fixed multi_person + differenciates X,Y,Z in scaling
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davidpagnon
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b793ad1c7c
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6f7e883cd3
@ -179,7 +179,7 @@ make_c3d = true # also save triangulated data in c3d format
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make_c3d = true # save triangulated data in c3d format in addition to trc
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[opensim]
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[kinematics]
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use_augmentation = true # true or false (lowercase) # Set to true if you want to use the model with augmented markers
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right_left_symmetry = true # true or false (lowercase) # Set to false only if you have good reasons to think the participant is not symmetrical (e.g. prosthetic limb)
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remove_individual_scaling_setup = true # true or false (lowercase) # If true, the individual scaling setup files are removed to avoid cluttering
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@ -179,7 +179,7 @@
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# make_c3d = false # save triangulated data in c3d format in addition to trc
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# [opensim]
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# [kinematics]
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# use_augmentation = true # true or false (lowercase) # Set to true if you want to use the model with augmented markers
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# right_left_symmetry = true # true or false (lowercase) # Set to false only if you have good reasons to think the participant is not symmetrical (e.g. prosthetic limb)
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# remove_individual_scaling_setup = true # true or false (lowercase) # If true, the individual scaling setup files are removed to avoid cluttering
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@ -179,7 +179,7 @@ keypoints_to_consider = 'all' # 'all' if all points should be considered, for ex
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# make_c3d = false # save triangulated data in c3d format in addition to trc
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# [opensim]
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# [kinematics]
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# use_augmentation = true # true or false (lowercase) # Set to true if you want to use the model with augmented markers
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# right_left_symmetry = true # true or false (lowercase) # Set to false only if you have good reasons to think the participant is not symmetrical (e.g. prosthetic limb)
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# remove_individual_scaling_setup = true # true or false (lowercase) # If true, the individual scaling setup files are removed to avoid cluttering
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@ -179,7 +179,7 @@ make_c3d = false # also save triangulated data in c3d format
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make_c3d = true # save triangulated data in c3d format in addition to trc
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[opensim]
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[kinematics]
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use_augmentation = true # true or false (lowercase) # Set to true if you want to use the model with augmented markers
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right_left_symmetry = true # true or false (lowercase) # Set to false only if you have good reasons to think the participant is not symmetrical (e.g. prosthetic limb)
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remove_individual_scaling_setup = true # true or false (lowercase) # If true, the individual scaling setup files are removed to avoid cluttering
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@ -217,7 +217,7 @@ def poseEstimation(config=None):
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config_dict.get("project").update({"project_dir":"<YOUR_TRIAL_DIRECTORY>"})')
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# Set up logging
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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# Batch process all trials
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@ -264,7 +264,7 @@ def synchronization(config=None):
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config_dict.get("project").update({"project_dir":"<YOUR_TRIAL_DIRECTORY>"})')
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# Set up logging
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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# Batch process all trials
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@ -296,7 +296,7 @@ def personAssociation(config=None):
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or the function can be called without an argument, in which case it the config directory is the current one.
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'''
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from Pose2Sim.personAssociation import track_2d_all
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from Pose2Sim.personAssociation import associate_all
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# Determine the level at which the function is called (root:2, trial:1)
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level, config_dicts = read_config_files(config)
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@ -308,7 +308,7 @@ def personAssociation(config=None):
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config_dict.get("project").update({"project_dir":"<YOUR_TRIAL_DIRECTORY>"})')
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# Set up logging
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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# Batch process all trials
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@ -326,7 +326,7 @@ def personAssociation(config=None):
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logging.info(f"Project directory: {project_dir}")
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logging.info("---------------------------------------------------------------------\n")
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track_2d_all(config_dict)
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associate_all(config_dict)
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end = time.time()
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elapsed = end-start
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@ -354,7 +354,7 @@ def triangulation(config=None):
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config_dict.get("project").update({"project_dir":"<YOUR_TRIAL_DIRECTORY>"})')
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# Set up logging
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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# Batch process all trials
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@ -400,7 +400,7 @@ def filtering(config=None):
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config_dict.get("project").update({"project_dir":"<YOUR_TRIAL_DIRECTORY>"})')
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# Set up logging
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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# Batch process all trials
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@ -441,7 +441,7 @@ def markerAugmentation(config=None):
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raise ValueError('Please specify the project directory in config_dict:\n \
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config_dict.get("project").update({"project_dir":"<YOUR_TRIAL_DIRECTORY>"})')
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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for config_dict in config_dicts:
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@ -485,7 +485,7 @@ def kinematics(config=None):
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raise ValueError('Please specify the project directory in config_dict:\n \
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config_dict.get("project").update({"project_dir":"<YOUR_TRIAL_DIRECTORY>"})')
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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# Process each configuration dictionary
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@ -519,7 +519,7 @@ def runAll(config=None, do_calibration=True, do_poseEstimation=True, do_synchron
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# Set up logging
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level, config_dicts = read_config_files(config)
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..'))
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session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '.'))
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setup_logging(session_dir)
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currentDateAndTime = datetime.now()
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@ -275,7 +275,7 @@ def dict_segment_marker_pairs(scaling_root, right_left_symmetry=True):
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'''
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measurement_dict = {}
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segment_markers_dict = {}
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for measurement in scaling_root.findall(".//Measurement"):
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# Collect all marker pairs for this measurement
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marker_pairs = [pair.find('markers').text.strip().split() for pair in measurement.findall(".//MarkerPair")]
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@ -283,17 +283,22 @@ def dict_segment_marker_pairs(scaling_root, right_left_symmetry=True):
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# Collect all body scales for this measurement
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for body_scale in measurement.findall(".//BodyScale"):
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body_name = body_scale.get('name')
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if right_left_symmetry:
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measurement_dict[body_name] = marker_pairs
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else:
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if body_name.endswith('_r'):
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marker_pairs_r = [pair for pair in marker_pairs if any([pair[0].startswith('R'), pair[1].startswith('R')])]
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measurement_dict[body_name] = marker_pairs_r
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elif body_name.endswith('_l'):
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marker_pairs_l = [pair for pair in marker_pairs if any([pair[0].startswith('L'), pair[1].startswith('L')])]
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measurement_dict[body_name] = marker_pairs_l
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axes = body_scale.find('axes').text.strip().split()
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for axis in axes:
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body_name_axis = f"{body_name}_{axis}"
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if right_left_symmetry:
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segment_markers_dict.setdefault(body_name_axis, []).extend(marker_pairs)
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else:
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if body_name.endswith('_r'):
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marker_pairs_r = [pair for pair in marker_pairs if any([pair[0].upper().startswith('R'), pair[1].upper().startswith('R')])]
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segment_markers_dict.setdefault(body_name_axis, []).extend(marker_pairs_r)
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elif body_name.endswith('_l'):
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marker_pairs_l = [pair for pair in marker_pairs if any([pair[0].upper().startswith('L'), pair[1].upper().startswith('L')])]
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segment_markers_dict.setdefault(body_name_axis, []).extend(marker_pairs_l)
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else:
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segment_markers_dict.setdefault(body_name_axis, []).extend(marker_pairs)
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return measurement_dict
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return segment_markers_dict
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def dict_segment_ratio(scaling_root, unscaled_model, Q_coords_scaling, markers, right_left_symmetry=True):
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@ -321,10 +326,15 @@ def dict_segment_ratio(scaling_root, unscaled_model, Q_coords_scaling, markers,
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# Calculate ratio for each segment
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segment_ratios = trc_segment_lengths / model_segment_lengths
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segment_markers_dict = dict_segment_marker_pairs(scaling_root, right_left_symmetry=right_left_symmetry)
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segment_ratio_dict = segment_markers_dict.copy()
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segment_ratio_dict.update({key: np.mean([segment_ratios[segment_pairs.index(k)]
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segment_ratio_dict_temp = segment_markers_dict.copy()
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segment_ratio_dict_temp.update({key: np.mean([segment_ratios[segment_pairs.index(k)]
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for k in segment_markers_dict[key]])
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for key in segment_markers_dict.keys()})
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# Merge X, Y, Z ratios into single key
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segment_ratio_dict={}
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xyz_keys = list(set([key[:-2] for key in segment_ratio_dict_temp.keys()]))
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for key in xyz_keys:
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segment_ratio_dict[key] = [segment_ratio_dict_temp[key+'_X'], segment_ratio_dict_temp[key+'_Y'], segment_ratio_dict_temp[key+'_Z']]
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return segment_ratio_dict
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@ -351,11 +361,11 @@ def update_scale_values(scaling_root, segment_ratio_dict):
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scale_set.remove(scale)
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# Add new Scale elements based on scale_dict
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for segment, scale in segment_ratio_dict.items():
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for segment, scales in segment_ratio_dict.items():
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new_scale = etree.Element('Scale')
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# scales
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scales_elem = etree.SubElement(new_scale, 'scales')
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scales_elem.text = ' '.join([str(scale)]*3)
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scales_elem.text = ' '.join(map(str, scales))
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# segment name
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segment_elem = etree.SubElement(new_scale, 'segment')
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segment_elem.text = segment
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@ -394,7 +404,7 @@ def perform_scaling(trc_file, kinematics_dir, osim_setup_dir, model_name, right_
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scaling_path = get_scaling_setup(model_name, osim_setup_dir)
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scaling_tree = etree.parse(scaling_path)
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scaling_root = scaling_tree.getroot()
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scaling_path_temp = str(kinematics_dir / Path(scaling_path).name)
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scaling_path_temp = str(kinematics_dir / (trc_file.stem + '_scaling_setup.xml'))
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# Read trc file
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Q_coords, _, _, markers, _ = read_trc(trc_file)
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@ -415,8 +425,7 @@ def perform_scaling(trc_file, kinematics_dir, osim_setup_dir, model_name, right_
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scaling_root[0].find(".//scaling_order").text = ' manualScale measurements'
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deactivate_measurements(scaling_root)
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update_scale_values(scaling_root, segment_ratio_dict)
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for mk_f in scaling_root[0].findall(".//marker_file"):
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mk_f.text = "Unassigned"
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for mk_f in scaling_root[0].findall(".//marker_file"): mk_f.text = "Unassigned"
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scaling_root[0].find('ModelScaler').find('output_model_file').text = str(scaled_model_path)
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etree.indent(scaling_tree, space='\t', level=0)
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@ -448,7 +457,7 @@ def perform_IK(trc_file, kinematics_dir, osim_setup_dir, model_name, remove_IK_s
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try:
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# Retrieve data
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ik_path = get_IK_Setup(model_name, osim_setup_dir)
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ik_path_temp = str(kinematics_dir / Path(ik_path).name)
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ik_path_temp = str(kinematics_dir / (trc_file.stem + '_ik_setup.xml'))
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scaled_model_path = (kinematics_dir / (trc_file.stem + '.osim')).resolve()
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output_motion_file = Path(kinematics_dir, trc_file.stem + '.mot').resolve()
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if not trc_file.exists():
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@ -546,7 +555,7 @@ def kinematics(config_dict):
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elif not type(subject_mass) == list:
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subject_mass = [subject_mass]
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elif len(subject_mass) < len(trc_files):
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logging.warning("Number of subject masses does not match number of TRC files. Missing masses are set to 70kg.")
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logging.warning("Number of subject masses does not match number of TRC files. Missing masses are set to 70kg.\n")
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subject_mass += [70] * (len(trc_files) - len(subject_mass))
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# Perform scaling and IK for each trc file
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@ -558,7 +567,7 @@ def kinematics(config_dict):
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logging.info(f"\tDone. OpenSim logs saved to {opensim_logs_file.resolve()}.")
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logging.info(f"\tScaled model saved to {(kinematics_dir / (trc_file.stem + '_scaled.osim')).resolve()}")
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logging.info("\nInverse Kinematics...")
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logging.info("Inverse Kinematics...")
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perform_IK(trc_file, kinematics_dir, osim_setup_dir, model_name, remove_IK_setup=remove_IK_setup)
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logging.info(f"\tDone. OpenSim logs saved to {opensim_logs_file.resolve()}.")
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logging.info(f"\tJoint angle data saved to {(kinematics_dir / (trc_file.stem + '.mot')).resolve()}\n")
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@ -604,7 +604,7 @@ def recap_tracking(config_dict, error=0, nb_cams_excluded=0):
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logging.info(f'\nTracked json files are stored in {os.path.realpath(poseTracked_dir)}.')
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def track_2d_all(config_dict):
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def associate_all(config_dict):
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'''
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For each frame,
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- Find all possible combinations of detected persons
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@ -191,6 +191,7 @@ def sort_people(Q_kpt_old, Q_kpt):
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frame_by_frame_dist = []
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for comb in personsIDs_comb:
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frame_by_frame_dist += [euclidean_distance(Q_kpt_old[comb[0]],Q_kpt[comb[1]])]
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frame_by_frame_dist = np.mean(frame_by_frame_dist, axis=1)
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# sort correspondences by distance
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minL, _, associated_tuples = min_with_single_indices(frame_by_frame_dist, personsIDs_comb)
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