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| import numpy as np | |
| import os | |
| import sys | |
| # SMAL_DATA_DIR = '/is/cluster/work/nrueegg/dog_project/pytorch-dogs-inference/src/smal_pytorch/smpl_models/' | |
| # SMAL_DATA_DIR = os.path.join(os.path.dirname(__file__), '..', 'smal_pytorch', 'smal_data') | |
| SMAL_DATA_DIR = os.path.join(os.path.dirname(__file__), '..', '..', 'data', 'smal_data') | |
| # we replace the old SMAL model by a more dog specific model (see BARC cvpr 2022 paper) | |
| # our model has several differences compared to the original SMAL model, some of them are: | |
| # - the PCA shape space is recalculated (from partially new data and weighted) | |
| # - coefficients for limb length changes are allowed (similar to WLDO, we did borrow some of their code) | |
| # - all dogs have a core of approximately the same length | |
| # - dogs are centered in their root joint (which is close to the tail base) | |
| # -> like this the root rotations is always around this joint AND (0, 0, 0) | |
| # -> before this it would happen that the animal 'slips' from the image middle to the side when rotating it. Now | |
| # 'trans' also defines the center of the rotation | |
| # - we correct the back joint locations such that all those joints are more aligned | |
| SMAL_MODEL_PATH = os.path.join(SMAL_DATA_DIR, 'my_smpl_SMBLD_nbj_v3.pkl') | |
| UNITY_SMAL_SHAPE_PRIOR_DOGS = os.path.join(SMAL_DATA_DIR, 'my_smpl_data_SMBLD_v3.pkl') | |
| SYMMETRY_INDS_FILE = os.path.join(SMAL_DATA_DIR, 'symmetry_inds.json') | |
| mean_dog_bone_lengths_txt = os.path.join(SMAL_DATA_DIR, 'mean_dog_bone_lengths.txt') | |
| # there exist different keypoint configurations, for example keypoints corresponding to SMAL joints or keypoints defined based on vertex locations | |
| KEYPOINT_CONFIGURATION = 'green' # green: same as in https://github.com/benjiebob/SMALify/blob/master/config.py | |
| # some vertex indices, (from silvia zuffi´s code, create_projected_images_cats.py) | |
| KEY_VIDS = np.array(([1068, 1080, 1029, 1226], # left eye | |
| [2660, 3030, 2675, 3038], # right eye | |
| [910], # mouth low | |
| [360, 1203, 1235, 1230], # front left leg, low | |
| [3188, 3156, 2327, 3183], # front right leg, low | |
| [1976, 1974, 1980, 856], # back left leg, low | |
| [3854, 2820, 3852, 3858], # back right leg, low | |
| [452, 1811], # tail start | |
| [416, 235, 182], # front left leg, top | |
| [2156, 2382, 2203], # front right leg, top | |
| [829], # back left leg, top | |
| [2793], # back right leg, top | |
| [60, 114, 186, 59], # throat, close to base of neck | |
| [2091, 2037, 2036, 2160], # withers (a bit lower than in reality) | |
| [384, 799, 1169, 431], # front left leg, middle | |
| [2351, 2763, 2397, 3127], # front right leg, middle | |
| [221, 104], # back left leg, middle | |
| [2754, 2192], # back right leg, middle | |
| [191, 1158, 3116, 2165], # neck | |
| [28], # Tail tip | |
| [542], # Left Ear | |
| [2507], # Right Ear | |
| [1039, 1845, 1846, 1870, 1879, 1919, 2997, 3761, 3762], # nose tip | |
| [0, 464, 465, 726, 1824, 2429, 2430, 2690]), dtype=object) # half tail | |
| # the following vertices are used for visibility only: if one of the vertices is visible, | |
| # then we assume that the joint is visible! There is some noise, but we don't care, as this is | |
| # for generation of the synthetic dataset only | |
| KEY_VIDS_VISIBILITY_ONLY = np.array(([1068, 1080, 1029, 1226, 645], # left eye | |
| [2660, 3030, 2675, 3038, 2567], # right eye | |
| [910, 11, 5], # mouth low | |
| [360, 1203, 1235, 1230, 298, 408, 303, 293, 384], # front left leg, low | |
| [3188, 3156, 2327, 3183, 2261, 2271, 2573, 2265], # front right leg, low | |
| [1976, 1974, 1980, 856, 559, 851, 556], # back left leg, low | |
| [3854, 2820, 3852, 3858, 2524, 2522, 2815, 2072], # back right leg, low | |
| [452, 1811, 63, 194, 52, 370, 64], # tail start | |
| [416, 235, 182, 440, 8, 80, 73, 112], # front left leg, top | |
| [2156, 2382, 2203, 2050, 2052, 2406, 3], # front right leg, top | |
| [829, 219, 218, 173, 17, 7, 279], # back left leg, top | |
| [2793, 582, 140, 87, 2188, 2147, 2063], # back right leg, top | |
| [60, 114, 186, 59, 878, 130, 189, 45], # throat, close to base of neck | |
| [2091, 2037, 2036, 2160, 190, 2164], # withers (a bit lower than in reality) | |
| [384, 799, 1169, 431, 321, 314, 437, 310, 323], # front left leg, middle | |
| [2351, 2763, 2397, 3127, 2278, 2285, 2282, 2275, 2359], # front right leg, middle | |
| [221, 104, 105, 97, 103], # back left leg, middle | |
| [2754, 2192, 2080, 2251, 2075, 2074], # back right leg, middle | |
| [191, 1158, 3116, 2165, 154, 653, 133, 339], # neck | |
| [28, 474, 475, 731, 24], # Tail tip | |
| [542, 147, 509, 200, 522], # Left Ear | |
| [2507,2174, 2122, 2126, 2474], # Right Ear | |
| [1039, 1845, 1846, 1870, 1879, 1919, 2997, 3761, 3762], # nose tip | |
| [0, 464, 465, 726, 1824, 2429, 2430, 2690]), dtype=object) # half tail | |
| # see: https://github.com/benjiebob/SMALify/blob/master/config.py | |
| # JOINT DEFINITIONS - based on SMAL joints and additional {eyes, ear tips, chin and nose} | |
| TORSO_JOINTS = [2, 5, 8, 11, 12, 23] | |
| CANONICAL_MODEL_JOINTS = [ | |
| 10, 9, 8, # upper_left [paw, middle, top] | |
| 20, 19, 18, # lower_left [paw, middle, top] | |
| 14, 13, 12, # upper_right [paw, middle, top] | |
| 24, 23, 22, # lower_right [paw, middle, top] | |
| 25, 31, # tail [start, end] | |
| 33, 34, # ear base [left, right] | |
| 35, 36, # nose, chin | |
| 38, 37, # ear tip [left, right] | |
| 39, 40, # eyes [left, right] | |
| 6, 11, # withers, throat (throat is inaccurate and withers also) | |
| 28] # tail middle | |
| # old: 15, 15, # withers, throat (TODO: Labelled same as throat for now), throat | |
| # the following list gives the indices of the KEY_VIDS_JOINTS that must be taken in order | |
| # to judge if the CANONICAL_MODEL_JOINTS are visible - those are all approximations! | |
| CMJ_VISIBILITY_IN_KEY_VIDS = [ | |
| 3, 14, 8, # left front leg | |
| 5, 16, 10, # left rear leg | |
| 4, 15, 9, # right front leg | |
| 6, 17, 11, # right rear leg | |
| 7, 19, # tail front, tail back | |
| 20, 21, # ear base (but can not be found in blue, se we take the tip) | |
| 2, 2, # mouth (was: 22, 2) | |
| 20, 21, # ear tips | |
| 1, 0, # eyes | |
| 18, # withers, not sure where this point is | |
| 12, # throat | |
| 23, # mid tail | |
| ] | |
| # define which bone lengths are used as input to the 2d-to-3d network | |
| IDXS_BONES_NO_REDUNDANCY = [6,7,8,9,16,17,18,19,32,1,2,3,4,5,14,15,24,25,26,27,28,29,30,31] | |
| # load bone lengths of the mean dog (already filtered) | |
| mean_dog_bone_lengths = [] | |
| with open(mean_dog_bone_lengths_txt, 'r') as f: | |
| for line in f: | |
| mean_dog_bone_lengths.append(float(line.split('\n')[0])) | |
| MEAN_DOG_BONE_LENGTHS_NO_RED = np.asarray(mean_dog_bone_lengths)[IDXS_BONES_NO_REDUNDANCY] # (24, ) | |
| # Body part segmentation: | |
| # the body can be segmented based on the bones and for the new dog model also based on the new shapedirs | |
| # axis_horizontal = self.shapedirs[2, :].reshape((-1, 3))[:, 0] | |
| # all_indices = np.arange(3889) | |
| # tail_indices = all_indices[axis_horizontal.detach().cpu().numpy() < 0.0] | |
| VERTEX_IDS_TAIL = [ 0, 4, 9, 10, 24, 25, 28, 453, 454, 456, 457, | |
| 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, | |
| 469, 470, 471, 472, 473, 474, 475, 724, 725, 726, 727, | |
| 728, 729, 730, 731, 813, 975, 976, 977, 1109, 1110, 1111, | |
| 1811, 1813, 1819, 1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, | |
| 1828, 1835, 1836, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, | |
| 1968, 1969, 2418, 2419, 2421, 2422, 2423, 2424, 2425, 2426, 2427, | |
| 2428, 2429, 2430, 2431, 2432, 2433, 2434, 2435, 2436, 2437, 2438, | |
| 2439, 2440, 2688, 2689, 2690, 2691, 2692, 2693, 2694, 2695, 2777, | |
| 3067, 3068, 3069, 3842, 3843, 3844, 3845, 3846, 3847] | |
| # same as in https://github.com/benjiebob/WLDO/blob/master/global_utils/config.py | |
| EVAL_KEYPOINTS = [ | |
| 0, 1, 2, # left front | |
| 3, 4, 5, # left rear | |
| 6, 7, 8, # right front | |
| 9, 10, 11, # right rear | |
| 12, 13, # tail start -> end | |
| 14, 15, # left ear, right ear | |
| 16, 17, # nose, chin | |
| 18, 19] # left tip, right tip | |
| KEYPOINT_GROUPS = { | |
| 'legs': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], # legs | |
| 'tail': [12, 13], # tail | |
| 'ears': [14, 15, 18, 19], # ears | |
| 'face': [16, 17] # face | |
| } | |