├── LICENSE ├── README.md ├── annotations ├── .gitattributes ├── modanet2018_instances_train.json └── modanet2018_instances_val.json └── logo └── modanet_logo2.png /LICENSE: -------------------------------------------------------------------------------- 1 | Copyright © 2018 eBay Inc.(https://www.ebayinc.com/) 2 | 3 | Creative Commons Attribution-NonCommercial 4.0 International Public License 4 | 5 | By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial 4.0 International Public License ("Public License"). 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Redistribution and use software in source and binary form, with or without modification, are permitted provided that the following conditions are met: 96 | 97 | Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 98 | Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 99 | Neither the name of the COCO Consortium nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. 100 | THIS SOFTWARE AND ANNOTATIONS ARE PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 101 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | [![License: CC BY-NC 4.0](https://licensebuttons.net/l/by-nc/4.0/80x15.png)](https://creativecommons.org/licenses/by-nc/4.0/) 2 | # ModaNet 3 | ![logo](logo/modanet_logo2.png) 4 | 5 |
Table of Contents

6 | 7 | * [Why we made ModaNet](#why-we-made-modanet) 8 | * [Labels](#labels) 9 | * [Contributing](#contributing) 10 | * [Contact](#contact) 11 | * [Citing ModaNet](#citing-modanet) 12 |

13 | 14 | 15 | **ModaNet** is a street fashion images dataset consisting of annotations related to RGB images. ModaNet provides multiple polygon annotations for each image. This dataset is described in a technical paper with the title [`ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations`](https://arxiv.org/pdf/1807.01394.pdf). 16 | Each polygon is associated with a label from 13 meta fashion categories. The annotations are based on images in the [PaperDoll image set](https://github.com/kyamagu/paperdoll/tree/master/data/chictopia), which has only a few hundred images annotated by the superpixel-based tool. The contribution of ModaNet is to provide new and extra **polygon** annotations for the images. 17 | 18 | Thanks to the [EvalAI team](https://evalAI.cloudcv.org), we have [ModaNet challenge leaderboard](https://evalai.cloudcv.org/web/challenges/challenge-page/151), please submit your best results there. It provides leaderboards for semantic segmentation, instance segmentation, and object detection, all in [COCO-style](http://cocodataset.org). We also provide the per-class IOU score for semantic segmentation task in stdout File. You might need to register an account in EvalAI. 19 | 20 | ## Why we made ModaNet 21 | 22 | ModaNet is intended to serve an educational purpose by providing a benchmark annotation set for emerging computer vision research including **semantic segmentation**, **object detection**, **instance segmentation**, **polygon detection**, and etc. 23 | 24 | ### Access to the annotations git repo 25 | Please first install Git Large File Storage by following the below instructions. You might need to apply this step before you download the sql file from paperdoll repo. 26 | ``` 27 | https://help.github.com/articles/installing-git-large-file-storage/ 28 | ``` 29 | 30 | Then you should git clone the repo along with the annotation files, otherwise the annotation files would not be downloaded directly using `git clone`. 31 | 32 | ``` 33 | git clone git@github.com:eBay/modanet.git 34 | ``` 35 | 36 | Before you start working on the dataset, please verify the annotation files by using `md5sum`. In Mac, this requires you to run the following command: 37 | ``` 38 | md5 modanet2018_instances_train.json 39 | ``` 40 | you should expect to see the following md5 value: 41 | ``` 42 | MD5 (modanet2018_instances_train.json) = 96478657d20e322e9d3282c6d73c0c4c 43 | ``` 44 | If you apply the same command to check the val annotation, you should expect to see: 45 | ``` 46 | MD5 (modanet2018_instances_val.json) = 900b24b7d6c0c48203e6244f45d65499 47 | ``` 48 | 49 | Notice the file size: 50 | ``` 51 | modanet2018_instances_train.json (101MB) 52 | modanet2018_instances_val.json (210KB) 53 | ``` 54 | 55 | ### Labels 56 | Each polygon (bounding box, segmentation mask) annotation is assigned to one of the following labels: 57 | 58 | | Label | Description | Fine-Grained-categories | 59 | | --- | --- | --- | 60 | | 1 | bag | bag | 61 | | 2 | belt | belt | 62 | | 3 | boots | boots | 63 | | 4 | footwear | footwear | 64 | | 5 | outer | coat/jacket/suit/blazers/cardigan/sweater/Jumpsuits/Rompers/vest | 65 | | 6 | dress | dress/t-shirt dress | 66 | | 7 | sunglasses | sunglasses | 67 | | 8 | pants | pants/jeans/leggings | 68 | | 9 | top | top/blouse/t-shirt/shirt | 69 | |10 | shorts | shorts | 70 | |11 | skirt | skirt | 71 | |12 | headwear | headwear | 72 | |13 | scarf & tie | scartf & tie | 73 | 74 | The annotation data format of ModaNet follows the same style as [COCO-dataset](http://cocodataset.org). 75 | 76 | 77 | #### Data format 78 | ``` 79 | { 80 | 'info' : info, 'images' : [image], 'annotations' : [annotation], 'licenses' : [license],'year': year, 'categories': [category], 'type': type 81 | } 82 | 83 | info{ 84 | 'version' : str, 'description' : str, 'contributor' : str, 'date_created' : datetime, 85 | } 86 | 87 | image{ 88 | 'id' : int, 'width' : int, 'height' : int, 'file_name' : str, 'license' : int 89 | } 90 | 91 | license{ 92 | 'id' : int, 'name' : str, 'url' : str, 93 | } 94 | 95 | annotation{ 96 | 'area': int, 97 | 'bbox': [x,y,width,height], 98 | 'segmentation': [polygon], 99 | 'image_id': int, 100 | 'id': int, 101 | 'category_id': int, 102 | 'iscrowd': int 103 | } 104 | category{ 105 | 'supercategory': str, 'id': int, 'name': str, 106 | } 107 | ``` 108 | 109 | #### Submitting results to leaderboard 110 | 111 | You can participate only the Object Detection task by submitting results as follows 112 | 113 | ``` 114 | [{ 115 | 'image_id' : int, 'category_id' : int, 'bbox' : [x,y,width,height], 'score' : float, 116 | }] 117 | ``` 118 | Example 119 | ``` 120 | [{'bbox': [192, 30, 20, 28], 121 | 'category_id': 13, 122 | 'image_id': 100014, 123 | 'score': 0.8}] 124 | ``` 125 | 126 | You can participate only the Instance Segmentation/Semantic Segmentation/Polygon prediction tasks by submitting results as follows 127 | ``` 128 | [{ 129 | 'image_id' : int, 'category_id' : int, 'segmentation' : polygon, 'score' : float, 130 | }] 131 | ``` 132 | 133 | Example 134 | ``` 135 | [{'segmentation': [[210, 136 | 31, 137 | 212, 138 | 35, 139 | 204, 140 | 37, 141 | 204, 142 | 45, 143 | 205, 144 | 54, 145 | 199, 146 | 58, 147 | 194, 148 | 52, 149 | 198, 150 | 42, 151 | 192, 152 | 32, 153 | 194, 154 | 30, 155 | 201, 156 | 33]], 157 | 'category_id': 13, 158 | 'image_id': 100014, 159 | 'score': 0.8 }] 160 | ``` 161 | 162 | You can participate the task of joint detection and segmentation by submitting results as follows 163 | 164 | 165 | ``` 166 | [{ 167 | 'image_id' : int, 'category_id' : int, 'segmentation' : polygon, 'score' : float, 'bbox' : [x,y,width,height] 168 | }] 169 | ``` 170 | Example 171 | ``` 172 | [{'bbox': [192, 30, 20, 28], 173 | 'category_id': 13, 174 | 'image_id': 100014, 175 | 'segmentation': [[210, 176 | 31, 177 | 212, 178 | 35, 179 | 204, 180 | 37, 181 | 204, 182 | 45, 183 | 205, 184 | 54, 185 | 199, 186 | 58, 187 | 194, 188 | 52, 189 | 198, 190 | 42, 191 | 192, 192 | 32, 193 | 194, 194 | 30, 195 | 201, 196 | 33]], 197 | 'score': 0.8}] 198 | ``` 199 | 200 | We acknowledge the contribution of COCOdataset team and all the format would follow the same style as those in the COCOdataset. Check [COCOAPI](https://github.com/cocodataset/cocoapi). 201 | 202 | ## Contributing 203 | You are more than welcome to contribute to this github repo! Either by submitting a bug report, or providing feedback about this dataset. Please open issues for specific tasks or post to the contact Google group below. 204 | 205 | 206 | ## Contact 207 | To discuss the dataset, please contact [Moda-net Google Group](https://groups.google.com/forum/#!forum/moda-net). 208 | 209 | 210 | ## Citing ModaNet 211 | If you use ModaNet, we would appreciate reference to the following paper: 212 | 213 | Shuai Zheng, Fan Yang, M. Hadi Kiapour, Robinson Piramuthu. ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations. ACM Multimedia, 2018. [PDF 5.7MB](https://arxiv.org/pdf/1807.01394.pdf) 214 | 215 | 216 | Biblatex entry: 217 | ``` 218 | @inproceedings{zheng/2018acmmm, 219 | author = {Shuai Zheng and Fan Yang and M. Hadi Kiapour and Robinson Piramuthu}, 220 | title = {ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations}, 221 | booktitle = {ACM Multimedia}, 222 | year = {2018}, 223 | } 224 | ``` 225 | ## License 226 | This annotation data is released under the [Creative Commons Attribution-NonCommercial license 4.0](https://creativecommons.org/licenses/by-nc/4.0/). 227 | 228 | 229 | -------------------------------------------------------------------------------- /annotations/.gitattributes: -------------------------------------------------------------------------------- 1 | modanet2018_instances_train.json filter=lfs diff=lfs merge=lfs -text 2 | modanet2018_instances_val.json filter=lfs diff=lfs merge=lfs -text 3 | -------------------------------------------------------------------------------- /annotations/modanet2018_instances_train.json: -------------------------------------------------------------------------------- 1 | version https://git-lfs.github.com/spec/v1 2 | oid sha256:b8a3fd0dcfa8d6f209a0cef88cedd76decbf593bf47b4246504f681b7fb625af 3 | size 105924292 4 | -------------------------------------------------------------------------------- /annotations/modanet2018_instances_val.json: -------------------------------------------------------------------------------- 1 | version https://git-lfs.github.com/spec/v1 2 | oid sha256:b7d2d3266b0594f3e16831008b58770334e375eb58fda0be141005c5fd4854d2 3 | size 215183 4 | -------------------------------------------------------------------------------- /logo/modanet_logo2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/eBay/modanet/1928a80b2c12d663c68e452d744a6c0b0e608ed1/logo/modanet_logo2.png --------------------------------------------------------------------------------