AttrDataset

IMAGE

*.jpg

format: JPG

Notes: 1. The long side of images are resized to 300; 2. The aspect ratios of original images are kept unchanged.

BBOX LABELS

list_bbox.txt

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

Notes: 1. The order of bbox labels accords with the order of entry names; 2. 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_consumer2shop.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"].

CATEGORY LABELS

list_category_cloth.txt

First Row: number of categories
Second Row: entry names
Rest of the Rows: <category name> <category type>

list_category_img.txt

First Row: number of images
Second Row: entry names
Rest of the Rows: <image name> <category label>

Notes: 1. In category type, "1" represents upper-body clothes, "2" represents lower-body clothes, "3" represents full-body clothes; 2. The order of category labels accords with the order of category names; 3. In category labels, the number represents the category id in category names; 4. For the clothing categories, "Cape", "Nightdress", "Shirtdress" and "Sundress" have been merged into "Dress"; 5. Category prediction is treated as a 1-of-K classification problem.

ATTRIBUTE LABELS

list_attr_cloth.txt

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

list_attr_img.txt

First Row: number of images
Second Row: entry names
Rest of the Rows: <image name> <attribute labels>

Notes: 1. In attribute type, "1" represents texture-related attributes, "2" represents fabric-related attributes, "3" represents shape-related attributes, "4" represents part-related attributes, "5" represents style-related attributes; 2. The order of attribute labels accords with the order of attribute names; 3. In attribute labels, "1" represents positive while "-1" represents negative, '0' represents unknown; 4. 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> <evaluation status>

Notes: 1. In evaluation status, "train" represents training image, "val" represents validation image, "test" represents testing image; 2. Please refer to the paper "DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations" for more details.