--- a
+++ b/app/resources/pymo/README.md
@@ -0,0 +1,156 @@
+# PyMO
+A library for using motion capture data for machine learning
+
+**This library is currently highly experimental and everything is subject to change :)**
+
+
+## Roadmap
+* Mocap Data Parsers and Writers
+* Common mocap pre-processing algorithms
+* Feature extraction library
+* Visualization tools
+
+## Current Features
+* [Read BVH Files](#read-bvh-files)
+* Write BVH Files
+* Pre-processing pipelines
+    * [Supporting `scikit-learn` API](#scikit-learn-pipeline-api)
+    * Convert data representations 
+        * [Euler angles to positions](#convert-to-positions)
+        * Euler angles to exponential maps
+        * Exponential maps to euler angles
+    * Body-oriented global translation and rotation calculation with inverse tranform
+    * Root-centric position normalizer with inverse tranform
+    * Standard scaler
+    * Joint selectors        
+* Visualization tools
+    * [Skeleton hierarchy](#get-skeleton-info)
+    * [2D frame visualization](#visualize-a-single-2d-frame)
+    * [3D webgl-based animation](#animate-in-3d-inside-a-jupyter-notebook)
+* Annotations
+    * Foot/ground contact detector
+
+
+
+### Read BVH Files
+
+```python
+from pymo.parsers import BVHParser
+import pymo.viz_tools
+
+parser = BVHParser()
+
+parsed_data = parser.parse('data/AV_8Walk_Meredith_HVHA_Rep1.bvh')
+```
+
+### Get Skeleton Info
+
+```python
+import pymo.viz_tools
+
+viz_tools.print_skel(parsed_data)
+```
+Will print the skeleton hierarchy:
+```
+- Hips (None)
+| | - RightUpLeg (Hips)
+| | - RightLeg (RightUpLeg)
+| | - RightFoot (RightLeg)
+| | - RightToeBase (RightFoot)
+| | - RightToeBase_Nub (RightToeBase)
+| - LeftUpLeg (Hips)
+| - LeftLeg (LeftUpLeg)
+| - LeftFoot (LeftLeg)
+| - LeftToeBase (LeftFoot)
+| - LeftToeBase_Nub (LeftToeBase)
+- Spine (Hips)
+| | - RightShoulder (Spine)
+| | - RightArm (RightShoulder)
+| | - RightForeArm (RightArm)
+| | - RightHand (RightForeArm)
+| | | - RightHand_End (RightHand)
+| | | - RightHand_End_Nub (RightHand_End)
+| | - RightHandThumb1 (RightHand)
+| | - RightHandThumb1_Nub (RightHandThumb1)
+| - LeftShoulder (Spine)
+| - LeftArm (LeftShoulder)
+| - LeftForeArm (LeftArm)
+| - LeftHand (LeftForeArm)
+| | - LeftHand_End (LeftHand)
+| | - LeftHand_End_Nub (LeftHand_End)
+| - LeftHandThumb1 (LeftHand)
+| - LeftHandThumb1_Nub (LeftHandThumb1)
+- Head (Spine)
+- Head_Nub (Head)
+```
+
+
+### scikit-learn Pipeline API
+
+```python
+data_pipe = Pipeline([
+    ('rcpn', RootCentricPositionNormalizer()),
+    ('delta', RootTransformer('abdolute_translation_deltas')),
+    ('const', ConstantsRemover()),
+    ('np', Numpyfier()),
+    ('down', DownSampler(2)),
+    ('stdscale', ListStandardScaler())
+])
+
+piped_data = data_pipe.fit_transform(train_X)
+```
+
+### Convert to Positions
+
+```python
+mp = MocapParameterizer('positions')
+
+positions = mp.fit_transform([parsed_data])
+```
+
+### Visualize a single 2D Frame
+
+```python
+draw_stickfigure(positions[0], frame=10)
+```
+
+![2D Skeleton Viz](assets/viz_skel_2d.png)
+
+### Animate in 3D (inside a Jupyter Notebook)
+
+```python
+nb_play_mocap(positions[0], 'pos', 
+              scale=2, camera_z=800, frame_time=1/120, 
+              base_url='../pymo/mocapplayer/playBuffer.html')
+```
+
+![Mocap Player](assets/mocap_player.png)
+
+
+### Foot/Ground Contact Detector
+```python
+from pymo.features import *
+
+plot_foot_up_down(positions[0], 'RightFoot_Yposition')
+```
+
+![Foot Contact](assets/foot_updown.png)
+
+```python
+signal = create_foot_contact_signal(pos_data[3], 'RightFoot_Yposition')
+plt.figure(figsize=(12,5))
+plt.plot(signal, 'r')
+plt.plot(pos_data[3].values['RightFoot_Yposition'].values, 'g')
+```
+
+![Foot Contact Signal](assets/footcontact_signal.png)
+
+## Feedback, Bugs, and Questions
+For any questions, feedback, and bug reports, please use the [Github Issues](https://github.com/omimo/PyMO/issues).
+
+## Credits
+Created by [Omid Alemi](https://omid.al/projects/)
+
+
+## License
+This code is available under the [MIT license](http://opensource.org/licenses/MIT).