Changes in version 0.9.0.9000                      

                 Changes in version 0.9.0 (2026-04-22)                  

Breaking changes

  - Split coco_detection_dataset() into coco_detection_dataset()
    (detection only) and new coco_segmentation_dataset() (instance
    segmentation) reducing memory usage by ~50% (@Chandraveersingh1717,
    #280).
  - coco_classes() is now aligned with the 90 sparse pytorch COCO
    classses, in order to match pretrained model predictions. (@318).
  - Renamed $categories to $classes for consistency (character vector of
    class names; old attribute is deprecated with a warning) (#300).

New features

  - Added resolution function for COCO Imagenet_21k and Pascal_VOC
    classes and labels (#284).
  - Added article showcasing model_fcn_resnet50() with visualization
    utilities draw_segmentation_masks() and vision_make_grid()
    (@DerrickUnleashed, #281).
  - Added collection dataset catalog with search_collection(),
    get_collection_catalog(), and list_collection_datasets() functions
    for discovering and exploring collections (#271, @ANAMASGARD).
  - Added target_transform_coco_masks() and
    target_transform_trimap_masks() transformation functions for
    explicit segmentation mask generation (@ANAMASGARD).
  - Added support for connectivity argument for drawing lines between
    keypoints in draw_keypoints() (@DerrickUnleashed, #303).

New models

  - Added model_maskrcnn_resnet50_fpn() and
    model_maskrcnn_resnet50_fpn_v2() for instance segmentation (#278,
    @ANAMASGARD).
  - Added model_convnext_*_detection() for object detection, with *
    within tiny/small/base (#262, @ANAMASGARD).
  - Added model_convnext_*_fcn() and model_convnext_*_upernet() for
    semantic segmentation, with * within tiny/small/base (#265,
    @ANAMASGARD).

New datasets

  - Added vggface2_dataset() for loading the VGGFace2 dataset
    (@DerrickUnleashed, #238).
  - Added moth dataset to rf100_biology_collection() and currency and
    wine_label to rf100_document_collection() (#274).

Bug fixes and improvements

  - model_maskrcnn_*() and model_fasterrcnn_*() now match the pytorch
    implementation (#318).
  - transform_ now correctly manage batched 4D torch tensors and 4D
    arrays (#313).
  - mnist_datataset() and derivatives now correctly return item x()
    values with a 1-channel dimension (@Chandraveersingh1717, #307).
  - transform_affine(), transform_rotate() and random derivatives now
    use interpolation and fill parameter in favor of resampleand
    fillcolor (@Chandraveersingh1717, #299).
  - Fixed draw_keypoints() documentation and error message
    (@srishtiii28, #296).
  - Standardized dataset messages: download messages now include split
    information, success messages show image count and class count for
    consistency.
  - fix model_fasterrcnn_* did not provide boxes output normalized to
    image size, did not manage batches, fix performance of the
    roi_align() function (#284).
  - fix rf100 collection bounding-box now consider the correct native
    COCO format being 'xywh' (#272).
  - Remove .getbatch method from MNIST as it is providing inconsistent
    tensor dimensions with .getitem due to non-vectorized transform_
    operations (#264).
  - Added article for draw_keypoints() (@DerrickUnleashed, #303).
  - Fix typos and align model documentation for model_deeplabv3_* and
    model_convnext_*_detection() to ensure consistency
    (@DerrickUnleashed #302).
  - Fixed draw_keypoints() documentation: corrected connectivity
    parameter type, obsolete note, colors description default
    (@srishtiii28 #296).

                 Changes in version 0.8.0 (2025-11-06)                  

New datasets

  - Added lfw_people_dataset() and lfw_pairs_dataset() for loading
    Labelled Faces in the Wild (LFW) datasets (@DerrickUnleashed, #203).
  - Added places365_dataset() for loading the Places365 dataset
    (@koshtiakanksha, #196).
  - Added pascal_segmentation_dataset(), and pascal_detection_dataset()
    for loading the Pascal Visual Object Classes datasets
    (@DerrickUnleashed, #209).
  - Added whoi_plankton_dataset(), whoi_small_plankton_dataset(), and
    whoi_small_coral_dataset() (@cregouby, #236).
  - Added rf100_document_collection(), rf100_medical_collection(),
    rf100_biology_collection(), rf100_damage_collection(),
    rf100_infrared_collection(), and rf100_underwater_collection().
    These are collections of datasets from Roboflow 100 under the same
    theme, for a total of 35 datasets (@koshtiakanksha, @cregouby,
    #239).
  - Added rf100_peixos_segmentation_dataset(). (@koshtiakanksha,
    @cregouby, #250).

New models

  - Added model_maxvit() for MaxViT: Multi-Axis Vision Transformer
    (#229, @koshtiakanksha).
  - Added model_facenet_pnet(), model_facenet_rnet(), and
    model_facenet_onet() for Facenet MTCNN face detection models.
    (@DerrickUnleashed, #227)
  - Added model_mtcnn() and model_inception_resnet_v1() models for face
    detection and recognition. (@DerrickUnleashed, #217)
  - Added model_mobilenet_v3_large() and model_mobilenet_v3_small()
    models for efficient image classification. (@DerrickUnleashed, #237)
  - Added 8 of the model_convnext_() family models for image
    classification, thanks to @horlar1 contribution. (@cregouby, #251)
  - Added 2 model_fasterrcnn_resnet50_() models and 2
    model_fasterrcnn_mobilenet_v3_large_() for object detection.
    (@koshtiakanksha, #251)

New features

  - Added imagenet_label() and imagenet_classes() for ImageNet classes
    resolution (#229, @koshtiakanksha).
  - base_loader() now accept URLs (@cregouby, #246).
  - draw_segmentation_masks() now accepts semantic segmentation models
    torch_float() output. (@cregouby #247)
  - MNIST datasets and Roboflow 100 collections now have a .getbatch
    attached method (@cregouby #255)

Bug fixes and improvements

  - Switch pre 0.5.0 models to their /v2/ URL in torch-cdn.mlverse.org.
    (#215)
  - Models are now separated in the documentation by tasks between
    classification, object detection, and semantic segmentation models
    (@cregouby, #247)
  - Breaking Change : Refactoring of coco_* dataset family now provides
    each item$x being an image array (for consistency with other
    datasets). You can use transform = transform_to_tensor to restore
    the previous x output to be a torch_tensor().
  - transform_ are now documented into 3 different categories: unitary
    transformations, random transformations and combining
    transformations. (@cregouby, #250)
  - Deprecation : emnist_dataset is deprecated in favor of
    emnist_collection() (@cregouby, #260).

                 Changes in version 0.7.0 (2025-07-18)                  

New datasets

  - Added fashion_mnist_dataset() for loading the Fashion-MNIST dataset
    (@koshtiakanksha, #148).
  - Added eurosat_dataset(), eurosat_all_bands_dataset(), and
    eurosat100_dataset() for loading RGB, all-band, and small-subset
    variants of the EuroSAT dataset (@cregouby, #126).
  - Added qmnist_dataset() for loading the QMNIST dataset
    (@DerrickUnleashed, #153).
  - Added emnist_dataset() for loading the EMNIST dataset
    (@DerrickUnleashed, #152).
  - Added fgvc_aircraft_dataset() for loading the FGVC-Aircraft dataset
    (@DerrickUnleashed, #156).
  - Added coco_detection_dataset() and coco_caption_dataset() for
    loading the MS COCO detection and captions datasets
    (@koshtiakanksha, #161, #172).
  - Added caltech101_dataset() and caltech256_dataset() for loading the
    Caltech 101 and 256 datasets (@DerrickUnleashed, #158).
  - Added fer_dataset() for loading the FER-2013 dataset
    (@DerrickUnleashed, #154).
  - Added flowers102_dataset() for loading the Flowers102 dataset
    (@DerrickUnleashed, #157).
  - Added flickr8k_dataset() and flickr30k_dataset() for loading the
    Flickr8k and Flickr30k datasets (@DerrickUnleashed, #159).
  - Added oxfordiiitpet_dataset(), oxfordiiitpet_binary_dataset(), and
    oxfordiiitpet_segmentation_dataset() for loading the Oxford-IIIT Pet
    datasets (@DerrickUnleashed, #162).
  - Added rf100_document_collection(), rf100_underwater_collection(),
    rf100_medical_collection(), rf100_biology_collection(), and
    rf100_peixos_segmentation_dataset() for loading Roboflow 100
    datasets (@koshtiakanksha, #239).

New models

  - Added EfficientNet model family (B0–B7) – scalable CNNs for image
    classification. (#166, @koshtiakanksha)
  - Added EfficientNetV2 model family (V2-S/M/L) – improved EfficientNet
    models for faster training. (#166, @koshtiakanksha)
  - Added model_vit_b_16(), model_vit_b_32(), model_vit_l_16(),
    model_vit_l_32(), and model_vit_h_14() for loading Vision
    Transformer models (@DerrickUnleashed, #202).

New features

  - tensor_image_display() and tensor_image_browse() now accept all
    tensor_image dtypes (@cregouby, #115).
  - draw_bounding_boxes() and draw_segmentation_masks() now accept
    image_with_bounding_box and image_with_segmentation_mask inputs
    which are the default items class for respectively detection
    datasets and segmentation datasets (@koshtiakanksha, #175).
  - fgvc_aircraft_dataset() gains support for annotation_level = "all"
    (@DerrickUnleashed, #168).
  - folder_dataset() now supports TIFF image formats (@cregouby, #169).
  - New nms() and batched_nms() functions provide Non-Maximum
    Suppression utilities. Added box_convert() to convert between
    bounding box formats (@Athospd, #40).

Minor bug fixes and improvements

  - transform_rotation() now correctly uses width × height for image
    size instead of width × width (@cregouby, #114).
  - Clarified documentation for transform_affine() to reduce confusion
    with transform_random_affine() (@cregouby, #116).
  - Added French translations for message outputs (@cregouby, #112).

                 Changes in version 0.6.0 (2024-06-14)                  

  - Remove again dependency on zip::unzip added in version 0.4.0. (#89)
  - Improve performance on tinyimagenet-alexnet example (#90,
    @statist-bhfz)
  - Updated URL of downloaded resources to use the new torch CDN. (#109)

                 Changes in version 0.5.1 (2023-04-14)                  

  - Remove usage of torch_lstsq that was removed in torch v0.10.0

                 Changes in version 0.5.0 (2023-03-15)                  

  - Bugs fixed in transform_adjust_hue() and
    transform_linear_transformation() (#72, #73, @sebffischer)
  - add draw_bounding_boxes() , draw_segmentation_masks() and
    draw_keypoints() on top of image tensors, and add a convenience
    tensor_image_browse() and tensor_image_display() functions to
    visualize image tensors respectively in browser or in X11 device
    (#80, @cregouby)
  - Added the InceptionV3 model. (#82)

                 Changes in version 0.4.1 (2022-01-28)                  

  - Implemented MobileNetV2 (#60)
  - Improved vignettes so they use nnf_cross_entropy for numerical
    stability. (#61)
  - Implement the full list of ResNet model family (#66, @cregouby)
  - Improved how datasets and models are downloaded by using a large
    timeout by default and downloading to temporary file to avoid hard
    to debug errors when the files are corrupt. (#67)

                 Changes in version 0.4.0 (2021-08-17)                  

  - Added a dependency on zip to zip::unzip the tinyimagenet dataset.
  - Removed all usages of torch::enumerate() from docs and tests in
    favor of coro::loop() (#57)
  - Fixed non-namespaced calls to torch. (#58)

                 Changes in version 0.3.0 (2021-05-04)                  

  - Use a self hosted version of the MNIST dataset to avoid frequent
    download failures. (#48)
  - Fix torch_arange calls after breaking change in torch. (#47)
  - Fix bug in transform_resize when passing size with length 1. (#49)

                 Changes in version 0.2.0 (2021-01-05)                  

  - Fixed bugs in transform_rotate. (#31)
  - Fixed bugs in transform_random_affine and transform_affine (#32)
  - Added VGG model (#35)

                 Changes in version 0.1.0 (2020-10-29)                  

  - Added a NEWS.md file to track changes to the package.