InShopDataset

• Annotations (Anno/)

  • segmentation/ clothing semgentaion and detection annotations

  • Attribute Annotations (list_attr_cloth.txt & list_attr_items.txt)

    clothing attribute labels. See ATTRIBUTE LABELS section below for more info.

  • Bounding Box Annotations (list_bbox_inshop.txt)

    bounding box labels. See BBOX LABELS section below for more info.

  • Description Annotations (list_description_inshop.json)

    item descriptions. See DESCRIPTION LABELS section below for more info.

  • Item Annotations (list_item_inshop.txt)

    item labels. See ITEM LABELS section below for more info.

  • Fashion Landmark Annotations (list_landmarks_inshop.txt)

    fashion landmark labels. See LANDMARK LABELS section below for more info.

• Images (Img/)

  in-shop clothes images. See IMAGE section below for more info.

• Evaluation Partitions (Eval/list_eval_partition.txt)

  image names for training, validation and testing set respectively. See EVALUATION PARTITIONS section below for more info.

IMAGE

For Fashion Retrieval task, use "img.zip"; for fashion parsing and segmentation task, use "img_highres.zip". *.jpg

format: JPG

Notes: 1. Images are centered and resized to 256*256; 2. The aspect ratios of original images are kept unchanged.

BBOX LABELS

list_bbox_inshop.txt

First Row: number of images
Second Row: entry names
Rest of the Rows: <image name> <clothes type> <pose type> <bbox location>

Notes: 1. The order of bbox labels accords with the order of entry names; 2. In clothes type, "1" represents upper-body clothes, "2" represents lower-body clothes, "3" represents full-body clothes; 3. In pose type, "1" represents frontal view, "2" represents side view, "3" represents back view, "4" represents zoom-out view, "5" represents zoom-in view, "6" represents stand-alone view; 4. In bbox location, "x_1" and "y_1" represent the upper left point coordinate of bounding box, "x_2" and "y_2" represent the lower right point coordinate of bounding box. Bounding box locations are listed in the order of [x_1, y_1, x_2, y_2].

LANDMARK LABELS

list_landmarks_inshop.txt

First Row: number of images
Second Row: entry names
Rest of the Rows: <image name> <clothes type> <variation type> [<landmark visibility 1> <landmark location x_1> <landmark location y_1>, ... <landmark visibility 8> <landmark location x_8> <landmark location y_8>]

Notes: 1. The order of landmark labels accords with the order of entry names; 2. In clothes type, "1" represents upper-body clothes, "2" represents lower-body clothes, "3" represents full-body clothes. Upper-body clothes possess six fahsion landmarks, lower-body clothes possess four fashion landmarks, full-body clothes possess eight fashion landmarks; 3. In variation type, "1" represents normal pose, "2" represents medium pose, "3" represents large pose, "4" represents medium zoom-in, "5" represents large zoom-in; 4. In landmark visibility state, "0" represents visible, "1" represents invisible/occluded, "2" represents truncated/cut-off; 5. For upper-body clothes, landmark annotations are listed in the order of ["left collar", "right collar", "left sleeve", "right sleeve", "left hem", "right hem"]; For lower-body clothes, landmark annotations are listed in the order of ["left waistline", "right waistline", "left hem", "right hem"]; For upper-body clothes, landmark annotations are listed in the order of ["left collar", "right collar", "left sleeve", "right sleeve", "left waistline", "right waistline", "left hem", "right hem"].

ITEM LABELS

list_item_inshop.txt

First Row: number of items

Rest of the Rows:

Notes: 1. Please refer to the paper "DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations" for more details.

DESCRIPTION LABELS

list_description_inshop.json

Each Row:

Notes: 1. Please refer to the paper "DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations" for more details.

ATTRIBUTE LABELS

list_attr_cloth.txt

First Row: number of attributes
Second Row: entry names
Rest of the Rows: <attribute name>

list_attr_items.txt

First Row: number of items
Second Row: entry names
Rest of the Rows: <item id> <attribute labels>

Notes: 1. The order of attribute labels accords with the order of attribute names; 2. In attribute labels, "1" represents positive while "-1" represents negative, '0' represents unknown; 3. Attribute prediction is treated as a multi-label tagging problem.

EVALUATION PARTITIONS

list_eval_partition.txt

First Row: number of images
Second Row: entry names
Rest of the Rows: <image name> <item id> <evaluation status>

Notes: 1. In evaluation status, "train" represents training image, "query" represents query image, "gallery" represents gallery image; 2. Items of clothes images are NOT overlapped within this dataset partition; 3. Please refer to the paper "DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations" for more details.