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from __future__ import print_function
import os
import sys
import random
import copy
import argparse
import math
import pickle
import json
import glob
import numpy as np
sys.path.insert(0, os.getcwd())
from lib.utils.utils_data import crop_scale
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--name_action', type=str)
args = parser.parse_args()
print("\nParameters:")
for attr, value in sorted(args.__dict__.items()):
print("\t{}={}".format(attr.upper(), value))
return args
def json2pose(json_dict):
pose_h36m = np.zeros([17,3])
idx2key = ['Hip',
'R Hip',
'R Knee',
'R Ankle',
'L Hip',
'L Knee',
'L Ankle',
'Belly',
'Neck',
'Nose',
'Head',
'L Shoulder',
'L Elbow',
'L Wrist',
'R Shoulder',
'R Elbow',
'R Wrist',
]
for i in range(17):
if idx2key[i]=='Belly' or idx2key[i]=='Head':
pose_h36m[i] = 0, 0, 0
else:
item = json_dict[idx2key[i]]
pose_h36m[i] = item['x'], item['y'], item['logits']
return pose_h36m
def load_motion(json_path):
json_dict = json.load(open(json_path, 'r'))
pose_h36m = json2pose(json_dict)
return pose_h36m
args = parse_args()
dataset_root = 'data/Motion2d/InstaVariety/InstaVariety_tracks/'
action_motions = []
dir_action = os.path.join(dataset_root, args.name_action)
for name_vid in sorted(os.listdir(dir_action)):
dir_vid = os.path.join(dir_action, name_vid)
for name_clip in sorted(os.listdir(dir_vid)):
motion_path = os.path.join(dir_vid, name_clip)
motion_list = sorted(glob.glob(motion_path+'/*.json'))
if len(motion_list)==0:
continue
motion = [load_motion(i) for i in motion_list]
motion = np.array(motion)
motion = crop_scale(motion)
motion[:,:,:2] = motion[:,:,:2] - motion[0:1,0:1,:2]
motion[motion[:,:,2]==0] = 0
action_motions.append(motion)
print("%s Done, %d vids processed" % (name_vid, len(action_motions)))
print("%s Done, %d vids processed" % (args.name_action, len(action_motions)))
with open(os.path.join(dir_action, '%s.pkl' % args.name_action), 'wb') as f:
pickle.dump(action_motions, f)
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