2816)$ pairs of {scene sketch, scene image} examples and the segmentation ground truth for $14081(train 11265 + val 2816)$ scene sketches. Some val scene images come from the train images of the COCO-Stuff dataset for increasing the number of the val images of the SketchyCOCO dataset.

Dataset Augmentaion

We increase 4662 images for 9 objects, their correspondence edge maps and sketches. The details of dataset augmentation is shown below. And the augmentation has been merged into Object-level data.

cat	dog	zebra	giraffe	horse	cow	elephant	sheep	Car
659	777	401	246	773	628	398	369	411

Captions of the file structure in the dataset

• data
  • Scene - Scene-level data
    • GT - Ground Truth
      • trainInTrain - Train images of SketchyCOCO dataset from the train images of the COCO-Stuff dataset
      • valInTrain - Val images of SketchyCOCO dataset from the train images of the COCO-Stuff dataset
      • val - Val images of SketchyCOCO dataset from the val images of the COCO-Stuff dataset
    • Sketch - Sketch scene of GT (a sketch scene has the same name with the corresponding GT)
    • Annotation - Annotations for sketch scene segmentation
  • Object - Object-level data
    • GT - Ground Truth
    • Sketch - Sketch image of the GT (a edge image has the same name with the corresponding GT)
    • Edge - Edge image of the GT (a edge image has the same name with the corresponding GT)
  • Others - Intermediate products when building the dataset
    • background - Background images and sketches
    • background_training - Images of {foreground image&background sketch} data
    • foreground - Foreground images and sketches used in the scene
    • intermediate product - Images of {generated image&background sketch} data
    • sketches_background - Sketches for building the background sketches
  • Image Source - Files storing the source of images
• matlab_code - Codes for building the dataset

Google Drive Hosting

• Object-level data
• Scene-level data
• Others
• Image Source

Baidu Netdisk Hosting

• Object-level data Password:nv6n
• Scene-level data A Password:7k48
• Scene-level data B Password:l43w
• Scene-level data C Password:3umq
• Others Password:4hy0
• Image Source Password:vrem

PS: Merge trainInTrain_part of Scene-level data B and data C into GT/trainInTrain of Scene-level data A after downloading.

Optional

• You can build a new dataset using the following instructions:

  1. Install COCO API for Matlab.

  2. Download images and annotations of the COCO-Stuff dataset.

  3. Run ./matlab_code/constructDataset.m after changing the parameters in the code.

• The XDoG image can be obtained by running ./matlab_code/XDoG.m after changing the parameters in the code.

• The pairs of the objects can be obtained by running ./matlab_code/preprocess_combine.m after changing the parameters in the code.

• The pairs of the scenes can be obtained by running ./matlab_code/combineScript.m after changing the parameters in the code.

Licensing

SketchyCOCO is a derivative work of [the Sketchy Database](http://sketchy.eye.gatech.edu/), [the COCO-Stuff Dataset](https://github.com/nightrome/cocostuff), [TU Berlin](http://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/), [Car Dataset](http://ai.stanford.edu/~jkrause/cars/car_dataset.html), [cats_vs_dogs](https://tensorflow.google.cn/datasets/catalog/cats_vs_dogs?hl=zh-cn) and [Pascal voc 2012](http://host.robots.ox.ac.uk/pascal/VOC/). The authors of the COCO-Stuff database, the Sketchy Database, TU Berlin, Car Dataset, cats_vs_dogs and Pascal voc 2012 do not in any form endorse this work. Different licenses apply:

• Images: Flicker Terms of use
• Sketches: Creative Commons Attribution 4.0 License
• SketchyCOCO code: Creative Commons Attribution 4.0 License