Diff-TTSG / pymo /parsers_new.py
Shivam Mehta
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"""
BVH Parser Class
By Omid Alemi
Created: June 12, 2017
Based on: https://gist.github.com/johnfredcee/2007503
"""
import os
import re
import numpy as np
from pymo.data import Joint, MocapData
class BVHScanner:
"""
A wrapper class for re.Scanner
"""
def __init__(self):
def identifier(scanner, token):
return "IDENT", token
def operator(scanner, token):
return "OPERATOR", token
def digit(scanner, token):
return "DIGIT", token
def open_brace(scanner, token):
return "OPEN_BRACE", token
def close_brace(scanner, token):
return "CLOSE_BRACE", token
self.scanner = re.Scanner(
[
(r"[a-zA-Z_]\w*", identifier),
# (r'-*[0-9]+(\.[0-9]+)?', digit), # won't work for .34
# (r'[-+]?[0-9]*\.?[0-9]+', digit), # won't work for 4.56e-2
# (r'[-+]?[0-9]*\.?[0-9]+([eE][-+]?[0-9]+)?', digit),
(r"-*[0-9]*\.?[0-9]+([eE][-+]?[0-9]+)?", digit),
(r"}", close_brace),
(r"}", close_brace),
(r"{", open_brace),
(r":", None),
(r"\s+", None),
]
)
def scan(self, stuff):
return self.scanner.scan(stuff)
class BVHParser:
"""
A class to parse a BVH file.
Extracts the skeleton and channel values
"""
def __init__(self, filename=None):
self.reset()
def reset(self):
self._skeleton = {}
self.bone_context = []
self._motion_channels = []
self._motions = []
self.current_token = 0
self.framerate = 0.0
self.root_name = ""
self.scanner = BVHScanner()
self.data = MocapData()
def parse(self, filename, start=0, stop=-1):
self.reset()
with open(filename) as bvh_file:
raw_contents = bvh_file.read()
tokens, remainder = self.scanner.scan(raw_contents)
self._parse_hierarchy(tokens)
self.current_token = self.current_token + 1
self._parse_motion(tokens, start, stop)
self.data.skeleton = self._skeleton
self.data.channel_names = self._motion_channels
self.data.values = self._to_DataFrame()
self.data.root_name = self.root_name
self.data.framerate = self.framerate
self.data.take_name = os.path.basename(os.path.splitext(filename)[0])
return self.data
def _to_DataFrame(self):
"""Returns all of the channels parsed from the file as a pandas DataFrame"""
import pandas as pd
time_index = pd.to_timedelta([f[0] for f in self._motions], unit="s")
frames = [f[1] for f in self._motions]
channels = np.asarray([[channel[2] for channel in frame] for frame in frames])
column_names = ["%s_%s" % (c[0], c[1]) for c in self._motion_channels]
return pd.DataFrame(data=channels, index=time_index, columns=column_names)
def _new_bone(self, parent, name):
bone = {"parent": parent, "channels": [], "offsets": [], "order": "", "children": []}
return bone
def _push_bone_context(self, name):
self.bone_context.append(name)
def _get_bone_context(self):
return self.bone_context[len(self.bone_context) - 1]
def _pop_bone_context(self):
self.bone_context = self.bone_context[:-1]
return self.bone_context[len(self.bone_context) - 1]
def _read_offset(self, bvh, token_index):
if bvh[token_index] != ("IDENT", "OFFSET"):
return None, None
token_index = token_index + 1
offsets = [0.0] * 3
for i in range(3):
offsets[i] = float(bvh[token_index][1])
token_index = token_index + 1
return offsets, token_index
def _read_channels(self, bvh, token_index):
if bvh[token_index] != ("IDENT", "CHANNELS"):
return None, None
token_index = token_index + 1
channel_count = int(bvh[token_index][1])
token_index = token_index + 1
channels = [""] * channel_count
order = ""
for i in range(channel_count):
channels[i] = bvh[token_index][1]
token_index = token_index + 1
if channels[i] == "Xrotation" or channels[i] == "Yrotation" or channels[i] == "Zrotation":
order += channels[i][0]
else:
order = ""
return channels, token_index, order
def _parse_joint(self, bvh, token_index):
end_site = False
joint_id = bvh[token_index][1]
token_index = token_index + 1
joint_name = bvh[token_index][1]
token_index = token_index + 1
parent_name = self._get_bone_context()
if joint_id == "End":
joint_name = parent_name + "_Nub"
end_site = True
joint = self._new_bone(parent_name, joint_name)
if bvh[token_index][0] != "OPEN_BRACE":
print("Was expecting brance, got ", bvh[token_index])
return None
token_index = token_index + 1
offsets, token_index = self._read_offset(bvh, token_index)
joint["offsets"] = offsets
if not end_site:
channels, token_index, order = self._read_channels(bvh, token_index)
joint["channels"] = channels
joint["order"] = order
for channel in channels:
self._motion_channels.append((joint_name, channel))
self._skeleton[joint_name] = joint
self._skeleton[parent_name]["children"].append(joint_name)
while (bvh[token_index][0] == "IDENT" and bvh[token_index][1] == "JOINT") or (
bvh[token_index][0] == "IDENT" and bvh[token_index][1] == "End"
):
self._push_bone_context(joint_name)
token_index = self._parse_joint(bvh, token_index)
self._pop_bone_context()
if bvh[token_index][0] == "CLOSE_BRACE":
return token_index + 1
print("Unexpected token ", bvh[token_index])
def _parse_hierarchy(self, bvh):
self.current_token = 0
if bvh[self.current_token] != ("IDENT", "HIERARCHY"):
return None
self.current_token = self.current_token + 1
if bvh[self.current_token] != ("IDENT", "ROOT"):
return None
self.current_token = self.current_token + 1
if bvh[self.current_token][0] != "IDENT":
return None
root_name = bvh[self.current_token][1]
root_bone = self._new_bone(None, root_name)
self.current_token = self.current_token + 2 # skipping open brace
offsets, self.current_token = self._read_offset(bvh, self.current_token)
channels, self.current_token, order = self._read_channels(bvh, self.current_token)
root_bone["offsets"] = offsets
root_bone["channels"] = channels
root_bone["order"] = order
self._skeleton[root_name] = root_bone
self._push_bone_context(root_name)
for channel in channels:
self._motion_channels.append((root_name, channel))
while bvh[self.current_token][1] == "JOINT":
self.current_token = self._parse_joint(bvh, self.current_token)
self.root_name = root_name
def _parse_motion(self, bvh, start, stop):
if bvh[self.current_token][0] != "IDENT":
print("Unexpected text")
return None
if bvh[self.current_token][1] != "MOTION":
print("No motion section")
return None
self.current_token = self.current_token + 1
if bvh[self.current_token][1] != "Frames":
return None
self.current_token = self.current_token + 1
frame_count = int(bvh[self.current_token][1])
if stop < 0 or stop > frame_count:
stop = frame_count
assert start >= 0
assert start < stop
self.current_token = self.current_token + 1
if bvh[self.current_token][1] != "Frame":
return None
self.current_token = self.current_token + 1
if bvh[self.current_token][1] != "Time":
return None
self.current_token = self.current_token + 1
frame_rate = float(bvh[self.current_token][1])
self.framerate = frame_rate
self.current_token = self.current_token + 1
frame_time = 0.0
self._motions = [()] * (stop - start)
idx = 0
for i in range(stop):
channel_values = []
for channel in self._motion_channels:
channel_values.append((channel[0], channel[1], float(bvh[self.current_token][1])))
self.current_token = self.current_token + 1
if i >= start:
self._motions[idx] = (frame_time, channel_values)
frame_time = frame_time + frame_rate
idx += 1