* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* register custom_hooks in runner
* set custom_hooks_config to cfg.get(custom_hooks, None)
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* move init_cfg to parameter
* isort
* Use a sentinel value to denote the default init_cfg
* Refector label smooth loss, now support mode `original`, `classy_vision`
and `multi_label`.
* Add unittests for label smooth loss.
* Improve docstring of LSR
* add increasing in solarize and posterize
* fix linting
* Revert "add increasing in solarize and posterize"
This reverts commit 128af36e9b.
* revise according to comments
* Add paramater magnitude_std in RandAugment to allow randomly movement of magnitude_value
* Add unittest for magnitude_std
* Improve docstring of magnitude_std
* GlabelAveragePooling support 1d, 2d and 3d by param, and add neck test
* Imporve neck test
* Change 'mode' attribute in GAP to 'dim', and add docstring
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* set cal_acc in ClsHead defaults to False
* set cal_acc defaults to False
* use *args, **kwargs instead
* change bs16 to 3 in test_image_classifier_vit
* fix some comments
* change cal_acc=True
* test LinearClsHead
* add imagenet bs 4096
* add vit_base_patch16_224_finetune
* add vit_base_patch16_224_pretrain
* add vit_base_patch16_384_finetune
* add vit_base_patch16_384_finetune
* add vit_b_p16_224_finetune_imagenet
* add vit_b_p16_224_pretrain_imagenet
* add vit_b_p16_384_finetune_imagenet
* add vit
* add vit
* add vit head
* vit unitest
* keep up with ClsHead
* test vit
* add flag to determiine whether to calculate acc during training
* Changes related to mmcv1.3.0
* change checkpoint saving interval to 10
* add label smooth
* default_runtime.py recovery
* docformatter
* docformatter
* delete 2 lines of comments
* delete configs/_base_/schedules/imagenet_bs4096.py
* add configs/_base_/schedules/imagenet_bs2048_AdamW.py
* rename imagenet_bs4096.py to imagenet_bs2048_AdamW.py
* add AutoAugment
* fix weight decay in vit
* change eval interval to 10
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* delete @torch.jit.ignore
* change eval interval back to 1
* add some comments to imagenet_bs2048_AdamW
* add some comments
* add convert_to_one_hot
* add test_label_smooth_loss
* add my label_smooth_loss
* fix CELoss bug
* test new label smooth loss
* LabelSmoothLoss downward compatibility
* add some comments
* remove the old version of LabelSmoothLoss
* add some comments
* add some comments
* add some comments
* add label smooth to config
* support random augmentation
* minor fix on posterize
* minor fix on posterize
* minor fix on cutout
* minor fix on cutout
* fix bug in solarize add
* revised according to comments
* Add mixup option
* Modify the structure of mixup and add configs
* Clean configs
* Add test for mixup and SoftCrossEntropyLoss
* Add simple test for ImageClassifier
* Fix bug in test_losses.py
* Add assertion in CrossEntropyLoss
* resolve conflicts
add heads and config for multilabel tasks
* minor change
* remove evaluating mAP in head
* add baseline config
* add configs
* reserve only one config
* minor change
* fix minor bug
* minor change
* minor change
* add unittests and fix docstrings
* support thr
* replace thrs with thr
* fix docstring
* minor change
* revise according to comments
* revised according to comments
* revise according to comments
* rewrite basedataset.evaluate to avoid duplicate calculation
* minor change
* change thr to thrs
* add more unit test
* support support, support class-wise evaluation results and move eval_metrics.py
* Fix docstring
* change average to be non-optional
* revise according to comments
* add more unittest
* add bce loss for multilabel task
* minor change
* apply class wise sum
* fix docstring
* do not apply sum over classes and fix docstring
* fix docstring
* fix weight shape
* fix weight shape
* fix docstring
* fix linting issue
Co-authored-by: Y. Xiong <xiongyuxy@gmail.com>
* add focal loss
* apply class wise sum
* fix doctring
* do not apply sum over classes and fix docstring
* fix docstring
* fix weight shape
* fix weight shape
* add mean_ap
* add difficult_examples in mAP to support dataset without difficult_examples
* fix docstring
* add CP,CR,CF1,OP,OR,OF1 as multilabel metrics
* fix docstring
* temporary solution to ci until new version of mmcv is avaliable (#127)
* temporary solution to ci until new version of mmcv is avaliable
* temporary solution to ci until new version of mmcv is avaliable
* add mean_ap
* add difficult_examples in mAP to support dataset without difficult_examples
* fix docstring
* add CP,CR,CF1,OP,OR,OF1 as multilabel metrics
* fix docstring
* Swap -1 and 0 for labels
* Revised according to comments
* Revised according to comments
* Revised according to comments
* Revert "Revised according to comments"
It is suggested that we should not include paper from arxiv.
This reverts commit 48a781cd6a.
* Revert "Revert "Revised according to comments""
This reverts commit 6d3b0f1a7b.
* Revert "Revised according to comments"
It is suggested we should not cite paper from arxiv.
This reverts commit 120ecda884.
* Revised according to comments
* revised according to comments
* Revised according to comments
* add macro-averaged precision,recall,f1 options in evaluation
* remove unnecessary comments
* Revise according to comments
* Revise according to comments
* Use build_runner in train api
* Support iter in eval_hook
* Add runner section
* Add test_eval_hook
* Pin mmcv version in install docs
* Replace max_iters with max_epochs
* Set by_epoch=True as default
* Remove trailing space
* Replace DeprecationWarning with UserWarning
* pre-commit
* Fix tests
* add model inference on single image
* rm --eval
* revise doc
* add inference tool and demo
* fix linting
* rename inference_image to inference_model
* infer pred_label and pred_score
* fix linting
* add docstr for inference
* add remove_keys
* add doc for inference
* dump results rather than outputs
* add class_names
* add related infer scripts
* add demo image and the first part of colab tutorial
* conduct evaluation in dataset
* return lst in simple_test
* compuate topk accuracy with numpy
* return outputs in test api
* merge inference and evaluation tool
* fix typo
* rm gt_labels in test conifg
* get gt_labels during evaluation
* sperate the ipython notebook to another PR
* return tensor for onnx_export
* detach var in simple_test
* rm inference script
* rm inference script
* construct data dict to replace LoadImage
* print first predicted result if args.out is None
* modify test_pipeline in inference
* refactor class_names of imagenet
* set class_to_idx as a property in base dataset
* output pred_class during inference
* remove unused docstr
* resize according to short edge
* revise doc for resize
* fix unitest for resize
* resize short_edge when second value of size is -1
* rename short_edge to short_side
whcao
AllentDan
WRH
q.yao
Ma Zerun
LXXXXR
Miao Zheng
Yinhao Li
Y. Xiong
Wenwei Zhang
mzr1996
QingChuanWS
agim-a
David de la Iglesia Castro
ftbabi
Ülkü Tuncer Küçüktaş
Lei Yang
Jerry Jiarui XU
anthracene
Xiaojie Li
Kai Chen
yanglei
lixiaojie