# EasyMocap Doc - Output [En](Output) | [中文](#输出) ## Contents 1. [Json Format](#json-format) 2. [Export to .bvh](#export-to-bvh-format) ## Json Format The results are saved in `json` format. ```bash ├── keypoints3d │   ├── 000000.json │   └── xxxxxx.json └── smpl    ├── 000000.jpg    ├── 000000.json    └── 000004.json ``` The data in `keypoints3d/000000.json` is a list, each element represents a human body. ```bash { 'id': , # the person ID 'keypoints3d': [[x0, y0, z0, c0], [x1, y1, z0, c1], ..., [xn, yn, zn, cn]], # x,y,z is the 3D coordinates, c means the confidence of this joint. If the c=0, it means this joint is invisible. } ``` The definition of the joints is as [body25](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/02_output.md#pose-output-format-body_25). The data in `smpl/000000.json` is also a list, each element represents the SMPL parameters which is slightly different from official model. ```bash { "id": , "Rh": <(1, 3)>, "Th": <(1, 3)>, "poses": <(1, 72/78/87)>, "expression": <(1, 10)>, "shapes": <(1, 10)> } ``` If you use SMPL+H model, the poses contains `22x3+6+6`. We use `6` pca coefficients for each hand. `3(jaw, left eye, right eye)x3` poses of head are added for SMPL-X model. ### Attention (for SMPL/SMPL-X users) **This parameter is a little different from original SMPL/SMPL-X parameters.** We set the first 3 dimensions of `poses` to zero, and add a new parameter `Rh` to represents the global oritentation, the vertices of SMPL model V = RX(theta, beta) + T. Please note that the paramter `Rh` is not equal to `global_orient` in SMPL-X model. We take this representation because that changing paramters to new coordinate system in origin is difficult(see [this link](https://www.dropbox.com/scl/fi/zkatuv5shs8d4tlwr8ecc/Change-parameters-to-new-coordinate-system.paper?dl=0&rlkey=lotq1sh6wzkmyttisc05h0in0)). In our representation, you can just use `R'@(RX + T) + T'` to convert the model, and the new global rotaion and translation is simply written as `R'@R` and `R'@T + T'` To compute the joints locations from these parameters, please refer to `./code/vis_render.py`. The key steps are: ```python # 0. load SMPL model from smplmodel import load_model body_model = load_model(args.gender, model_type=args.model) # 1. load parameters infos = dataset.read_smpl(nf*step) # 2. compute joints joints = body_model(return_verts=False, return_tensor=False, **info)[0] # 3. compute vertices vertices = body_model(return_verts=True, return_tensor=False, **info)[0] ``` ## Export to bvh format To export the SMPL results to bvh file, you need to download the SMPL-maya model from the website of SMPL. Place the `.fbx` model in `./data/smplx/SMPL_maya`, it may be like this: ```bash └── smplx ├── smpl │   ├── SMPL_FEMALE.pkl │   ├── SMPL_MALE.pkl │   └── SMPL_NEUTRAL.pkl ├── SMPL_maya │   ├── basicModel_f_lbs_10_207_0_v1.0.2.fbx │   ├── basicModel_m_lbs_10_207_0_v1.0.2.fbx │   ├── joints_mat_v1.0.2.pkl │   ├── README.txt │   ├── release_notes_v1.0.2.txt │   └── SMPL_maya_plugin_v1.0.2.py └── smplx ``` The Blender is also needed. The `` is usually `${out}/smpl`, which contanis the `000000.json, ...` of SMPL parameters. ```bash BLENDER_PATH=/blender-2.79a-linux-glibc219-x86_64 ${BLENDER_PATH}/blender -b -t 12 -P scripts/postprocess/convert2bvh.py -- --o ``` We have not implement the export of SMPL+H, SMPL-X model yet. If you are interested on it, feel free to create a pull request to us. ----- # 输出 ## Json格式 关键点重建的结果会输出到`${out}/keypoints3d`路径下 ```bash ├── keypoints3d │ ├── 000000.json │ └── xxxxxx.json └── skel ``` 每个json里面是一个列表，包含了当前帧的所有人，列表里的每一个元素表示一个人，内容如下： ```json { 'id': , # 表示人的跟踪的id 'keypoints3d': [[x0, y0, z0, c0], [x1, y1, z0, c1], ..., [xn, yn, zn, cn]]: # (N, 4)，表示人的关键点坐标，c表示置信度，置信度为0则该关节点不可见 } ``` 关键点的定义使用OpenPose的[BODY25格式](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/02_output.md#pose-output-format-body_25) ## 导出为bvh格式 这里使用Blender进行导出，测试的Blender版本为2.79。需要先下载SMPL的fbx模型 ```bash BLENDER_PATH=/blender-2.79a-linux-glibc219-x86_64 ${BLENDER_PATH}/blender -b -t 12 -P scripts/postprocess/convert2bvh.py -- --o ```