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mot to csv for Blender

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davidpagnon 2023-10-18 18:53:06 +02:00
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148
Pose2Sim/Utilities/csv_from_mot_osim.py Normal file
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
##################################################
## Build csv from mot and osim files ##
##################################################
Build a csv file which stores locations and orientations of all bodies
calculated from a .mot motion file and a .osim model file.
Equivalent to OpenSim Analysis -> BodyKinematics but without the bugs in
orientations due to their use of Euler angle instead of homography matrices
Transforms from OpenSim's zup to Blender's yup
Usage:
from Pose2Sim.Utilities import csv_from_mot_osim; csv_from_mot_osim.csv_from_mot_osim_func(r'<input_mot_file>', r'<output_osim_file>', r'<output_csv_file>')
python -m csv_from_mot_osim -m input_mot_file -o input_osim_file
python -m csv_from_mot_osim -m input_mot_file -o input_osim_file -c output_csv_file
'''
## INIT
import os
import numpy as np
import opensim as osim
import argparse
direction = 'zup'
## AUTHORSHIP INFORMATION
__author__ = "David Pagnon, Jonathan Camargo"
__copyright__ = "Copyright 2023, BlendOSim & Sim2Blend"
__credits__ = ["David Pagnon", "Jonathan Camargo"]
__license__ = "MIT License"
__version__ = "0.0.1"
__maintainer__ = "David Pagnon"
__email__ = "contact@david-pagnon.com"
__status__ = "Development"
def csv_from_mot_osim_func(*args):
'''
Build a csv file which stores locations and orientations of all bodies
calculated from a .mot motion file and a .osim model file.
Equivalent to OpenSim Analysis -> BodyKinematics but without the bugs in
orientations due to their use of Euler angle instead of homography matrices
Usage:
from Pose2Sim.Utilities import csv_from_mot_osim; csv_from_mot_osim.csv_from_mot_osim_func(r'<input_mot_file>', r'<output_osim_file>', r'<output_csv_file>')
python -m csv_from_mot_osim -m input_mot_file -o input_osim_file
python -m csv_from_mot_osim -m input_mot_file -o input_osim_file -t output_csv_file
'''
try:
motion_path = args[0]['input_mot_file'] # invoked with argparse
osim_path = args[0]['input_osim_file']
if args[0]['csv_output_file'] == None:
output_csv_file = motion_path.replace('.mot', '.csv')
else:
output_csv_file = args[0]['csv_output_file']
except:
motion_path = args[0] # invoked as a function
osim_path = args[1]
try:
output_csv_file = args[2]
except:
output_csv_file = motion_path.replace('.mot', '.csv')
# Read model and motion files
model = osim.Model(input_osim_file)
motion_data = osim.TimeSeriesTable(input_mot_file)
# Model: get model coordinates and bodies
model_coordSet = model.getCoordinateSet()
coordinates = [model_coordSet.get(i) for i in range(model_coordSet.getSize())]
coordinateNames = [c.getName() for c in coordinates]
model_bodySet = model.getBodySet()
bodies = [model_bodySet.get(i) for i in range(model_bodySet.getSize())]
bodyNames = [b.getName() for b in bodies]
# Motion: read coordinates and convert to radians
times = motion_data.getIndependentColumn()
motion_data_np = motion_data.getMatrix().to_numpy()
for i in range(len(coordinates)):
if coordinates[i].getMotionType() == 1: # 1: rotation, 2: translation, 3: coupled
motion_data_np[:,i] = motion_data_np[:,i] * np.pi/180 # if rotation, convert to radians
# Animate model
state = model.initSystem()
loc_rot_frame_all = []
H_zup = np.array([[1,0,0,0], [0,0,-1,0], [0,1,0,0], [0,0,0,1]])
for n in range(motion_data.getNumRows()):
# Set model struct in each time state
for c, coord in enumerate(coordinateNames):
model.getCoordinateSet().get(coord).setValue(state, motion_data_np[n,c])
# Use state of model to get body coordinates in ground
loc_rot_frame = []
for b in bodies:
H_swig = b.getTransformInGround(state)
T = H_swig.T().to_numpy()
R_swig = H_swig.R()
R = np.array([[R_swig.get(0,0), R_swig.get(0,1), R_swig.get(0,2)],
[R_swig.get(1,0), R_swig.get(1,1), R_swig.get(1,2)],
[R_swig.get(2,0), R_swig.get(2,1), R_swig.get(2,2)]])
H = np.block([ [R,T.reshape(3,1)], [np.zeros(3), 1] ])
# y-up to z-up
if direction=='zup':
H = H_zup @ H
# Convert matrix to loc and rot, and export to csv
loc_x, loc_y, loc_z = H[0:3,3]
R_mat = H[0:3,0:3]
sy = np.sqrt(R_mat[1,0]**2 + R_mat[0,0]**2) # singularity when y angle is +/- pi/2
if sy>1e-6:
rot_x = np.arctan2(R_mat[2,1], R_mat[2,2])
rot_y = np.arctan2(-R_mat[2,0], sy)
rot_z = np.arctan2(R_mat[1,0], R_mat[0,0])
else: # to be verified
rot_x = np.arctan2(-R_mat[1,2], R_mat[1,1])
rot_y = np.arctan2(-R[2,0], sy)
rot_z = 0
loc_rot_frame.extend([loc_x, loc_y, loc_z, rot_x, rot_y, rot_z])
loc_rot_frame_all.append(loc_rot_frame)
# Export to csv
loc_rot_frame_all_np = np.array(loc_rot_frame_all)
loc_rot_frame_all_np = np.insert(loc_rot_frame_all_np, 0, times, axis=1) # insert time column
bodyHeader = 'times, ' + ''.join([f'{b}_x, {b}_y, {b}_z, {b}_rotx, {b}_roty, {b}_rotz, ' for b in bodyNames])[:-2]
np.savetxt(os.path.splitext(output_csv_file)[0]+'.csv', loc_rot_frame_all_np, delimiter=',', header=bodyHeader)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-m', '--input_mot_file', required = True, help='input mot file')
parser.add_argument('-o', '--input_osim_file', required = True, help='input osim file')
parser.add_argument('-c', '--csv_output_file', required=False, help='csv output file')
args = vars(parser.parse_args())
csv_from_mot_osim_func(args)

24
README.md
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@ -708,7 +708,7 @@ A list of standalone tools (see [Utilities](https://github.com/perfanalytics/pos
<details>
<summary><b>Converting files and Calibrating</b> (CLICK TO SHOW)</summary>
<summary><b>Converting calibration files</b> (CLICK TO SHOW)</summary>
<pre>
[Blazepose_runsave.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/Blazepose_runsave.py)
@ -720,9 +720,6 @@ Converts a DeepLabCut (h5) 2D pose estimation file into OpenPose (json) files.
[AlphaPose_to_OpenPose.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/AlphaPose_to_OpenPose.py)
Converts AlphaPose single json file to OpenPose frame-by-frame files.
[c3d_to_trc.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/c3d_to_trc.py)
Converts 3D point data of a .c3d file to a .trc file compatible with OpenSim. No analog data (force plates, emg) nor computed data (angles, powers, etc) are retrieved.
[calib_from_checkerboard.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/calib_from_checkerboard.py)
Calibrates cameras with images or a video of a checkerboard, saves calibration in a Pose2Sim .toml calibration file.
You should probably use Pose2Sim.calibration() instead, which is much easier and better.
@ -736,8 +733,14 @@ Converts a Pose2Sim .toml calibration file (e.g., from a checkerboard) to a Qual
[calib_easymocap_to_toml.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/calib_easymocap_to_toml.py)
Converts EasyMocap intrinsic and extrinsic .yml calibration files to an OpenCV .toml calibration file.
[calib_easymocap_to_yml.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/calib_toml_to_easymocap.py)
[calib_toml_to_easymocap.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/calib_toml_to_easymocap.py)
Converts an OpenCV .toml calibration file to EasyMocap intrinsic and extrinsic .yml calibration files.
[calib_toml_to_opencap.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/calib_toml_to_opencap.py)
Converts an OpenCV .toml calibration file to OpenCap .pickle calibration files.
[calib_toml_to_opencap.py]( )
To convert OpenCap calibration tiles to a .toml file, please use Pose2Sim.calibration() and set convert_from = 'opencap' in Config.toml.
</pre>
</details>
@ -759,7 +762,10 @@ Displays X, Y, Z coordinates of each 3D keypoint of a TRC file in a different ma
<details>
<summary><b>Other trc tools</b> (CLICK TO SHOW)</summary>
<pre>
[c3d_to_trc.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/c3d_to_trc.py)
Converts 3D point data of a .c3d file to a .trc file compatible with OpenSim. No analog data (force plates, emg) nor computed data (angles, powers, etc) are retrieved.
[trc_desample.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/trc_desample.py)
Undersamples a trc file.
@ -767,7 +773,7 @@ Undersamples a trc file.
Changes Z-up system coordinates to Y-up system coordinates.
[trc_filter.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/trc_filter.py)
Filters trc files. Available filters: Butterworth, Butterworth on speed, Gaussian, LOESS, Median.
Filters trc files. Available filters: Butterworth, Kalman, Butterworth on speed, Gaussian, LOESS, Median.
[trc_gaitevents.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/trc_gaitevents.py)
Detects gait events from point coordinates according to [Zeni et al. (2008)](https://www.sciencedirect.com/science/article/abs/pii/S0966636207001804?via%3Dihub).
@ -777,6 +783,10 @@ Combine two trc files, for example a triangulated DeepLabCut trc file and a tria
[trc_from_mot_osim.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/trc_from_mot_osim.py)
Build a trc file from a .mot motion file and a .osim model file.
[csv_from_mot_osim.py](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Utilities/csv_from_mot_osim.py)
Converts a mot file to a .csv file with rotation and orientation of all segments.
</pre>
</details>