Mattings Human - Dataset Ninja

Introduction #

Released 2019-04-08 ·AISegment

The authors of the AISegment Mattings Human dataset introduce a compelling application known as human segmentation, which involves the high-resolution extraction of humans from images. Despite its many potential uses, this problem remains significantly under-constrained, prompting active research efforts to develop more sophisticated methods. The dataset is designed to contribute to this research by offering a high-quality collection of images and corresponding masks.

The dataset stands as the largest portrait matting dataset to date, comprising 34,425 images along with their corresponding matting results. Notably, the dataset has been meticulously annotated by Beijing Play Star Convergence Technology Co., Ltd., ensuring high quality. Moreover, a portrait soft segmentation model, trained on this dataset, has been successfully commercialized.

The original images within the dataset are sourced from platforms such as Flickr, Baidu, and Taobao. After undergoing face detection and area cropping, the dataset presents half-length portraits of dimensions 600x800, showcasing a commitment to maintaining quality throughout the data preparation process.

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GitHub

Summary #

AISegment Mattings Human is a dataset for a semantic segmentation task. It is used in the entertainment industry.

The dataset consists of 34425 images with 34425 labeled objects belonging to 1 single class (human).

Images in the Mattings Human dataset have pixel-level semantic segmentation annotations. All images are labeled (i.e. with annotations). There are no pre-defined train/val/test splits in the dataset. Additionally, every image has group and clip tags. The dataset was released in 2019 by the AISegment, China.

Here is the visualized example grid with animated annotations:

Explore #

Mattings Human dataset has 34425 images. Click on one of the examples below or open "Explore" tool anytime you need to view dataset images with annotations. This tool has extended visualization capabilities like zoom, translation, objects table, custom filters and more. Hover the mouse over the images to hide or show annotations.

Sample annotation mask from Mattings Human

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Have a look at 34425 images

View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 1 annotation classes in the dataset. Find the general statistics and balances for every class in the table below. Click any row to preview images that have labels of the selected class. Sort by column to find the most rare or prevalent classes.

Rows 1-1 of 1

Class ㅤ	Images ㅤ	Objects ㅤ	Count on image average	Area on image average
human➔ mask	34425	34425	1	55.47%

Images #

Explore every single image in the dataset with respect to the number of annotations of each class it has. Click a row to preview selected image. Sort by any column to find anomalies and edge cases. Use horizontal scroll if the table has many columns for a large number of classes in the dataset.

Object distribution #

Interactive heatmap chart for every class with object distribution shows how many images are in the dataset with a certain number of objects of a specific class. Users can click cell and see the list of all corresponding images.

Class sizes #

The table below gives various size properties of objects for every class. Click a row to see the image with annotations of the selected class. Sort columns to find classes with the smallest or largest objects or understand the size differences between classes.

Rows 1-1 of 1

Class	Object count	Avg area	Max area	Min area	Min height	Min height	Max height	Max height	Avg height	Avg height	Min width	Min width	Max width	Max width
human mask	34425	55.47%	98.53%	23.9%	411px	51.38%	800px	100%	690px	86.28%	305px	50.83%	600px	100%

Spatial Heatmap #

The heatmaps below give the spatial distributions of all objects for every class. These visualizations provide insights into the most probable and rare object locations on the image. It helps analyze objects' placements in a dataset.

Objects #

Table contains all 34425 objects. Click a row to preview an image with annotations, and use search or pagination to navigate. Sort columns to find outliers in the dataset.

Rows 1-10 of 34425

Object ID ㅤ	Class ㅤ	Image name click row to open	Image size height x width	Height ㅤ	Height ㅤ	Width ㅤ	Width ㅤ	Area ㅤ
1➔	human mask	1803260054-00000525.jpg	800 x 600	582px	72.75%	559px	93.17%	48.03%
2➔	human mask	1803261926-00000317.jpg	800 x 600	636px	79.5%	564px	94%	44.73%
3➔	human mask	1803240710-00000341.jpg	800 x 600	637px	79.62%	600px	100%	53.93%
4➔	human mask	1803241840-00000499.jpg	800 x 600	761px	95.12%	600px	100%	67.42%
5➔	human mask	1803281541-00000083.jpg	800 x 600	567px	70.88%	482px	80.33%	33.54%
6➔	human mask	1803260459-00000566.jpg	800 x 600	544px	68%	538px	89.67%	41.84%
7➔	human mask	1803251003-00000541.jpg	800 x 600	731px	91.38%	595px	99.17%	53.28%
8➔	human mask	1803151818-00008002.jpg	800 x 600	757px	94.62%	600px	100%	70.4%
9➔	human mask	1803241840-00000150.jpg	800 x 600	730px	91.25%	580px	96.67%	58.55%
10➔	human mask	1803260216-00000530.jpg	800 x 600	729px	91.12%	571px	95.17%	54.56%

License #

AISegment Mattings Human is under MIT license.

Source

Citation #

If you make use of the Mattings Human data, please cite the following reference:

@dataset{Mattings Human,
  author={AISegment},
  title={AISegment Mattings Human},
  year={2019},
  url={https://www.kaggle.com/datasets/laurentmih/aisegmentcom-matting-human-datasets}
}

Source

If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:

@misc{ visualization-tools-for-aisegmentcom-human-matting-dataset,
  title = { Visualization Tools for Mattings Human Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/aisegmentcom-human-matting } },
  url = { https://datasetninja.com/aisegmentcom-human-matting },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { sep },
  note = { visited on 2024-09-15 },
}

Download #

Dataset Mattings Human can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='Mattings Human', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

The data in original format can be downloaded here.

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Disclaimer #

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