* add cn tutorials/config.md
* add heads api and doc title link
* Update tutorials index
* Update tutorials index
* Update config.md
* add english version
* Update config.md
* add custom_runtime
* Update docs
* modify title
* modify en to zh_CN in chinses docs
* Update Readme
* fix punctuations
* Update docs/tutorials/customize_runtime.md
Co-authored-by: Ma Zerun <mzr1996@163.com>
* Update docs/tutorials/customize_runtime.md
Co-authored-by: Ma Zerun <mzr1996@163.com>
* split to schedule and runtime
* fix lint
* improve docs after review
* fix TOC
* imporve expersion
* fix an error
* Imporve schedule.md
* Improve runtime.md
* Improve chinese docs.
* Fix toc-tree
* fix en link and add a case of gradient clipping
* fix wrong word
Co-authored-by: Ma Zerun <mzr1996@163.com>
* Disable auto line-wrap in docs.
* Add model_zoo.md and CONTRIBUTING.md in docs.
* Revise getting_started.md and install.md
* Rewrite finetune.md
* Fix typo
* Imporve `finetune.md`
* Fix `GitHub` link
* Fix a small typo.
* Add Citation in README
Add Citation and mmgeneration in README
* Merge inference and test section in getting_start.md and other small chagne.
* Fix code type in install.md
* Add Chinese Readme
* README and docs improvement.
* 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