* 1.fix error with 4 channels of image of fom predictor. 2.fix error of fom evaluate 3.fix lapstyle vgg network

* add LapStyle Model

* test

* add training od first order motion

* Modify codes according to reviews

* Modify codes according to reviews

* (1)modify single person and multi person process of fom model. (2)git rid of sklearn, skimage

* modify documents of fom

* modify review code

* modify review code

* modify review code

* 1.add vox training; 2.fix attributed error for DataParallel. 3.fix fom fps

* add training od first order motion
* Modify codes according to reviews
* modify single person and multi person process of fom model. 
* Git rid of sklearn, skimage

* add edvr model

* modifying code formats and comments

* modifying code formats and comments

* modifying code formats and comments

* add notes
Co-authored-by: NLielinJiang <50691816+LielinJiang@users.noreply.github.com>

* add configuration options
e.g. python tools/main.py --c configs/stylegan_v2_256_ffhq.yaml -o total_iters=1 log_config.visiual_interval=1

* add stargan-v2 test and train code

* code normalization

* modify FAN code

* add munch in requirements.txt

* fix bugs

* fix 2.0-beta bugs

* update pretreained path

* add extract_weight.py

* adapt animegan

* clean code
Co-authored-by: Nqingqing01 <dangqingqing@baidu.com>

* add drn model

* add stylegan model

* add wav2lip trainning code

* add realsr model

* fix some bugs

* update configs

* add lesrcnn model

* Add photo2cartoon model
* Resolve conflicts
* Remove comments
* Add photo2cartoon tutorial
* update p2c tutorials

* add esrgan model, refine codes

* add some custom gan models

* add animeganv2 network and dataset
* animegan:refine code,add License
Co-authored-by: Nqingqing01 <dangqingqing@baidu.com>

* add ugatit model

* docs: update install instruction

1. paddlepaddle2.0.0rc instruction can be found from main page
2. only two steps, install paddlepaddle and paddlegan, other than 3step

* docs: update en install
* feat: add dcgan
* reform: debug with mnist datset
validate performance with different options, and original structure and setting

* refine codes docs

* fix pix2pix to_tensor

* fix apps

* add video restore tutorial

* refine code

* test

* fix apps

* update readme

* rm unused code

* fix apps output when input is image

* clean code

* update requirements.txt