def __init__(self, width, height):
self.viewDist = 50
self.width = width
self.height = height
self.zNear = 1.0
self.zFar = 2000.0
self.xMousePosPrev = 0
self.yMousePosPrev = 0
self.xTrans = 0
self.yTrans = 0
self.zTrans = 400
self.xRot = 60
self.yRot = -40
self.zRot = 0
self.viewMode = 'free'
self.frameId = 0
self.camId = deque('00', maxlen=2)
self.coco25_parents = [
1, 1, 1, 2, 3, 1, 5, 6, 1, 8, 9, 10, 8, 12, 13, 0, 0, 15, 16, 14,
19, 14, 11, 22, 11
]
self.adamWrapper = ADAM(pkl_path=adamPath)
self.smplWrapper = SMPL(pkl_path=smplPath, joint_type='legacy')
self.mouseAction = ""
self.models = None
self.modelsGhost = None
self.meshs = None
self.curcamid = 0
def __init__(self, width, height):
self.viewDist = 50
self.width = width
self.height = height
self.zNear = 1.0
self.zFar = 2000.0
self.xMousePosPrev = 0
self.yMousePosPrev = 0
self.xTrans = 0
self.yTrans = 0
self.zTrans = 800
self.xRot = 60
self.yRot = -40
self.zRot = 0
self.viewMode = 'free'
self.frameId = 0
self.camId = deque('00', maxlen=2)
self.adamWrapper = ADAM(pkl_path=adamPath)
self.smplWrapper = SMPL(pkl_path=smplPath, joint_type='legacy')
self.mouseAction = ""
self.models = None
def main_func():
aWrapper = ADAM(pkl_path='../../models/adamModel_lbs_200.pkl')
with open('../../models/adamModel_lbs_200.pkl') as fio:
adamModel = pickle.load(fio)
model_file = '../../models/adam_v1_plus2.json'
with open(model_file) as fio:
modelStr = json.load(fio)
coco_reg = modelStr['small_coco_reg']
coco_reg = np.array(coco_reg[1:])
coco_reg_sparse = scipy.sparse.coo_matrix(
(coco_reg[:, 2], (coco_reg[:, 0], coco_reg[:, 1])),
shape=(19, 18540)).tocsr()
coco25_reg_sparse = scipy.sparse.csr_matrix((25, 18540))
coco25_coco19_remap = [
14, 12, 8, 7, 6, 9, 10, 11, 13, 2, 1, 0, 3, 4, 5, 16, 15, 18, 17
]
coco25_reg_sparse[0:19, :] = coco_reg_sparse[coco25_coco19_remap, :]
coco25_reg_sparse[
8, :] = coco25_reg_sparse[12, :] * 0.5 + coco25_reg_sparse[9, :] * 0.5
coco25_reg_sparse[19, 12239] = 1.0
coco25_reg_sparse[20, 12289] = 1.0
coco25_reg_sparse[21, 12368] = 0.5
coco25_reg_sparse[21, 12357] = 0.5
coco25_reg_sparse[22, 14238] = 1.0 #
coco25_reg_sparse[23, 14288] = 1.0
coco25_reg_sparse[24, 14357] = 0.5
coco25_reg_sparse[24, 14361] = 0.5
adamModel['J_regressor_coco25'] = coco25_reg_sparse
adamModel['kintree_coco25'] = numpy.vstack((coco25_parents, coco25_ids))
print adamModel['J_regressor_coco25']
with open('../../models/adamModel_with_coco25_reg.pkl', 'wb') as fio:
pickle.dump(adamModel, fio, protocol=pickle.HIGHEST_PROTOCOL)
import numpy as np
import numpy.random
import matplotlib.pyplot as plt
import os.path
import glob
import json
import time
import cPickle as pickle
import copy
import sys
sys.path.append('/home/xiul/workspace/PanopticDome/python')
from domedb_utils.batch_adam import ADAM
import mvg_utils.triangulate as DLTtriangulate
adamWrapper = ADAM(
pkl_path='../../models/adamModel_with_coco25_reg.pkl', reg_type='coco25')
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
def parse_calibs(calibFile, viewnodes):
#P_Matrix as K*[R,t] 3x4
with open(calibFile) as f:
calibs = json.load(f)
cameras = calibs['cameras']
#cameras = rawCalibs['cameras']
allPanel = map(lambda x: x['panel'], cameras)
hdCamIndices = [i for i, x in enumerate(allPanel) if x == 0]
hdCams = [cameras[i] for i in hdCamIndices]
import numpy as np
import numpy.linalg as nl
import sys
import os
sys.path.append('/home/xiul/workspace/PanopticDome/python')
from meshWrapper import meshWrapper
from domedb_utils.batch_adam import ADAM
from domedb_utils.batch_smpl import SMPL
import copy
import cPickle as pickle
from opendr.geometry import VertNormals
import sklearn.preprocessing
import scipy.sparse
rootpath = os.path.dirname(os.path.abspath(__file__))
adamPath = '/media/posefs3b/Users/xiu/PanopticDome/models/adamModel_lbs_200.pkl'
adamWrapper = ADAM(pkl_path=adamPath, reg_type='legacy')
smplPath = '/media/posefs3b/Users/xiu/PanopticDome/models/neutral_smpl_with_cocoplus_reg.pkl'
smplWrapper = SMPL(pkl_path=smplPath, joint_type='cocoplus')
coco_reg = smplWrapper.joint_regressor[0].T
dome_to_angjoo = [
14, 13, 12, 6, 7, 8, 11, 10, 9, 3, 4, 5, 0, 2, 1, 15, 17, 16, 18
]
corrsFile = '../../models/correspondences_nofeet.txt'
corrsId = np.loadtxt(corrsFile)
handsId = []
target_adam_v = None
# #generateAdam_UVI_map()
meshlib = meshWrapper(
lib_file=os.path.join(rootpath, '../../build/libPythonWrapper.so'))
import threading
import time
import glob
import os.path
import copy
import sklearn.preprocessing
import cv2
sys.path.append('/home/xiul/workspace/PanopticDome/python')
from domedb_utils.batch_adam import ADAM
from domedb_utils.batch_smpl import SMPL
smplPath = '/media/posefs3b/Users/xiu/PanopticDome/models/neutral_smpl_with_cocoplus_reg.pkl'
adamPath = '/media/posefs3b/Users/xiu/PanopticDome/models/adamModel_lbs_200.pkl'
adamWrapper = ADAM(pkl_path=adamPath)
smplWrapper = SMPL(pkl_path=smplPath)
g_args = None
g_paramfiles = []
g_saveDir = None
def InstanceSMPL(frame_id):
print g_paramfiles[frame_id]
trans = []
betas = []
poses = []
exps = []