* upload original backbone and configs
* ConvNext Refactor
* ConvNext Refactor
* convnext customization refactor with mmseg style
* convnext customization refactor with mmseg style
* add ade20k_640x640.py
* upload files for training
* delete dist_optimizer_hook and remove layer_decay_optimizer_constructor
* check max(out_indices) < num_stages
* add unittest
* fix lint error
* use MMClassification backbone
* fix bugs in base_1k
* add mmcls in requirements/mminstall.txt
* add mmcls in requirements/mminstall.txt
* fix drop_path_rate and layer_scale_init_value
* use logger.info instead of print
* add mmcls in runtime.txt
* fix f string && delete
* add doctring in LearningRateDecayOptimizerConstructor and fix mmcls version in requirements
* fix typo in LearningRateDecayOptimizerConstructor
* use ConvNext models in unit test for LearningRateDecayOptimizerConstructor
* add unit test
* fix typo
* fix typo
* add layer_wise and fix redundant backbone.downsample_norm in it
* fix unit test
* give a ground truth lr_scale and weight_decay
* upload models and readme
* delete 'backbone.stem_norm' and 'backbone.downsample_norm' in get_num_layer()
* fix unit test and use mmcls url
* update md2yml.py and metafile
* fix typo
* support iSAID aerial dataset
* Update and rename docs/dataset_prepare.md to 博士/dataset_prepare.md
* Update dataset_prepare.md
* fix typo
* fix typo
* fix typo
* remove imgviz
* fix wrong order in annotation name
* upload models&logs
* upload models&logs
* add load_annotations
* fix unittest coverage
* fix unittest coverage
* fix correct crop size in config
* fix iSAID unit test
* fix iSAID unit test
* fix typos
* fix wrong crop size in readme
* use smaller figure as test data
* add smaller dataset in test data
* add blank in docs
* use 0 bytes pseudo data
* add footnote and comments for crop size
* change iSAID to isaid and add default value in it
* change iSAID to isaid in _base_
Co-authored-by: MengzhangLI <mcmong@pku.edu.cn>
* fix single loss type
* fix error in ohem & point_head
* fix coverage miss
* fix uncoverage error of PointHead loss
* fix coverage miss
* fix uncoverage error of PointHead loss
* nn.modules.container.ModuleList to nn.ModuleList
* more simple format
* merge unittest def
* [Feature] Add tool to show origin or augmented train data
* [Feature] Support eval concate dataset
* Add docstring and modify evaluate of concate dataset
Signed-off-by: FreyWang <wangwxyz@qq.com>
* format concat dataset in subfolder of imgfile_prefix
Signed-off-by: FreyWang <wangwxyz@qq.com>
* add unittest of concate dataset
Signed-off-by: FreyWang <wangwxyz@qq.com>
* update unittest for eval dataset with CLASSES is None
Signed-off-by: FreyWang <wangwxyz@qq.com>
* [FIX] bug of generator, which lead metric to nan when pre_eval=False
Signed-off-by: FreyWang <wangwxyz@qq.com>
* format code
Signed-off-by: FreyWang <wangwxyz@qq.com>
* add more unittest
* add more unittest
* optim concat dataset builder
* Support progressive test with fewer memory cost.
* Temp code
* Using processor to refactor evaluation workflow.
* refactor eval hook.
* Fix process bar.
* Fix middle save argument.
* Modify some variable name of dataset evaluate api.
* Modify some viriable name of eval hook.
* Fix some priority bugs of eval hook.
* Depreciated efficient_test.
* Fix training progress blocked by eval hook.
* Depreciated old test api.
* Fix test api error.
* Modify outer api.
* Build a sampler test api.
* TODO: Refactor format_results.
* Modify variable names.
* Fix num_classes bug.
* Fix sampler index bug.
* Fix grammaly bug.
* Support batch sampler.
* More readable test api.
* Remove some command arg and fix eval hook bug.
* Support format-only arg.
* Modify format_results of datasets.
* Modify tool which use test apis.
* support cityscapes eval
* fixed cityscapes
* 1. Add comments for batch_sampler;
2. Keep eval hook api same and add deprecated warning;
3. Add doc string for dataset.pre_eval;
* Add efficient_test doc string.
* Modify test tool to compat old version.
* Modify eval hook to compat with old version.
* Modify test api to compat old version api.
* Sampler explanation.
* update warning
* Modify deploy_test.py
* compatible with old output, add efficient test back
* clear logic of exclusive
* Warning about efficient_test.
* Modify format_results save folder.
* Fix bugs of format_results.
* Modify deploy_test.py.
* Update doc
* Fix deploy test bugs.
* Fix custom dataset unit tests.
* Fix dataset unit tests.
* Fix eval hook unit tests.
* Fix some imcompatible.
* Add pre_eval argument for eval hooks.
* Update eval hook doc string.
* Make pre_eval false in default.
* Add unit tests for dataset format_results.
* Fix some comments and bc-breaking bug.
* Fix pre_eval set cfg field.
* Remove redundant codes.
Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>
* Add save_best option in eval_hook.
* Update meta to fix best model can not test bug
* refactor with _do_evaluate
* remove redundent
* add meta
Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>
* Fix fence(IoU) = 0 when training on PascalContextDataset59;
* Add a test case in test_metrics() of tests/test_metrics.py to test the bug caused by torch.histc;
* Update tests/test_metrics.py
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
* pytorch metrics impl and test
* support list[str] input, delete unused test code and delete numpy version
* modify input data type
* add docstring and unitest of filename inputs
* add indents in docstring and use tempfile lib to create dir
* using with statement
* add dice evaluation metric
* add dice evaluation metric
* add dice evaluation metric
* support 2 metrics
* support 2 metrics
* support 2 metrics
* support 2 metrics
* fix docstring
* use np.round once for all
* fix acc and iou compute nan problem
* fix acc and iou compute nan problem
* add nan_to_num args for mean_iou
* add nan_to_num args for mean_iou
* add nan_to_num args for mean_iou
* add nan_to_num args for mean_iou
* add nan_to_num args for mean_iou
* Update mmseg/core/evaluation/mean_iou.py
* Update mean_iou.py
* Update mean_iou.py
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>