def save_pic_and_lmk(kk):
shuru = kk
if shuru == 0:
e = 1 #return 0 输入为0,说明只有一张图
else:
lmk_dir = '/home/zhang/correctdata/data/landmark/' #注意lmk文件的后缀为.txt
pic_dir = '/home/zhang/correctdata/data/picture/'
bbox_dir = '/home/zhang/correctdata/bbox/'
length = len(shuru)
for i in range(length):
if i % 2 == 0:
filename1 = pic_dir + shuru[i]
'''filename2 = pic_dir+shuru[i+1]'''
lmk1 = utils.read_mat(lmk_dir + shuru[i + 1] + '.txt')
lmk2 = utils.read_mat(lmk_dir + shuru[i] + '.txt')
lmk = 0.5 * lmk1 + 0.5 * lmk2
image = plt.imread(filename1)
#图一的landmark归一化
bbox1 = utils.read_bbox(bbox_dir + shuru[i + 1] + '.rect')
lmk1 = utils.norm_landmarks(lmk1, bbox1)
image = image[bbox1[1]:bbox1[3], bbox1[0]:bbox1[2]]
#图一图二的插值图的landmark归一化
bbox2 = utils.read_bbox(bbox_dir + shuru[i] + '.rect')
lmk = utils.norm_landmarks(lmk, bbox2)
out = pwa.pwa(image.copy(), lmk1.copy(), lmk.copy(),
(256, 256))
# 图片与lmk保存
utils.save_landmarks(
lmk * 255, '/home/zhang/ming/save_for_lmk2/' +
shuru[i][:-5] + "%d" % (200 + i) + '.jpg' + '.txt')
io.imsave(
'/home/zhang/ming/save_for_pic2/' + shuru[i][:-5] + "%d" %
(200 + i) + '.jpg', out)
bbox_dir = os.path.join(root, 'bbox')
out_dir = os.path.join(root, 'crop')
if not os.path.exists(out_dir):
os.makedirs(os.path.join(out_dir, 'data/picture'))
os.makedirs(os.path.join(out_dir, 'data/landmark'))
for name in os.listdir(img_dir):
img_name = name
ldmk_name = name + '.txt'
bbox_name = name + '.rect'
img_path = os.path.join(img_dir, img_name)
ldmk_path = os.path.join(ldmk_dir, ldmk_name)
bbox_path = os.path.join(bbox_dir, bbox_name)
img_out_path = img_path.replace(root,
root + 'crop/').replace('.jpg', '.png')
ldmk_out_path = ldmk_path.replace(root, root + 'crop/')
img = plt.imread(img_path)
bbox = utils.read_bbox(bbox_path)
ldmk = utils.read_mat(ldmk_path)
minx, miny, maxx, maxy = bbox
ldmk -= [minx, miny]
img = img[miny:maxy + 1, minx:maxx + 1, :]
plt.imsave(img_out_path, img)
utils.save_landmarks(ldmk, ldmk_out_path)
images = [os.path.join(img_dir, f) for f in file_list]
landmarks = [os.path.join(landmark_dir, f + '.txt') for f in file_list]
bboxes = [os.path.join(bbox_dir, f + '.rect') for f in file_list]
img_out_dir = '/data/icme/align_by_ldmk/picture'
landmarks_out_dir = '/data/icme/align_by_ldmk/landmark'
t_out_dir = '/data/icme/align_by_ldmk/T'
if not os.path.exists(img_out_dir):
os.makedirs(img_out_dir)
if not os.path.exists(landmarks_out_dir):
os.makedirs(landmarks_out_dir)
for img_path, bbox_path, landmark_path, f in zip(images, bboxes, landmarks,
file_list):
bbox = utils.read_bbox(bbox_path)
landmark = utils.read_mat(landmark_path)
image = cv2.imread(img_path)
image, landmark, T = aligner(image, landmark, bbox)
# T[2, 0] /= image.shape[1]
# T[2, 1] /= image.shape[0]
# T[0:2, :] = np.linalg.inv(T[0:2, :])
cv2.imwrite(os.path.join(img_out_dir, f), image)
utils.save_landmarks(landmark,
os.path.join(landmarks_out_dir, f + '.txt'))
utils.save_T(T, os.path.join(t_out_dir, f + '.txt'))
num_workers=4))
for i in range(len(a)):
image, gt, t, name = next(batch_iterator)
image = image.cuda()
with torch.no_grad():
pr = net.forward(image)
pr = pr.cpu().data.numpy()
gt = gt.data.numpy()
t = t.data.numpy()
pr = np.reshape(pr, (-1, 2))
pr[:, 0] *= a.shape[1]
pr[:, 1] *= a.shape[0]
pr = a.aligner.inverse(pr, t[0])
gt = np.reshape(gt, (-1, 2))
all_pr.append(pr)
all_gt.append(gt)
# save prediction
utils.save_landmarks(pr, os.path.join(save_dir, name[0] + '.txt'))
all_gt = np.stack(all_gt, axis=0)
all_pr = np.stack(all_pr, axis=0)
nme = metrics.nme.update(np.reshape(all_gt, (-1, 106, 2)),
np.reshape(all_pr, (-1, 106, 2)))
metrics.auc.update(nme)
print("NME: %f\nAUC: %f" % (metrics.nme.value, metrics.auc.value))
# plt.subplot(1, 3, 3)
# plt.imshow(out)
# plt.axis((0, 128, 128, 0))
# plt.show()
for k in range(106):
cv2.circle(temp_out, (out_landmark[k, 0], out_landmark[k, 1]), 0,
(0, 255, 0))
temp_out = cv2.resize(temp_out, (1024, 1024))
# cv2.namedWindow('output', flags=cv2.WINDOW_NORMAL)
# cv2.imshow('output', temp_out)
# cv2.waitKey(0)
# time.sleep(3)
#创建新的名字
temp_src_name = src_name[0:len(src_name) - 4]
temp_dst_name = dst_name[0:len(dst_name) - 4]
distort_image_name = temp_src_name + '_' + temp_dst_name + '.jpg'
#保存扭曲图片
imagefile = Image.fromarray(out).convert('RGB')
imagefile.save(out_dir + 'images/' + distort_image_name)
#保存picture_draws
imagefile2 = Image.fromarray(temp_out).convert('RGB')
imagefile2.save(out_dir + 'picture_draws/' + str(j) + '/' +
distort_image_name)
#保存landmarks
utils.save_landmarks(
out_landmark, out_dir + 'landmarks/' + distort_image_name + '.txt')