cvdatasets/scripts/info_files/info.yml

BASE_DIR: /home/korsch_data/

DATA_DIR: datasets
MODEL_DIR: models

############ Existing models
### weights are used for fine-tuning
MODELS:
  efficientnet:    &efficientnet
    folder: efficientnet
    class_key: efficientnet
    weights: model.imagenet.npz

  inception_inat:    &inception_inat
    folder: inception
    class_key: inception
    weights: model.inat.ckpt.npz

  inception_imagenet:    &inception_inet
    folder: inception
    class_key: inception
    weights: model.imagenet.ckpt.npz

  inception:    &inception
    <<: *inception_inat

  inception_tf_inat:  &inception_tf_inat
    folder: inception_tf
    class_key: inception_tf
    weights: inception_v3_iNat_299.ckpt

  inception_tf_inet:  &inception_tf_inet
    folder: inception_tf
    class_key: inception_tf
    weights: inception_v3_ILSVRC_299.ckpt

  inception_tf:  &inception_tf
    <<: *inception_tf_inat

  resnet:       &resnet50
    folder: resnet
    class_key: resnet
    weights: model.npz

  vgg19:       &vgg19
    folder: vgg19
    class_key: vgg19
    weights: model.npz

############ Existing Datasets
DATASETS:

  IMAGENET:         &inet
    folder: ImageNet
    annotations: "BJOERN"
    n_classes: 1000

  IMAGENET_TOP_INAT20: &inet_top_inat20
    <<: *inet
    annotations: "TOP_INAT20"
    n_classes: 44

  CUB200:         &cub200
    folder: birds/cub200
    annotations: "ORIGINAL"
    n_classes: 200

  CUB200_2FOLD:   &cub200_2fold
    folder: birds/cub200_2fold
    annotations: "ORIGINAL"
    n_classes: 200

  CUB200_GOOGLE: &cub200_google
    folder: birds/cub200_google_images
    annotations: "ORIGINAL"
    n_classes: 200

  CUB200_GOOGLE_SEM: &cub200_google_sem
    folder: birds/cub200_google_images
    annotations: "sem_selected"
    n_classes: 200


  NAB:         &nabirds
    folder: birds/nabirds
    annotations: "ORIGINAL"
    n_classes: 555

  BIRDSNAP:         &birdsnap
    folder: birds/birdsnap
    annotations: "RESIZED"
    n_classes: 500


  CARS:         &cars
    folder: cars
    annotations: "ORIGINAL"
    n_classes: 196

  DOGS:         &dogs
    folder: dogs
    annotations: "ORIGINAL"
    n_classes: 120

  FLOWERS:         &flowers
    folder: flowers
    annotations: "flowers102"
    n_classes: 102

  INAT20:         &inat20
    folder: inat
    annotations: "2020/PLAIN"
    n_classes: 200

  INAT20_IN_CLASS:         &inat20_in_class
    <<: *inat20
    annotations: "2020/IN_CLASS"

  INAT20_NOISY_IN_CLASS: &inat20_noisy_in_class
    <<: *inat20
    annotations: "2020/NOISY_IN_CLASS"

  INAT20_OUT_CLASS:         &inat20_out_class
    <<: *inat20
    annotations: "2020/OUT_CLASS"

  INAT20_NOISY_OUT_CLASS:         &inat20_noisy_out_class
    <<: *inat20
    annotations: "2020/NOISY_OUT_CLASS"

  INAT20_U_OUT_CLASS:         &inat20_u_out_class
    <<: *inat20
    annotations: "2020/U_OUT_CLASS"

  INAT20_TEST:    &inat20_test
    <<: *inat20
    annotations: "2020/TEST"

  INAT19:         &inat19
    folder: inat
    annotations: "2019"
    n_classes: 1010

  INAT18:         &inat18
    folder: inat
    annotations: "2018"
    n_classes: 8142

  INAT19_MINI:    &inat19_mini
    <<: *inat19
    annotations: "2019_small"

  INAT19_TEST:    &inat19_test
    <<: *inat19
    annotations: "2019_test"


  HED:         &hed
    folder: medical/HED
    annotations: "patches224x224"
    n_classes: 2

  TIGERS:         &tigers
    folder: tigers
    annotations: "reid/train"
    n_classes: 107

  TIGERS_TEST:         &tigers_test
    folder: tigers
    annotations: "reid/test"
    n_classes: 107

############ Existing Part Annotations and Part Features
### feature file name composition:
# ${BASE_DIR}/${DATA_DIR}/${DATASETS:folder}/${PART_TYPES:annotations}/features

PART_TYPES:
  GLOBAL:         &parts_global
    feature_suffix: ""

  UNI:            &parts_uni
    is_uniform: true
    feature_suffix: _26parts_uniform
    rescale_size: !!int -1
    scales:
     - 0.2

  GT:             &parts_gt
    feature_suffix: _16parts_gt
    rescale_size: !!int -1
    scales:
     - 0.31

  GT2:            &parts_gt2
    feature_suffix: _5parts_gt
    rescale_size: !!int -1
    scales:
      - 0.31

  NAC:            &parts_nac
    feature_suffix: _20parts
    rescale_size: !!int 224
    scales:
      - 0.31
      - 0.45

  L1_pred:        &parts_l1p
    feature_suffix: _5parts_L1_pred
    rescale_size: !!int 299
    scales:
      - 0.31

  L1_full:        &parts_l1f
    feature_suffix: _5parts_L1_full
    rescale_size: !!int 299
    scales:
      - 0.31

  NTS:        &parts_nts
    feature_suffix: _7parts_nts
    rescale_size: !!int 448
    scales:
      - 0.31

  NTS2:        &parts_nts2
    feature_suffix: _5parts_nts
    rescale_size: !!int 448
    scales:
      - 0.31

PARTS:
  #### No Parts Annotations

  IMAGENET_GLOBAL:
    <<: *inet
    <<: *parts_global

  IMAGENET_TOP_INAT20_GLOBAL:
    <<: *inet_top_inat20
    <<: *parts_global

  CUB200_2FOLD_GLOBAL:
    <<: *cub200_2fold
    <<: *parts_global

  CUB200_GLOBAL:
    <<: *cub200
    <<: *parts_global

  CUB200_GOOGLE_GLOBAL:
    <<: *cub200_google
    <<: *parts_global

  CUB200_GOOGLE_SEM_GLOBAL:
    <<: *cub200_google_sem
    <<: *parts_global


  CARS_GLOBAL:
    <<: *cars
    <<: *parts_global

  DOGS_GLOBAL:
    <<: *dogs
    <<: *parts_global

  NAB_GLOBAL:
    <<: *nabirds
    <<: *parts_global

  BIRDSNAP_GLOBAL:
    <<: *birdsnap
    <<: *parts_global

  FLOWERS_GLOBAL:
    <<: *flowers
    <<: *parts_global

  INAT18_GLOBAL:
    <<: *inat18
    <<: *parts_global

  INAT19_GLOBAL:
    <<: *inat19
    <<: *parts_global

  INAT19_MINI_GLOBAL:
    <<: *inat19_mini
    <<: *parts_global
    feature_suffix: .mini

  INAT19_TEST_GLOBAL:
    <<: *inat19_test
    <<: *parts_global
    feature_suffix: .test

  INAT20_GLOBAL:
    <<: *inat20
    <<: *parts_global

  INAT20_TEST_GLOBAL:
    <<: *inat20_test
    <<: *parts_global

  INAT20_IN_CLASS_GLOBAL:
    <<: *inat20_in_class
    <<: *parts_global

  INAT20_OUT_CLASS_GLOBAL:
    <<: *inat20_out_class
    <<: *parts_global

  INAT20_U_OUT_CLASS_GLOBAL:
    <<: *inat20_u_out_class
    <<: *parts_global

  INAT20_NOISY_OUT_CLASS_GLOBAL:
    <<: *inat20_noisy_out_class
    <<: *parts_global

  INAT20_NOISY_IN_CLASS_GLOBAL:
    <<: *inat20_noisy_in_class
    <<: *parts_global

  HED_GLOBAL:
    <<: *hed
    <<: *parts_global

  TIGERS_GLOBAL:
    <<: *tigers
    <<: *parts_global
    rescale_size: !!int -1
    scales:
      - .31

  TIGERS_TEST_GLOBAL:
    <<: *tigers_test
    <<: *parts_global

  #### With Parts Annotations


  ####################################
  # CUB200-2011 2-Fold training set
  ####################################

  CUB200_2FOLD_L1_pred:
    <<: *cub200_2fold
    <<: *parts_l1p
    annotations: L1_pred
    rescale_size: !!int 427

  CUB200_2FOLD_L1_full:
    <<: *cub200_2fold
    <<: *parts_l1f
    annotations: L1_full
    rescale_size: !!int 427

  ####################################
  # CUB200-2011
  ####################################

  CUB200_UNI:
    <<: *cub200
    <<: *parts_uni

  CUB200_GT:
    <<: *cub200
    <<: *parts_gt

  CUB200_GT2:
    <<: *cub200
    <<: *parts_gt2
    annotations: cub200_11_regrouped

  CUB200_NAC:
    <<: *cub200
    <<: *parts_nac
    annotations: NAC/2017-bilinear

  CUB200_NTS:
    <<: *cub200
    <<: *parts_nts
    annotations: NTS

  CUB200_NTS2:
    <<: *cub200
    <<: *parts_nts2
    annotations: NTS2

  CUB200_L1_pred:
    <<: *cub200
    <<: *parts_l1p
    annotations: cub200_11_L1_pred_old
    # rescale_size: !!int 427

  CUB200_L1_full:
    <<: *cub200
    <<: *parts_l1f
    annotations: cub200_11_L1_full_old
    # rescale_size: !!int 427

  CUB200_L1_pred_15:
    <<: *cub200
    <<: *parts_l1p
    annotations: L1_pred_15
    rescale_size: !!int 427
    feature_suffix: _15parts_L1_pred

  CUB200_L1_full_15:
    <<: *cub200
    <<: *parts_l1f
    annotations: L1_full_15
    rescale_size: !!int 427
    feature_suffix: _15parts_L1_full

  CUB200_L1_pred_2:
    <<: *cub200
    <<: *parts_l1p
    annotations: L1_pred_2
    rescale_size: !!int 427
    feature_suffix: _2parts_L1_pred

  CUB200_L1_full_2:
    <<: *cub200
    <<: *parts_l1f
    annotations: L1_full_2
    rescale_size: !!int 427
    feature_suffix: _2parts_L1_full


  ####################################
  # NA Birds
  ####################################

  NAB_GT:
    <<: *nabirds
    <<: *parts_gt

  NAB_L1_pred:
    <<: *nabirds
    <<: *parts_l1p
    annotations: L1_pred
    rescale_size: !!int 427

  NAB_L1_full:
    <<: *nabirds
    <<: *parts_l1f
    annotations: L1_full
    rescale_size: !!int 427


  ####################################
  # BIRDSNAP
  ####################################

  BIRDSNAP_L1_pred:
    <<: *birdsnap
    <<: *parts_l1p
    annotations: L1_pred
    rescale_size: !!int 427

  BIRDSNAP_L1_full:
    <<: *birdsnap
    <<: *parts_l1f
    annotations: L1_full
    rescale_size: !!int 427

  ####################################
  # Stanford Cars
  ####################################

  CARS_L1_pred:
    <<: *cars
    <<: *parts_l1p
    annotations: L1_pred

  CARS_L1_full:
    <<: *cars
    <<: *parts_l1f
    annotations: L1_full


  ####################################
  # Flowers 102
  ####################################

  FLOWERS_L1_pred:
    <<: *flowers
    <<: *parts_l1p
    annotations: L1_pred

  FLOWERS_L1_full:
    <<: *flowers
    <<: *parts_l1f
    annotations: L1_full


  ####################################
  # iNaturalist 2019
  ####################################

  INAT19_MINI_L1_pred:
    <<: *inat19_mini
    <<: *parts_l1p
    annotations: 2019_small_L1_pred
    feature_suffix: _5parts_L1_pred.mini

  INAT19_MINI_L1_full:
    <<: *inat19_mini
    <<: *parts_l1f
    annotations: 2019_small_L1_full
    feature_suffix: _5parts_L1_full.mini

  INAT19_TEST_L1_pred:
    <<: *inat19_test
    <<: *parts_l1p
    annotations: 2019_test_L1_pred
    feature_suffix: _5parts_L1_pred.test

  INAT19_TEST_L1_full:
    <<: *inat19_test
    <<: *parts_l1f
    annotations: 2019_test_L1_full
    feature_suffix: _5parts_L1_full.test