* 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