DeepFashion Fine-Grained Fashion Classification

Large-scale fashion dataset with attribute prediction, consumer-to-shop matching, and landmark detection (Liu et al., CVPR 2016). Annotate clothing with 1000 categories and 50 attributes.

Fichier de configurationconfig.yaml

# DeepFashion Fine-Grained Fashion Classification Configuration
# Based on Liu et al., CVPR 2016

annotation_task_name: "DeepFashion Clothing Classification"
task_dir: "."

data_files:
  - "sample-data.json"

item_properties:
  id_key: "id"
  text_key: "image_url"
  context_key: "context"

user_config:
  allow_all_users: true

annotation_schemes:
  - annotation_type: "radio"
    name: "clothing_category"
    description: "Select the clothing category"
    labels:
      - name: "upper_body"
        tooltip: "Tops, shirts, jackets"
      - name: "lower_body"
        tooltip: "Pants, skirts, shorts"
      - name: "full_body"
        tooltip: "Dresses, jumpsuits"
      - name: "outerwear"
        tooltip: "Coats, jackets, blazers"

  - annotation_type: "multiselect"
    name: "texture_attributes"
    description: "Select texture attributes"
    labels:
      - name: "solid"
        tooltip: "Solid color"
      - name: "striped"
        tooltip: "Striped pattern"
      - name: "floral"
        tooltip: "Floral pattern"
      - name: "plaid"
        tooltip: "Plaid/checkered"
      - name: "spotted"
        tooltip: "Polka dots or spots"
      - name: "graphic"
        tooltip: "Graphics or prints"

  - annotation_type: "multiselect"
    name: "style_attributes"
    description: "Select style attributes"
    labels:
      - name: "casual"
        tooltip: "Casual style"
      - name: "formal"
        tooltip: "Formal/business"
      - name: "sporty"
        tooltip: "Athletic/sporty"
      - name: "vintage"
        tooltip: "Vintage/retro"
      - name: "bohemian"
        tooltip: "Bohemian style"
      - name: "minimalist"
        tooltip: "Minimalist design"

  - annotation_type: "multiselect"
    name: "fabric_attributes"
    description: "Select fabric attributes"
    labels:
      - name: "cotton"
        tooltip: "Cotton fabric"
      - name: "denim"
        tooltip: "Denim/jeans"
      - name: "leather"
        tooltip: "Leather"
      - name: "silk"
        tooltip: "Silk or satin"
      - name: "wool"
        tooltip: "Wool or knit"
      - name: "lace"
        tooltip: "Lace"

  - annotation_type: "radio"
    name: "sleeve_length"
    description: "Sleeve length (if applicable)"
    labels:
      - name: "sleeveless"
        tooltip: "No sleeves"
      - name: "short_sleeve"
        tooltip: "Short sleeves"
      - name: "long_sleeve"
        tooltip: "Long sleeves"
      - name: "not_applicable"
        tooltip: "Not applicable"

interface_config:
  item_display_format: "<img src='{{text}}' style='max-width:100%; max-height:500px;'/><br/><small>{{context}}</small>"

output_annotation_format: "json"
output_annotation_dir: "annotations"

Données d'exemplesample-data.json

[
  {
    "id": "fashion_001",
    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/e/e5/Red_coat.jpg/800px-Red_coat.jpg",
    "context": "Annotate this clothing item with category, texture, style, and fabric attributes."
  },
  {
    "id": "fashion_002",
    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/c/c2/Aiga_toiletsq_men.svg/800px-Aiga_toiletsq_men.svg.png",
    "context": "Classify the clothing and select all applicable attributes."
  }
]

// ... and 1 more items

Obtenir ce design

View on GitHub

Clone or download from the repository

Démarrage rapide :

git clone https://github.com/davidjurgens/potato-showcase.git
cd potato-showcase/image/specialized/deepfashion
potato start config.yaml

Détails

Types d'annotation

multiselectradio

Domaine

Computer VisionFashion

Cas d'utilisation

Fashion ClassificationAttribute PredictionVisual Search

Étiquettes

deepfashionfashionclothingattributescvpr2016

Vous avez trouvé un problème ou souhaitez améliorer ce design ?

Ouvrir un ticket

Designs associés

ADE20K Semantic Segmentation

Comprehensive scene parsing with 150 semantic categories (Zhou et al., CVPR 2017). Annotate indoor and outdoor scenes with pixel-level labels covering objects, parts, and stuff classes.

multiselectradio

BDD100K Autonomous Driving Segmentation

Large-scale diverse driving video dataset (Yu et al., CVPR 2020). Annotate driving scenes with bounding boxes, lane markings, drivable areas, and full-frame instance segmentation.

multiselectradio

CUB-200-2011 Fine-Grained Bird Classification

Fine-grained visual categorization of 200 bird species (Wah et al., 2011). Annotate bird images with species labels, part locations, and attribute annotations.

multiselectradio