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import os
import json
common_root = 'd:/Datasets'
depth_root = 'kitti/kitti_depth/depth/data_depth_annotated'
raw_root = 'kitti_raw/kitti_raw'
#print(os.listdir(os.path.join(common_root, raw_root)))
mid = 'proj_depth/groundtruth'
mid_raw = 'data'
test_file_dict = {}
test_file_list = []
train_file_dict = {}
with open('D:/Datasets/eigen_train.txt') as f:
lines_train = f.readlines()
cnt = 0
invalid_cnt = 0
if True:
lines = lines_train
for l in lines:
l_ls = l.split(' ')
scene = l_ls[0]
date = scene.split('/')[0]
scene_no_date = scene.split('/')[1]
frame = l_ls[1]
frame = frame.zfill(10)
if 'l' in l_ls[2]:
cam = 'image_02'
P_str = 'P_rect_02'
elif 'r' in l_ls[2]:
cam = 'image_03'
P_str = 'P_rect_03'
else:
raise NotImplementedError()
depth_train = os.path.join(depth_root, 'train', scene_no_date, mid, cam , frame + '.png')
depth_val = os.path.join(depth_root, 'val', scene_no_date, mid, cam, frame+'.png')
rgb = os.path.join(raw_root, scene, cam, mid_raw, frame+'.png')
with open(os.path.join(common_root, raw_root, date, 'calib_cam_to_cam.txt')) as c:
lines_c = c.readlines()
for l_c in lines_c:
if P_str in l_c:
k_str = l_c.split(':')[1:]
k = k_str[0].split(' ')
cam_in = [float(k[1]), float(k[6]), float(k[3]), float(k[7])]
rgb_path = os.path.join(common_root, rgb)
assert os.path.join(common_root, rgb_path)
if os.path.exists(os.path.join(common_root, depth_train)):
depth_path = os.path.join(common_root, depth_train)
depth_rel = depth_train
else:
depth_path = os.path.join(common_root, depth_val)
depth_rel = depth_val
try:
assert os.path.exists(depth_path)
cnt += 1
except:
invalid_cnt += 1
continue
curr_file = [{'rgb':rgb.replace("\\", '/'), 'depth':depth_rel.replace("\\", '/'), 'cam_in':cam_in}]
test_file_list = test_file_list + curr_file
if ((cnt + invalid_cnt) % 1000 == 0):
print(cnt + invalid_cnt)
print(cnt, invalid_cnt)
train_file_dict['files'] = test_file_list
with open('eigen_train.json', 'w') as fj:
json.dump(train_file_dict, fj) |