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lfw_people_dataset() and
lfw_pairs_dataset() for loading Labelled Faces in the Wild
(LFW) datasets (@DerrickUnleashed, #203).places365_dataset()for loading the Places365
dataset (@koshtiakanksha, #196).pascal_segmentation_dataset(), and
pascal_detection_dataset() for loading the Pascal Visual
Object Classes datasets (@DerrickUnleashed, #209).whoi_plankton_dataset(),
whoi_small_plankton_dataset(), and
whoi_small_coral_dataset() (@cregouby, #236).rf100_document_collection(),
rf100_medical_collection(),
rf100_biology_collection(),
rf100_damage_collection(),
rf100_infrared_collection(), and
rf100_underwater_collection() . Those are collection of
datasets from RoboFlow 100 under the same thematic, for a total of 35
datasets (@koshtiakanksha, @cregouby, #239).rf100_peixos_segmentation_dataset(). (@koshtiakanksha,
@cregouby,
#250).model_maxvit() for MaxViT: Multi-Axis Vision
Transformer (#229, @koshtiakanksha).model_facenet_pnet(),
model_facenet_rnet(), and model_facenet_onet()
for Facenet MTCNN face detection models. (@DerrickUnleashed, #227)model_mtcnn() and
model_inception_resnet_v1() models for face detection and
recognition. (@DerrickUnleashed, #217)model_mobilenet_v3_large() and
model_mobilenet_v3_small() models for efficient image
classification. (@DerrickUnleashed, #237)model_convnext_() family models for
image classification, thanks to @horlar1 contribution. (@cregouby, #251)model_fasterrcnn_resnet50_() models and 2
model_fasterrcnn_mobilenet_v3_large_() for object
detection. (@koshtiakanksha, #251)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).getbatch attached method (@cregouby #255)/v2/ URL in
torch-cdn.mlverse.org. (#215)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)emnist_dataset is deprecated in favor of
emnist_collection() (@cregouby, #260).fashion_mnist_dataset() for loading the
Fashion-MNIST dataset (@koshtiakanksha, #148).eurosat_dataset(),
eurosat_all_bands_dataset(), and
eurosat100_dataset() for loading RGB, all-band, and
small-subset variants of the EuroSAT dataset (@cregouby, #126).qmnist_dataset() for loading the QMNIST dataset
(@DerrickUnleashed, #153).emnist_dataset() for loading the EMNIST dataset
(@DerrickUnleashed, #152).fgvc_aircraft_dataset() for loading the
FGVC-Aircraft dataset (@DerrickUnleashed, #156).coco_detection_dataset() and
coco_caption_dataset() for loading the MS COCO detection
and captions datasets (@koshtiakanksha, #161, #172).caltech101_dataset() and
caltech256_dataset() for loading the Caltech 101 and 256
datasets (@DerrickUnleashed, #158).fer_dataset() for loading the FER-2013 dataset
(@DerrickUnleashed, #154).flowers102_dataset() for loading the Flowers102
dataset (@DerrickUnleashed, #157).flickr8k_dataset() and
flickr30k_dataset() for loading the Flickr8k and Flickr30k
datasets (@DerrickUnleashed, #159).oxfordiiitpet_dataset(),
oxfordiiitpet_binary_dataset(), and
oxfordiiitpet_segmentation_dataset() for loading the
Oxford-IIIT Pet datasets (@DerrickUnleashed, #162).rf100_document_collection(),
rf100_underwater_collection(),
rf100_medical_collection(),
rf100_biology_collection(), and
rf100_peixos_segmentation_dataset() for loading Roboflow
100 datasets (@koshtiakanksha, #239).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).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).nms() and batched_nms() functions
provide Non-Maximum Suppression utilities. Added
box_convert() to convert between bounding box formats
(@Athospd, #40).transform_rotation() now correctly uses width × height
for image size instead of width × width (@cregouby, #114).transform_affine() to
reduce confusion with transform_random_affine() (@cregouby, #116).zip::unzip added in version
0.4.0. (#89)tinyimagenet-alexnet example
(#90, @statist-bhfz)torch_lstsq that was removed in torch
v0.10.0transform_adjust_hue() and
transform_linear_transformation() (#72, #73, @sebffischer)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)nnf_cross_entropy for
numerical stability. (#61)zip to zip::unzip
the tinyimagenet dataset.torch::enumerate() from docs and
tests in favor of coro::loop() (#57)torch. (#58)torch_arange calls after breaking change in
torch. (#47)transform_resize when passing
size with length 1. (#49)transform_rotate. (#31)transform_random_affine and
transform_affine (#32)NEWS.md file to track changes to the
package.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.