FOCAL_LENGTH = 5000.

# Mean and standard deviation for normalizing input image
IMG_NORM_MEAN = [0.485, 0.456, 0.406]
IMG_NORM_STD = [0.229, 0.224, 0.225]

"""
We create a superset of joints containing the OpenPose joints together with the ones that each dataset provides.
We keep a superset of 24 joints such that we include all joints from every dataset.
If a dataset doesn't provide annotations for a specific joint, we simply ignore it.
The joints used here are the following:
"""
JOINT_NAMES = [
'OP Nose', 'OP Neck', 'OP RShoulder',           #0,1,2
'OP RElbow', 'OP RWrist', 'OP LShoulder',       #3,4,5
'OP LElbow', 'OP LWrist', 'OP MidHip',          #6, 7,8
'OP RHip', 'OP RKnee', 'OP RAnkle',             #9,10,11
'OP LHip', 'OP LKnee', 'OP LAnkle',             #12,13,14
'OP REye', 'OP LEye', 'OP REar',                #15,16,17
'OP LEar', 'OP LBigToe', 'OP LSmallToe',        #18,19,20
'OP LHeel', 'OP RBigToe', 'OP RSmallToe', 'OP RHeel',  #21, 22, 23, 24  ##Total 25 joints  for openpose
'Right Ankle', 'Right Knee', 'Right Hip',               #0,1,2
'Left Hip', 'Left Knee', 'Left Ankle',                  #3, 4, 5
'Right Wrist', 'Right Elbow', 'Right Shoulder',     #6
'Left Shoulder', 'Left Elbow', 'Left Wrist',            #9
'Neck (LSP)', 'Top of Head (LSP)',                      #12, 13
'Pelvis (MPII)', 'Thorax (MPII)',                       #14, 15
'Spine (H36M)', 'Jaw (H36M)',                           #16, 17
'Head (H36M)', 'Nose', 'Left Eye',                      #18, 19, 20
'Right Eye', 'Left Ear', 'Right Ear'                    #21,22,23 (Total 24 joints)
]

# Dict containing the joints in numerical order
JOINT_IDS = {JOINT_NAMES[i]: i for i in range(len(JOINT_NAMES))}

# Map joints to SMPL joints
JOINT_MAP = {
'OP Nose': 24, 'OP Neck': 12, 'OP RShoulder': 17,
'OP RElbow': 19, 'OP RWrist': 21, 'OP LShoulder': 16,
'OP LElbow': 18, 'OP LWrist': 20, 'OP MidHip': 0,
'OP RHip': 2, 'OP RKnee': 5, 'OP RAnkle': 8,
'OP LHip': 1, 'OP LKnee': 4, 'OP LAnkle': 7,
'OP REye': 25, 'OP LEye': 26, 'OP REar': 27,
'OP LEar': 28, 'OP LBigToe': 29, 'OP LSmallToe': 30,
'OP LHeel': 31, 'OP RBigToe': 32, 'OP RSmallToe': 33, 'OP RHeel': 34,
'Right Ankle': 8, 'Right Knee': 5, 'Right Hip': 45,
'Left Hip': 46, 'Left Knee': 4, 'Left Ankle': 7,
'Right Wrist': 21, 'Right Elbow': 19, 'Right Shoulder': 17,
'Left Shoulder': 16, 'Left Elbow': 18, 'Left Wrist': 20,
'Neck (LSP)': 47, 'Top of Head (LSP)': 48,
'Pelvis (MPII)': 49, 'Thorax (MPII)': 50,
'Spine (H36M)': 51, 'Jaw (H36M)': 52,
'Head (H36M)': 53, 'Nose': 24, 'Left Eye': 26,
'Right Eye': 25, 'Left Ear': 28, 'Right Ear': 27
}

# Joint selectors
# Indices to get the 14 LSP joints from the 17 H36M joints
H36M_TO_J17 = [6, 5, 4, 1, 2, 3, 16, 15, 14, 11, 12, 13, 8, 10, 0, 7, 9]
H36M_TO_J14 = H36M_TO_J17[:14]
# Indices to get the 14 LSP joints from the ground truth joints
J24_TO_J17 = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 18, 14, 16, 17]
J24_TO_J14 = J24_TO_J17[:14]

# Permutation of SMPL pose parameters when flipping the shape
SMPL_JOINTS_FLIP_PERM = [0, 2, 1, 3, 5, 4, 6, 8, 7, 9, 11, 10, 12, 14, 13, 15, 17, 16, 19, 18, 21, 20, 23, 22]
SMPL_POSE_FLIP_PERM = []
for i in SMPL_JOINTS_FLIP_PERM:
    SMPL_POSE_FLIP_PERM.append(3*i)
    SMPL_POSE_FLIP_PERM.append(3*i+1)
    SMPL_POSE_FLIP_PERM.append(3*i+2)
# Permutation indices for the 24 ground truth joints
J24_FLIP_PERM = [5, 4, 3, 2, 1, 0, 11, 10, 9, 8, 7, 6, 12, 13, 14, 15, 16, 17, 18, 19, 21, 20, 23, 22]
# Permutation indices for the full set of 49 joints
J49_FLIP_PERM = [0, 1, 5, 6, 7, 2, 3, 4, 8, 12, 13, 14, 9, 10, 11, 16, 15, 18, 17, 22, 23, 24, 19, 20, 21]\
              + [25+i for i in J24_FLIP_PERM]