Support skeleton (#155)
* pose * pose * pose * pose * 你的提交消息 * pose * pose * Delete train1.sh * pretreatment * configs * pose * reference * Update gaittr.py * naming * naming * Update transform.py * update for datasets * update README * update name and README * update * Update transform.py
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Dongyang Jin
GitHub
@@ -196,3 +196,257 @@ def get_transform(trf_cfg=None):
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transform = [get_transform(cfg) for cfg in trf_cfg]
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return transform
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raise "Error type for -Transform-Cfg-"
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# **************** For pose ****************
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class RandomSelectSequence(object):
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"""
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Randomly select different subsequences
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"""
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def __init__(self, sequence_length=10):
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self.sequence_length = sequence_length
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def __call__(self, data):
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try:
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start = np.random.randint(0, data.shape[0] - self.sequence_length)
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except ValueError:
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raise ValueError("The sequence length of data is too short, which does not meet the requirements.")
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end = start + self.sequence_length
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return data[start:end]
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class SelectSequenceCenter(object):
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"""
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Select center subsequence
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"""
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def __init__(self, sequence_length=10):
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self.sequence_length = sequence_length
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def __call__(self, data):
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try:
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start = int((data.shape[0]/2) - (self.sequence_length / 2))
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except ValueError:
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raise ValueError("The sequence length of data is too short, which does not meet the requirements.")
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end = start + self.sequence_length
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return data[start:end]
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class MirrorPoses(object):
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"""
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Performing Mirror Operations
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"""
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def __init__(self, prob=0.5):
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self.probability = probability
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def __call__(self, data):
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if np.random.random() <= self.probability:
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center = np.mean(data[:, :, 0], axis=1, keepdims=True)
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data[:, :, 0] = center - data[:, :, 0] + center
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return data
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class NormalizeEmpty(object):
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"""
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Normliza Empty Joint
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"""
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def __call__(self, data):
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frames, joints = np.where(data[:, :, 0] == 0)
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for frame, joint in zip(frames, joints):
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center_of_gravity = np.mean(data[frame], axis=0)
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data[frame, joint, 0] = center_of_gravity[0]
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data[frame, joint, 1] = center_of_gravity[1]
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data[frame, joint, 2] = 0
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return data
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class RandomMove(object):
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"""
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Move: add Random Movement to each joint
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"""
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def __init__(self,random_r =[4,1]):
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self.random_r = random_r
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def __call__(self, data):
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noise = np.zeros(3)
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noise[0] = np.random.uniform(-self.random_r[0], self.random_r[0])
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noise[1] = np.random.uniform(-self.random_r[1], self.random_r[1])
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data += np.tile(noise,(data.shape[0], data.shape[1], 1))
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return data
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class PointNoise(object):
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"""
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Add Gaussian noise to pose points
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std: standard deviation
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"""
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def __init__(self, std=0.01):
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self.std = std
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def __call__(self, data):
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noise = np.random.normal(0, self.std, data.shape).astype(np.float32)
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return data + noise
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class FlipSequence(object):
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"""
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Temporal Fliping
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"""
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def __init__(self, probability=0.5):
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self.probability = probability
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def __call__(self, data):
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if np.random.random() <= self.probability:
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return np.flip(data,axis=0).copy()
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return data
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class InversePosesPre(object):
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'''
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Left-right flip of skeletons
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'''
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def __init__(self, probability=0.5, joint_format='coco'):
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self.probability = probability
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if joint_format == 'coco':
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self.invers_arr = [0, 2, 1, 4, 3, 6, 5, 8, 7, 10, 9, 12, 11, 14, 13, 16, 15]
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elif joint_format in ['alphapose', 'openpose']:
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self.invers_arr = [0, 1, 5, 6, 7, 2, 3, 4, 11, 12, 13, 8, 9, 10, 15, 14, 17, 16]
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else:
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raise ValueError("Invalid joint_format.")
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def __call__(self, data):
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for i in range(len(data)):
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if np.random.random() <= self.probability:
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data[i]=data[i,self.invers_arr,:]
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return data
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class JointNoise(object):
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"""
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Add Gaussian noise to joint
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std: standard deviation
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"""
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def __init__(self, std=0.25):
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self.std = std
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def __call__(self, data):
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# T, V, C
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noise = np.hstack((
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np.random.normal(0, self.std, (data.shape[1], 2)),
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np.zeros((data.shape[1], 1))
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)).astype(np.float32)
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return data + np.repeat(noise[np.newaxis, ...], data.shape[0], axis=0)
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class GaitTRMultiInput(object):
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def __init__(self, joint_format='coco',):
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if joint_format == 'coco':
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self.connect_joint = np.array([5,0,0,1,2,0,0,5,6,7,8,5,6,11,12,13,14])
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elif joint_format in ['alphapose', 'openpose']:
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self.connect_joint = np.array([1,1,1,2,3,1,5,6,2,8,9,5,11,12,0,0,14,15])
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else:
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raise ValueError("Invalid joint_format.")
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def __call__(self, data):
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# (C, T, V) -> (I, C * 2, T, V)
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data = np.transpose(data, (2, 0, 1))
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data = data[:2, :, :]
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C, T, V = data.shape
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data_new = np.zeros((5, C, T, V))
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# Joints
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data_new[0, :C, :, :] = data
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for i in range(V):
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data_new[1, :, :, i] = data[:, :, i] - data[:, :, 0]
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# Velocity
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for i in range(T - 2):
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data_new[2, :, i, :] = data[:, i + 1, :] - data[:, i, :]
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data_new[3, :, i, :] = data[:, i + 2, :] - data[:, i, :]
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# Bones
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for i in range(len(self.connect_joint)):
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data_new[4, :, :, i] = data[:, :, i] - data[:, :, self.connect_joint[i]]
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I, C, T, V = data_new.shape
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data_new = data_new.reshape(I*C, T, V)
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# (C T V) -> (T V C)
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data_new = np.transpose(data_new, (1, 2, 0))
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return data_new
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class GaitGraphMultiInput(object):
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def __init__(self, center=0, joint_format='coco'):
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self.center = center
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if joint_format == 'coco':
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self.connect_joint = np.array([5,0,0,1,2,0,0,5,6,7,8,5,6,11,12,13,14])
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elif joint_format in ['alphapose', 'openpose']:
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self.connect_joint = np.array([1,1,1,2,3,1,5,6,2,8,9,5,11,12,0,0,14,15])
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else:
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raise ValueError("Invalid joint_format.")
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def __call__(self, data):
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T, V, C = data.shape
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x_new = np.zeros((T, V, 3, C + 2))
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# Joints
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x = data
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x_new[:, :, 0, :C] = x
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for i in range(V):
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x_new[:, i, 0, C:] = x[:, i, :2] - x[:, self.center, :2]
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# Velocity
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for i in range(T - 2):
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x_new[i, :, 1, :2] = x[i + 1, :, :2] - x[i, :, :2]
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x_new[i, :, 1, 3:] = x[i + 2, :, :2] - x[i, :, :2]
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x_new[:, :, 1, 3] = x[:, :, 2]
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# Bones
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for i in range(V):
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x_new[:, i, 2, :2] = x[:, i, :2] - x[:, self.connect_joint[i], :2]
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# Angles
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bone_length = 0
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for i in range(C - 1):
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bone_length += np.power(x_new[:, :, 2, i], 2)
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bone_length = np.sqrt(bone_length) + 0.0001
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for i in range(C - 1):
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x_new[:, :, 2, C+i] = np.arccos(x_new[:, :, 2, i] / bone_length)
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x_new[:, :, 2, 3] = x[:, :, 2]
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return x_new
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class GaitGraph1Input(object):
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'''
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Transpose the input
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'''
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def __call__(self, data):
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# (T V C) -> (C T V)
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data = np.transpose(data, (2, 0, 1))
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return data[...,np.newaxis]
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class SkeletonInput(object):
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'''
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Transpose the input
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'''
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def __call__(self, data):
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# (T V C) -> (T C V)
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data = np.transpose(data, (0, 2, 1))
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return data[...,np.newaxis]
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class TwoView(object):
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def __init__(self,trf_cfg):
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assert is_list(trf_cfg)
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self.transform = T.Compose([get_transform(cfg) for cfg in trf_cfg])
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def __call__(self, data):
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return np.concatenate([self.transform(data), self.transform(data)], axis=1)
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class MSGGTransform():
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def __init__(self, joint_format="coco"):
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if joint_format == "coco": #17
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self.mask=[6,8,14,12,7,13,5,10,16,11,9,15]
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elif joint_format in ['alphapose', 'openpose']: #18
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self.mask=[2,3,9,8,6,12,5,4,10,11,7,13]
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else:
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raise ValueError("Invalid joint_format.")
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def __call__(self, x):
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result=x[...,self.mask,:].copy()
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return result
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