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| import math | |
| import numpy as np | |
| from PIL import Image | |
| def trans2_white_bg(img_path): | |
| img = Image.open(img_path) | |
| img_arr = 255 - np.array(img)[:, :, 3] | |
| img_ = Image.fromarray(img_arr) | |
| img_.save(img_path) | |
| return img_arr | |
| def affine_shear(seq, dx=-0.3, dy=0.0): | |
| mask = ~(seq == 0) | |
| seq_12 = seq.copy() | |
| seq_12[:,4] -= 12.0 | |
| seq_12[:,5] = -seq_12[:,5] + 12 | |
| seq_12[:,6] -= 12.0 | |
| seq_12[:,7] = -seq_12[:,7] + 12 | |
| seq_12[:,8] -= 12.0 | |
| seq_12[:,9] = -seq_12[:,9] + 12 | |
| seq_args = seq_12[:,4:] | |
| seq_args = np.concatenate([seq_args[:, :2], seq_args[:, 2:4], seq_args[:, 4:6]], 0).transpose(1,0) | |
| affine_matrix=np.array([[1, dx], | |
| [dy, 1]]) | |
| rotated_args = np.dot(affine_matrix,seq_args) | |
| rotated_args = rotated_args.transpose(1,0) | |
| new_args = np.concatenate([rotated_args[:seq.shape[0]], rotated_args[seq.shape[0]:seq.shape[0]*2], rotated_args[seq.shape[0]*2:]],-1) | |
| new_args[:,0] += 12.0 | |
| new_args[:,1] = -(new_args[:,1] - 12) | |
| new_args[:,2] += 12.0 | |
| new_args[:,3] = -(new_args[:,3] - 12) | |
| new_args[:,4] += 12.0 | |
| new_args[:,5] = -(new_args[:,5] - 12) | |
| new_seq = np.concatenate([seq[:, :4], new_args],1) | |
| new_seq = new_seq * mask | |
| return new_seq | |
| def affine_scale(seq, scale=0.8): | |
| mask = ~(seq==0) | |
| seq_args = seq[:, 4:] - 12.0 | |
| seq_args *= scale | |
| seq_args = seq_args + 12.0 | |
| new_seq = np.concatenate([seq[:, :4], seq_args], 1) | |
| new_seq = new_seq * mask | |
| return new_seq | |
| def affine_rotate(seq,theta=-5): | |
| mask = ~(seq==0) | |
| seq_12 = seq.copy() | |
| seq_12[:,4] -=12.0 | |
| seq_12[:,5] = -seq_12[:,5] + 12 | |
| seq_12[:,6] -=12.0 | |
| seq_12[:,7] = -seq_12[:,7] + 12 | |
| seq_12[:,8] -=12.0 | |
| seq_12[:,9] = -seq_12[:,9] + 12 | |
| seq_args =seq_12[:, 4:] # default as [71,6] | |
| seq_args = np.concatenate([seq_args[:,:2],seq_args[:,2:4],seq_args[:,4:6]],0).transpose(1,0)# note 2,213 | |
| theta = math.radians(theta) | |
| affine_matrix=np.array([[np.cos(theta),-np.sin(theta)], [np.sin(theta), np.cos(theta)]])# note 2,2 | |
| rotated_args = np.dot(affine_matrix,seq_args)# note 2,213 | |
| rotated_args = rotated_args.transpose(1,0)# note 213,2 | |
| new_args = np.concatenate([rotated_args[:seq.shape[0]],rotated_args[seq.shape[0]:seq.shape[0]*2],rotated_args[seq.shape[0]*2:]],-1)# note 2,213 | |
| new_args[:,0] +=12.0 | |
| new_args[:,1] = -(new_args[:,1]-12) | |
| new_args[:,2] +=12.0 | |
| new_args[:,3] = -(new_args[:,3]-12) | |
| new_args[:,4] +=12.0 | |
| new_args[:,5] = -(new_args[:,5]-12) | |
| new_seq = np.concatenate([seq[:,:4],new_args],1) | |
| new_seq =new_seq *mask | |
| return new_seq | |