All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog.
- Added integration with FiftyOne (#360)
- Added support for
torch.jit
to tasks where possible and documented task JIT compatibility (#389) - Added option to provide a
Sampler
to theDataModule
to use when creating aDataLoader
(#390) - Added support for multi-label text classification and toxic comments example (#401)
- Split
backbone
argument toSemanticSegmentation
intobackbone
andhead
arguments (#412)
- Fixed a bug where the
DefaultDataKeys.METADATA
couldn't be a dict (#393) - Fixed a bug where the
SemanticSegmentation
task would not work as expected with finetuning callbacks (#412)
- Fixed a bug where
flash.Trainer.from_argparse_args
+finetune
would not work (#382)
- Added
deeplabv3
,lraspp
, andunet
backbones for theSemanticSegmentation
task (#370)
- Changed the installation command for extra features (#346)
- Change resize interpolation default mode to nearest (#352)
- Deprecated
SemanticSegmentation
backbone namestorchvision/fcn_resnet50
andtorchvision/fcn_resnet101
, usefc_resnet50
andfcn_resnet101
instead (#370)
- Fixed
flash.Trainer.add_argparse_args
not adding any arguments (#343) - Fixed a bug where the translation task wasn't decoding tokens properly (#332)
- Fixed a bug where huggingface tokenizers were sometimes being pickled (#332)
- Fixed issue with
KorniaParallelTransforms
to assure to share the random state between transforms (#351) - Fixed a bug where using
val_split
withoverfit_batches
would give an infinite recursion (#375) - Fixed a bug where some timm models were mistakenly given a
global_pool
argument (#377) - Fixed
flash.Trainer.from_argparse_args
not passing arguments correctly (#380)
- Added DataPipeline API (#188 #141 #207)
- Added timm integration (#196)
- Added BaseViz Callback (#201)
- Added backbone API (#204)
- Added support for Iterable auto dataset (#227)
- Added multi label support (#230)
- Added support for schedulers (#232)
- Added visualisation callback for image classification (#228)
- Added Video Classification task (#216)
- Added Dino backbone for image classification (#259)
- Added Data Sources API (#256 #264 #272)
- Refactor preprocess_cls to preprocess, add Serializer, add DataPipelineState (#229)
- Added Semantic Segmentation task (#239 #287 #290)
- Added Object detection prediction example (#283)
- Added Style Transfer task and accompanying finetuning and prediction examples (#262)
- Added a Template task and tutorials showing how to contribute a task to flash (#306)
- Rename valid_ to val_ (#197)
- Refactor preprocess_cls to preprocess, add Serializer, add DataPipelineState (#229)
- Fix DataPipeline resolution in Task (#212)
- Fixed a bug where the backbone used in summarization was not correctly passed to the postprocess (#296)
- Added TIMM integration as backbones (#196)
- Fixed nltk.download (#210)
-
Switch to use
torchmetrics
(#169) -
Better support for
optimizer
andschedulers
(#232) -
Update lightning version to v1.2 (#133)
-
Fixed classification softmax (#169)
-
Fixed a bug where loading from a local checkpoint that had
pretrained=True
without an internet connection would sometimes raise an error (#237) -
Don't download data if exists (#157)
- Added
RetinaNet
&backbones
toObjectDetector
Task (#121) - Added .csv image loading utils (#116, #117, #118)
- Set inputs as optional (#109)
- Added
ObjectDetector
Task (#56) - Added TabNet for tabular classification (#101)
- Added support for more backbones(mobilnet, vgg, densenet, resnext) (#45)
- Added backbones for image embedding model (#63)
- Added SWAV and SimCLR models to
imageclassifier
+ backbone reorg (#68)
- Applied transform in
FilePathDataset
(#97) - Moved classification integration from vision root to folder (#86)