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utils.py
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utils.py
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import os
import numpy as np
import csv
import glob
import pandas as pd
from ast import literal_eval
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from matplotlib.animation import FFMpegWriter
from functools import partial
def est_to_pst(pst_h, pst_d):
est_hour = str((int(pst_h)-5)%24)
if int(est_hour) < 10:
est_hour = '0' + est_hour
if int(pst_h)<6:
est_day = '0' + str(int(pst_d)-1)
else:
est_day = pst_d
return est_hour, est_day
def listdir(path):
return glob.glob(os.path.join(path, '*'))
def create_df_from_hour(hourdir):
def create_df(file):
print(file)
raw_df = pd.read_csv(file)
f_df = pd.DataFrame(columns=keypoints)
for kp in keypoints:
f_df[kp] = literal_eval(raw_df[kp][0])
return f_df
data_files = listdir(hourdir)
data_files.sort()
df_full = create_df(data_files[0])
for f in data_files[1:]:
df_new = create_df(f)
df_full = pd.concat([df_full, df_new])
return df_full
def make_detailed_df(clean_coral_df):
for kp in keypoints:
clean_coral_df[kp] = clean_coral_df.apply(lambda row: [np.float(row[kp][0]),
np.float(row[kp][1]),
np.float(row[kp][2])],
axis=1)
clean_coral_df['FOOT'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_ANKLE[0] + 0.5*row.RIGHT_ANKLE[0],
0.5*row.LEFT_ANKLE[1] + 0.5*row.RIGHT_ANKLE[1]],
axis=1)
clean_coral_df['LEFT_SHANK'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_KNEE[0] + 0.5*row.LEFT_ANKLE[0],
0.5*row.LEFT_KNEE[1] + 0.5*row.LEFT_ANKLE[1]],
axis=1)
clean_coral_df['RIGHT_SHANK'] = clean_coral_df.apply(lambda row: [0.5*row.RIGHT_KNEE[0] + 0.5*row.RIGHT_ANKLE[0],
0.5*row.RIGHT_KNEE[1] + 0.5*row.RIGHT_ANKLE[1]],
axis=1)
clean_coral_df['SHANK'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_SHANK[0] + 0.5*row.RIGHT_SHANK[0],
0.5*row.LEFT_SHANK[1] + 0.5*row.RIGHT_SHANK[1]],
axis=1)
clean_coral_df['LEFT_THIGH'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_KNEE[0] + 0.5*row.LEFT_HIP[0],
0.5*row.LEFT_KNEE[1] + 0.5*row.LEFT_HIP[1]],
axis=1)
clean_coral_df['RIGHT_THIGH'] = clean_coral_df.apply(lambda row: [0.5*row.RIGHT_KNEE[0] + 0.5*row.RIGHT_HIP[0],
0.5*row.RIGHT_KNEE[1] + 0.5*row.RIGHT_HIP[1]],
axis=1)
clean_coral_df['THIGH'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_THIGH[0] + 0.5*row.RIGHT_THIGH[0],
0.5*row.LEFT_THIGH[1] + 0.5*row.RIGHT_THIGH[1]],
axis=1)
clean_coral_df['HAND'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_WRIST[0] + 0.5*row.RIGHT_WRIST[0],
0.5*row.LEFT_WRIST[1] + 0.5*row.RIGHT_WRIST[1]],
axis=1)
clean_coral_df['LEFT_FOREARM'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_WRIST[0] + 0.5*row.LEFT_ELBOW[0],
0.5*row.LEFT_WRIST[1] + 0.5*row.LEFT_ELBOW[1]],
axis=1)
clean_coral_df['RIGHT_FOREARM'] = clean_coral_df.apply(lambda row: [0.5*row.RIGHT_WRIST[0] + 0.5*row.RIGHT_ELBOW[0],
0.5*row.RIGHT_WRIST[1] + 0.5*row.RIGHT_ELBOW[1]],
axis=1)
clean_coral_df['FOREARM'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_WRIST[0] + 0.5*row.RIGHT_WRIST[0],
0.5*row.LEFT_WRIST[1] + 0.5*row.RIGHT_WRIST[1]],
axis=1)
clean_coral_df['LEFT_UPARM'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_SHOULDER[0] + 0.5*row.LEFT_ELBOW[0],
0.5*row.LEFT_SHOULDER[1] + 0.5*row.LEFT_ELBOW[1]],
axis=1)
clean_coral_df['RIGHT_UPARM'] = clean_coral_df.apply(lambda row: [0.5*row.RIGHT_SHOULDER[0] + 0.5*row.RIGHT_ELBOW[0],
0.5*row.RIGHT_SHOULDER[1] + 0.5*row.RIGHT_ELBOW[1]],
axis=1)
clean_coral_df['UPARM'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_UPARM[0] + 0.5*row.RIGHT_UPARM[0],
0.5*row.LEFT_UPARM[1] + 0.5*row.RIGHT_UPARM[1]],
axis=1)
clean_coral_df['PELVIS'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_HIP[0] + 0.5*row.RIGHT_HIP[0],
0.5*row.LEFT_HIP[1] + 0.5*row.RIGHT_HIP[1]],
axis=1)
clean_coral_df['LEFT_THORAX'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_SHOULDER[0] + 0.5*row.LEFT_HIP[0],
0.5*row.LEFT_SHOULDER[1] + 0.5*row.LEFT_HIP[1]],
axis=1)
clean_coral_df['RIGHT_THORAX'] = clean_coral_df.apply(lambda row: [0.5*row.RIGHT_SHOULDER[0] + 0.5*row.RIGHT_HIP[0],
0.5*row.RIGHT_SHOULDER[1] + 0.5*row.RIGHT_HIP[1]],
axis=1)
clean_coral_df['THORAX'] = clean_coral_df.apply(lambda row: [0.5*row.LEFT_THORAX[0] + 0.5*row.RIGHT_THORAX[0],
0.5*row.LEFT_THORAX[1] + 0.5*row.RIGHT_THORAX[1]],
axis=1)
clean_coral_df['HEAD'] = clean_coral_df['NOSE']
clean_coral_df['TRUNK'] = clean_coral_df['THORAX']
clean_coral_df['COM'] = clean_coral_df.apply(lambda row: [(1/1.286)*(0.0145*row.FOOT[0] +
0.0465*row.SHANK[0] +
0.10*row.THIGH[0] +
0.006*row.HAND[0] +
0.016*row.FOREARM[0] +
0.028*row.UPARM[0] +
0.142*row.PELVIS[0] +
0.355*row.THORAX[0] +
0.081*row.HEAD[0] +
0.497*row.TRUNK[0]),
(1/1.286)*(0.0145*row.FOOT[1] +
0.0465*row.SHANK[1] +
0.10*row.THIGH[1] +
0.006*row.HAND[1] +
0.016*row.FOREARM[1] +
0.028*row.UPARM[1] +
0.142*row.PELVIS[1] +
0.355*row.THORAX[1] +
0.081*row.HEAD[1] +
0.497*row.TRUNK[1])] , axis=1)
return clean_coral_df
def add_time(df):
df['time'] = df.apply(lambda row: row.NOSE[-1], axis=1)
df['time_int'] = df.apply(lambda row: int(row.time[:2])+ int(row.time[-5:-3])/60 + int(row.time[-2:])/6000, axis=1)
return df
keypoints = ['NOSE', 'LEFT_EYE', 'RIGHT_EYE', 'LEFT_EAR', 'RIGHT_EAR',
'LEFT_SHOULDER', 'RIGHT_SHOULDER', 'LEFT_ELBOW',
'RIGHT_ELBOW', 'LEFT_WRIST', 'RIGHT_WRIST', 'LEFT_HIP',
'RIGHT_HIP', 'LEFT_KNEE', 'RIGHT_KNEE', 'LEFT_ANKLE',
'RIGHT_ANKLE']
# indeces of keypoints between which we want to draw a line
num_edges = ((0, 1),(0, 2),(0, 3),(0, 4),(3, 1),(4, 2),
(1, 2),(5, 6),(5, 7),(5, 11),(6, 8),(6, 12),
(7, 9),(8, 10),(11, 12),(11, 13),(12, 14),
(13, 15),(14, 16),)
# same list but as keypoint names
EDGES = (
('NOSE', 'LEFT_EYE'),
('NOSE', 'RIGHT_EYE'),
('NOSE', 'LEFT_EAR'),
('NOSE', 'RIGHT_EAR'),
('LEFT_EAR', 'LEFT_EYE'),
('RIGHT_EAR', 'RIGHT_EYE'),
('LEFT_EYE', 'RIGHT_EYE'),
('LEFT_SHOULDER', 'RIGHT_SHOULDER'),
('LEFT_SHOULDER', 'LEFT_ELBOW'),
('LEFT_SHOULDER', 'LEFT_HIP'),
('RIGHT_SHOULDER', 'RIGHT_ELBOW'),
('RIGHT_SHOULDER', 'RIGHT_HIP'),
('LEFT_ELBOW', 'LEFT_WRIST'),
('RIGHT_ELBOW', 'RIGHT_WRIST'),
('LEFT_HIP', 'RIGHT_HIP'),
('LEFT_HIP', 'LEFT_KNEE'),
('RIGHT_HIP', 'RIGHT_KNEE'),
('LEFT_KNEE', 'LEFT_ANKLE'),
('RIGHT_KNEE', 'RIGHT_ANKLE'),
)