-
Annotations (Anno_fine/ Anno_coarse/)
-
Attribute Annotations (list_attr_cloth.txt & list_attr_img.txt)
clothing attribute labels. See ATTRIBUTE LABELS section below for more info.
-
Bounding Box Annotations (list_bbox.txt)
bounding box labels. See BBOX LABELS section below for more info.
-
Category Annotations (list_category_cloth.txt & list_category_img.txt)
clothing category labels. See CATEGORY LABELS section below for more info.
-
Fashion Landmark Annotations (list_landmarks.txt)
fashion landmark labels. See LANDMARK LABELS section below for more info.
-
-
Images (Img/)
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.
*.jpg
format: JPG
Notes:
- The long side of images are resized to 300;
- The aspect ratios of original images are kept unchanged.
list_bbox.txt
First Row: number of images
Second Row: entry names
Rest of the Rows: <image name> <bbox location>
Notes:
- The order of bbox labels accords with the order of entry names;
- 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].
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:
- The order of landmark labels accords with the order of entry names;
- 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;
- 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;
- In landmark visibility state, "0" represents visible, "1" represents invisible/occluded, "2" represents truncated/cut-off;
- 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"].
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:
- In category type, "1" represents upper-body clothes, "2" represents lower-body clothes, "3" represents full-body clothes;
- The order of category labels accords with the order of category names;
- In category labels, the number represents the category id in category names;
- For the clothing categories, "Cape", "Nightdress", "Shirtdress" and "Sundress" have been merged into "Dress";
- Category prediction is treated as a 1-of-K classification problem.
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:
- 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;
- The order of attribute labels accords with the order of attribute names;
- In attribute labels, "1" represents positive while "-1" represents negative, '0' represents unknown;
- Attribute prediction is treated as a multi-label tagging problem.
list_eval_partition.txt
First Row: number of images
Second Row: entry names
Rest of the Rows: <image name> <evaluation status>
Notes:
- In evaluation status, "train" represents training image, "val" represents validation image, "test" represents testing image;
- Please refer to the paper "DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations" for more details.