Merge branch 'main' into hf_space

benchmark/csv/meta_bonn.csv

@@ -0,0 +1,6 @@
+filepath_left,filepath_disparity
+bonn/rgbd_bonn_synchronous_rgb_left.mp4,bonn/rgbd_bonn_synchronous_disparity.npz
+bonn/rgbd_bonn_person_tracking_rgb_left.mp4,bonn/rgbd_bonn_person_tracking_disparity.npz
+bonn/rgbd_bonn_crowd2_rgb_left.mp4,bonn/rgbd_bonn_crowd2_disparity.npz
+bonn/rgbd_bonn_crowd3_rgb_left.mp4,bonn/rgbd_bonn_crowd3_disparity.npz
+bonn/rgbd_bonn_balloon2_rgb_left.mp4,bonn/rgbd_bonn_balloon2_disparity.npz

benchmark/csv/meta_kitti_val.csv

@@ -0,0 +1,14 @@
+filepath_left,filepath_disparity
+KITTI/2011_09_28_drive_0037_sync_rgb_left.mp4,KITTI/2011_09_28_drive_0037_sync_disparity.npz
+KITTI/2011_09_26_drive_0005_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0005_sync_disparity.npz
+KITTI/2011_09_30_drive_0016_sync_rgb_left.mp4,KITTI/2011_09_30_drive_0016_sync_disparity.npz
+KITTI/2011_09_26_drive_0079_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0079_sync_disparity.npz
+KITTI/2011_09_26_drive_0020_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0020_sync_disparity.npz
+KITTI/2011_09_26_drive_0095_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0095_sync_disparity.npz
+KITTI/2011_10_03_drive_0047_sync_rgb_left.mp4,KITTI/2011_10_03_drive_0047_sync_disparity.npz
+KITTI/2011_09_26_drive_0113_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0113_sync_disparity.npz
+KITTI/2011_09_26_drive_0036_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0036_sync_disparity.npz
+KITTI/2011_09_26_drive_0013_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0013_sync_disparity.npz
+KITTI/2011_09_26_drive_0002_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0002_sync_disparity.npz
+KITTI/2011_09_29_drive_0026_sync_rgb_left.mp4,KITTI/2011_09_29_drive_0026_sync_disparity.npz
+KITTI/2011_09_26_drive_0023_sync_rgb_left.mp4,KITTI/2011_09_26_drive_0023_sync_disparity.npz

benchmark/csv/meta_nyu_test.csv

@@ -0,0 +1,655 @@
+filepath_left,filepath_disparity
+NYUv2/test/kitchen_0004/rgb_0001_rgb_left.mp4,NYUv2/test/kitchen_0004/rgb_0001_disparity.npz
+NYUv2/test/kitchen_0004/rgb_0002_rgb_left.mp4,NYUv2/test/kitchen_0004/rgb_0002_disparity.npz
+NYUv2/test/office_0005/rgb_0009_rgb_left.mp4,NYUv2/test/office_0005/rgb_0009_disparity.npz
+NYUv2/test/office_0007/rgb_0014_rgb_left.mp4,NYUv2/test/office_0007/rgb_0014_disparity.npz
+NYUv2/test/office_0008/rgb_0015_rgb_left.mp4,NYUv2/test/office_0008/rgb_0015_disparity.npz
+NYUv2/test/office_0008/rgb_0016_rgb_left.mp4,NYUv2/test/office_0008/rgb_0016_disparity.npz
+NYUv2/test/office_0008/rgb_0017_rgb_left.mp4,NYUv2/test/office_0008/rgb_0017_disparity.npz
+NYUv2/test/office_0008/rgb_0018_rgb_left.mp4,NYUv2/test/office_0008/rgb_0018_disparity.npz
+NYUv2/test/office_0010/rgb_0021_rgb_left.mp4,NYUv2/test/office_0010/rgb_0021_disparity.npz
+NYUv2/test/office_0013/rgb_0028_rgb_left.mp4,NYUv2/test/office_0013/rgb_0028_disparity.npz
+NYUv2/test/office_0013/rgb_0029_rgb_left.mp4,NYUv2/test/office_0013/rgb_0029_disparity.npz
+NYUv2/test/office_0013/rgb_0030_rgb_left.mp4,NYUv2/test/office_0013/rgb_0030_disparity.npz
+NYUv2/test/office_0013/rgb_0031_rgb_left.mp4,NYUv2/test/office_0013/rgb_0031_disparity.npz
+NYUv2/test/office_0013/rgb_0032_rgb_left.mp4,NYUv2/test/office_0013/rgb_0032_disparity.npz
+NYUv2/test/office_0013/rgb_0033_rgb_left.mp4,NYUv2/test/office_0013/rgb_0033_disparity.npz
+NYUv2/test/office_0013/rgb_0034_rgb_left.mp4,NYUv2/test/office_0013/rgb_0034_disparity.npz
+NYUv2/test/office_0014/rgb_0035_rgb_left.mp4,NYUv2/test/office_0014/rgb_0035_disparity.npz
+NYUv2/test/office_0014/rgb_0036_rgb_left.mp4,NYUv2/test/office_0014/rgb_0036_disparity.npz
+NYUv2/test/office_0014/rgb_0037_rgb_left.mp4,NYUv2/test/office_0014/rgb_0037_disparity.npz
+NYUv2/test/office_0014/rgb_0038_rgb_left.mp4,NYUv2/test/office_0014/rgb_0038_disparity.npz
+NYUv2/test/office_0015/rgb_0039_rgb_left.mp4,NYUv2/test/office_0015/rgb_0039_disparity.npz
+NYUv2/test/office_0015/rgb_0040_rgb_left.mp4,NYUv2/test/office_0015/rgb_0040_disparity.npz
+NYUv2/test/office_0015/rgb_0041_rgb_left.mp4,NYUv2/test/office_0015/rgb_0041_disparity.npz
+NYUv2/test/office_0015/rgb_0042_rgb_left.mp4,NYUv2/test/office_0015/rgb_0042_disparity.npz
+NYUv2/test/office_0015/rgb_0043_rgb_left.mp4,NYUv2/test/office_0015/rgb_0043_disparity.npz
+NYUv2/test/bathroom_0003/rgb_0046_rgb_left.mp4,NYUv2/test/bathroom_0003/rgb_0046_disparity.npz
+NYUv2/test/bathroom_0004/rgb_0047_rgb_left.mp4,NYUv2/test/bathroom_0004/rgb_0047_disparity.npz
+NYUv2/test/bedroom_0011/rgb_0056_rgb_left.mp4,NYUv2/test/bedroom_0011/rgb_0056_disparity.npz
+NYUv2/test/bedroom_0011/rgb_0057_rgb_left.mp4,NYUv2/test/bedroom_0011/rgb_0057_disparity.npz
+NYUv2/test/bedroom_0013/rgb_0059_rgb_left.mp4,NYUv2/test/bedroom_0013/rgb_0059_disparity.npz
+NYUv2/test/bedroom_0013/rgb_0060_rgb_left.mp4,NYUv2/test/bedroom_0013/rgb_0060_disparity.npz
+NYUv2/test/bedroom_0013/rgb_0061_rgb_left.mp4,NYUv2/test/bedroom_0013/rgb_0061_disparity.npz
+NYUv2/test/bedroom_0013/rgb_0062_rgb_left.mp4,NYUv2/test/bedroom_0013/rgb_0062_disparity.npz
+NYUv2/test/bedroom_0013/rgb_0063_rgb_left.mp4,NYUv2/test/bedroom_0013/rgb_0063_disparity.npz
+NYUv2/test/bedroom_0018/rgb_0076_rgb_left.mp4,NYUv2/test/bedroom_0018/rgb_0076_disparity.npz
+NYUv2/test/bedroom_0018/rgb_0077_rgb_left.mp4,NYUv2/test/bedroom_0018/rgb_0077_disparity.npz
+NYUv2/test/bedroom_0018/rgb_0078_rgb_left.mp4,NYUv2/test/bedroom_0018/rgb_0078_disparity.npz
+NYUv2/test/bedroom_0018/rgb_0079_rgb_left.mp4,NYUv2/test/bedroom_0018/rgb_0079_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0084_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0084_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0085_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0085_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0086_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0086_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0087_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0087_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0088_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0088_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0089_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0089_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0090_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0090_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0091_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0091_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0117_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0117_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0118_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0118_disparity.npz
+NYUv2/test/bookstore_0001/rgb_0119_rgb_left.mp4,NYUv2/test/bookstore_0001/rgb_0119_disparity.npz
+NYUv2/test/kitchen_0005/rgb_0125_rgb_left.mp4,NYUv2/test/kitchen_0005/rgb_0125_disparity.npz
+NYUv2/test/kitchen_0005/rgb_0126_rgb_left.mp4,NYUv2/test/kitchen_0005/rgb_0126_disparity.npz
+NYUv2/test/kitchen_0005/rgb_0127_rgb_left.mp4,NYUv2/test/kitchen_0005/rgb_0127_disparity.npz
+NYUv2/test/kitchen_0005/rgb_0128_rgb_left.mp4,NYUv2/test/kitchen_0005/rgb_0128_disparity.npz
+NYUv2/test/kitchen_0005/rgb_0129_rgb_left.mp4,NYUv2/test/kitchen_0005/rgb_0129_disparity.npz
+NYUv2/test/kitchen_0007/rgb_0131_rgb_left.mp4,NYUv2/test/kitchen_0007/rgb_0131_disparity.npz
+NYUv2/test/kitchen_0007/rgb_0132_rgb_left.mp4,NYUv2/test/kitchen_0007/rgb_0132_disparity.npz
+NYUv2/test/kitchen_0007/rgb_0133_rgb_left.mp4,NYUv2/test/kitchen_0007/rgb_0133_disparity.npz
+NYUv2/test/kitchen_0007/rgb_0134_rgb_left.mp4,NYUv2/test/kitchen_0007/rgb_0134_disparity.npz
+NYUv2/test/kitchen_0009/rgb_0137_rgb_left.mp4,NYUv2/test/kitchen_0009/rgb_0137_disparity.npz
+NYUv2/test/living_room_0008/rgb_0153_rgb_left.mp4,NYUv2/test/living_room_0008/rgb_0153_disparity.npz
+NYUv2/test/living_room_0008/rgb_0154_rgb_left.mp4,NYUv2/test/living_room_0008/rgb_0154_disparity.npz
+NYUv2/test/living_room_0009/rgb_0155_rgb_left.mp4,NYUv2/test/living_room_0009/rgb_0155_disparity.npz
+NYUv2/test/living_room_0013/rgb_0167_rgb_left.mp4,NYUv2/test/living_room_0013/rgb_0167_disparity.npz
+NYUv2/test/living_room_0013/rgb_0168_rgb_left.mp4,NYUv2/test/living_room_0013/rgb_0168_disparity.npz
+NYUv2/test/living_room_0014/rgb_0169_rgb_left.mp4,NYUv2/test/living_room_0014/rgb_0169_disparity.npz
+NYUv2/test/bedroom_0003/rgb_0171_rgb_left.mp4,NYUv2/test/bedroom_0003/rgb_0171_disparity.npz
+NYUv2/test/bedroom_0003/rgb_0172_rgb_left.mp4,NYUv2/test/bedroom_0003/rgb_0172_disparity.npz
+NYUv2/test/bedroom_0003/rgb_0173_rgb_left.mp4,NYUv2/test/bedroom_0003/rgb_0173_disparity.npz
+NYUv2/test/bedroom_0003/rgb_0174_rgb_left.mp4,NYUv2/test/bedroom_0003/rgb_0174_disparity.npz
+NYUv2/test/bedroom_0003/rgb_0175_rgb_left.mp4,NYUv2/test/bedroom_0003/rgb_0175_disparity.npz
+NYUv2/test/bedroom_0003/rgb_0176_rgb_left.mp4,NYUv2/test/bedroom_0003/rgb_0176_disparity.npz
+NYUv2/test/bedroom_0005/rgb_0180_rgb_left.mp4,NYUv2/test/bedroom_0005/rgb_0180_disparity.npz
+NYUv2/test/bedroom_0005/rgb_0181_rgb_left.mp4,NYUv2/test/bedroom_0005/rgb_0181_disparity.npz
+NYUv2/test/bedroom_0005/rgb_0182_rgb_left.mp4,NYUv2/test/bedroom_0005/rgb_0182_disparity.npz
+NYUv2/test/bedroom_0006/rgb_0183_rgb_left.mp4,NYUv2/test/bedroom_0006/rgb_0183_disparity.npz
+NYUv2/test/bedroom_0006/rgb_0184_rgb_left.mp4,NYUv2/test/bedroom_0006/rgb_0184_disparity.npz
+NYUv2/test/bedroom_0006/rgb_0185_rgb_left.mp4,NYUv2/test/bedroom_0006/rgb_0185_disparity.npz
+NYUv2/test/bedroom_0006/rgb_0186_rgb_left.mp4,NYUv2/test/bedroom_0006/rgb_0186_disparity.npz
+NYUv2/test/bedroom_0006/rgb_0187_rgb_left.mp4,NYUv2/test/bedroom_0006/rgb_0187_disparity.npz
+NYUv2/test/bedroom_0006/rgb_0188_rgb_left.mp4,NYUv2/test/bedroom_0006/rgb_0188_disparity.npz
+NYUv2/test/bedroom_0007/rgb_0189_rgb_left.mp4,NYUv2/test/bedroom_0007/rgb_0189_disparity.npz
+NYUv2/test/bedroom_0007/rgb_0190_rgb_left.mp4,NYUv2/test/bedroom_0007/rgb_0190_disparity.npz
+NYUv2/test/bedroom_0007/rgb_0191_rgb_left.mp4,NYUv2/test/bedroom_0007/rgb_0191_disparity.npz
+NYUv2/test/bedroom_0007/rgb_0192_rgb_left.mp4,NYUv2/test/bedroom_0007/rgb_0192_disparity.npz
+NYUv2/test/bedroom_0007/rgb_0193_rgb_left.mp4,NYUv2/test/bedroom_0007/rgb_0193_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0194_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0194_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0195_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0195_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0196_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0196_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0197_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0197_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0198_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0198_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0199_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0199_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0200_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0200_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0201_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0201_disparity.npz
+NYUv2/test/kitchen_0002/rgb_0202_rgb_left.mp4,NYUv2/test/kitchen_0002/rgb_0202_disparity.npz
+NYUv2/test/living_room_0002/rgb_0207_rgb_left.mp4,NYUv2/test/living_room_0002/rgb_0207_disparity.npz
+NYUv2/test/living_room_0003/rgb_0208_rgb_left.mp4,NYUv2/test/living_room_0003/rgb_0208_disparity.npz
+NYUv2/test/living_room_0003/rgb_0209_rgb_left.mp4,NYUv2/test/living_room_0003/rgb_0209_disparity.npz
+NYUv2/test/living_room_0003/rgb_0210_rgb_left.mp4,NYUv2/test/living_room_0003/rgb_0210_disparity.npz
+NYUv2/test/living_room_0003/rgb_0211_rgb_left.mp4,NYUv2/test/living_room_0003/rgb_0211_disparity.npz
+NYUv2/test/living_room_0003/rgb_0212_rgb_left.mp4,NYUv2/test/living_room_0003/rgb_0212_disparity.npz
+NYUv2/test/bedroom_0022/rgb_0220_rgb_left.mp4,NYUv2/test/bedroom_0022/rgb_0220_disparity.npz
+NYUv2/test/bedroom_0024/rgb_0221_rgb_left.mp4,NYUv2/test/bedroom_0024/rgb_0221_disparity.npz
+NYUv2/test/bedroom_0024/rgb_0222_rgb_left.mp4,NYUv2/test/bedroom_0024/rgb_0222_disparity.npz
+NYUv2/test/kitchen_0015/rgb_0250_rgb_left.mp4,NYUv2/test/kitchen_0015/rgb_0250_disparity.npz
+NYUv2/test/living_room_0021/rgb_0264_rgb_left.mp4,NYUv2/test/living_room_0021/rgb_0264_disparity.npz
+NYUv2/test/office_0016/rgb_0271_rgb_left.mp4,NYUv2/test/office_0016/rgb_0271_disparity.npz
+NYUv2/test/office_0017/rgb_0272_rgb_left.mp4,NYUv2/test/office_0017/rgb_0272_disparity.npz
+NYUv2/test/study_room_0001/rgb_0273_rgb_left.mp4,NYUv2/test/study_room_0001/rgb_0273_disparity.npz
+NYUv2/test/study_room_0006/rgb_0279_rgb_left.mp4,NYUv2/test/study_room_0006/rgb_0279_disparity.npz
+NYUv2/test/bedroom_0131/rgb_0280_rgb_left.mp4,NYUv2/test/bedroom_0131/rgb_0280_disparity.npz
+NYUv2/test/bedroom_0131/rgb_0281_rgb_left.mp4,NYUv2/test/bedroom_0131/rgb_0281_disparity.npz
+NYUv2/test/bedroom_0131/rgb_0282_rgb_left.mp4,NYUv2/test/bedroom_0131/rgb_0282_disparity.npz
+NYUv2/test/bedroom_0131/rgb_0283_rgb_left.mp4,NYUv2/test/bedroom_0131/rgb_0283_disparity.npz
+NYUv2/test/classroom_0001/rgb_0284_rgb_left.mp4,NYUv2/test/classroom_0001/rgb_0284_disparity.npz
+NYUv2/test/classroom_0001/rgb_0285_rgb_left.mp4,NYUv2/test/classroom_0001/rgb_0285_disparity.npz
+NYUv2/test/classroom_0007/rgb_0296_rgb_left.mp4,NYUv2/test/classroom_0007/rgb_0296_disparity.npz
+NYUv2/test/classroom_0007/rgb_0297_rgb_left.mp4,NYUv2/test/classroom_0007/rgb_0297_disparity.npz
+NYUv2/test/classroom_0007/rgb_0298_rgb_left.mp4,NYUv2/test/classroom_0007/rgb_0298_disparity.npz
+NYUv2/test/classroom_0008/rgb_0299_rgb_left.mp4,NYUv2/test/classroom_0008/rgb_0299_disparity.npz
+NYUv2/test/classroom_0008/rgb_0300_rgb_left.mp4,NYUv2/test/classroom_0008/rgb_0300_disparity.npz
+NYUv2/test/classroom_0009/rgb_0301_rgb_left.mp4,NYUv2/test/classroom_0009/rgb_0301_disparity.npz
+NYUv2/test/classroom_0009/rgb_0302_rgb_left.mp4,NYUv2/test/classroom_0009/rgb_0302_disparity.npz
+NYUv2/test/classroom_0014/rgb_0310_rgb_left.mp4,NYUv2/test/classroom_0014/rgb_0310_disparity.npz
+NYUv2/test/classroom_0014/rgb_0311_rgb_left.mp4,NYUv2/test/classroom_0014/rgb_0311_disparity.npz
+NYUv2/test/classroom_0015/rgb_0312_rgb_left.mp4,NYUv2/test/classroom_0015/rgb_0312_disparity.npz
+NYUv2/test/classroom_0017/rgb_0315_rgb_left.mp4,NYUv2/test/classroom_0017/rgb_0315_disparity.npz
+NYUv2/test/classroom_0017/rgb_0316_rgb_left.mp4,NYUv2/test/classroom_0017/rgb_0316_disparity.npz
+NYUv2/test/classroom_0017/rgb_0317_rgb_left.mp4,NYUv2/test/classroom_0017/rgb_0317_disparity.npz
+NYUv2/test/classroom_0023/rgb_0325_rgb_left.mp4,NYUv2/test/classroom_0023/rgb_0325_disparity.npz
+NYUv2/test/classroom_0023/rgb_0326_rgb_left.mp4,NYUv2/test/classroom_0023/rgb_0326_disparity.npz
+NYUv2/test/classroom_0023/rgb_0327_rgb_left.mp4,NYUv2/test/classroom_0023/rgb_0327_disparity.npz
+NYUv2/test/classroom_0023/rgb_0328_rgb_left.mp4,NYUv2/test/classroom_0023/rgb_0328_disparity.npz
+NYUv2/test/classroom_0024/rgb_0329_rgb_left.mp4,NYUv2/test/classroom_0024/rgb_0329_disparity.npz
+NYUv2/test/classroom_0024/rgb_0330_rgb_left.mp4,NYUv2/test/classroom_0024/rgb_0330_disparity.npz
+NYUv2/test/classroom_0026/rgb_0331_rgb_left.mp4,NYUv2/test/classroom_0026/rgb_0331_disparity.npz
+NYUv2/test/classroom_0026/rgb_0332_rgb_left.mp4,NYUv2/test/classroom_0026/rgb_0332_disparity.npz
+NYUv2/test/computer_lab_0001/rgb_0333_rgb_left.mp4,NYUv2/test/computer_lab_0001/rgb_0333_disparity.npz
+NYUv2/test/computer_lab_0001/rgb_0334_rgb_left.mp4,NYUv2/test/computer_lab_0001/rgb_0334_disparity.npz
+NYUv2/test/computer_lab_0001/rgb_0335_rgb_left.mp4,NYUv2/test/computer_lab_0001/rgb_0335_disparity.npz
+NYUv2/test/foyer_0001/rgb_0351_rgb_left.mp4,NYUv2/test/foyer_0001/rgb_0351_disparity.npz
+NYUv2/test/foyer_0001/rgb_0352_rgb_left.mp4,NYUv2/test/foyer_0001/rgb_0352_disparity.npz
+NYUv2/test/home_office_0001/rgb_0355_rgb_left.mp4,NYUv2/test/home_office_0001/rgb_0355_disparity.npz
+NYUv2/test/home_office_0001/rgb_0356_rgb_left.mp4,NYUv2/test/home_office_0001/rgb_0356_disparity.npz
+NYUv2/test/home_office_0001/rgb_0357_rgb_left.mp4,NYUv2/test/home_office_0001/rgb_0357_disparity.npz
+NYUv2/test/home_office_0001/rgb_0358_rgb_left.mp4,NYUv2/test/home_office_0001/rgb_0358_disparity.npz
+NYUv2/test/home_office_0002/rgb_0359_rgb_left.mp4,NYUv2/test/home_office_0002/rgb_0359_disparity.npz
+NYUv2/test/home_office_0002/rgb_0360_rgb_left.mp4,NYUv2/test/home_office_0002/rgb_0360_disparity.npz
+NYUv2/test/home_office_0002/rgb_0361_rgb_left.mp4,NYUv2/test/home_office_0002/rgb_0361_disparity.npz
+NYUv2/test/home_office_0002/rgb_0362_rgb_left.mp4,NYUv2/test/home_office_0002/rgb_0362_disparity.npz
+NYUv2/test/home_office_0003/rgb_0363_rgb_left.mp4,NYUv2/test/home_office_0003/rgb_0363_disparity.npz
+NYUv2/test/home_office_0003/rgb_0364_rgb_left.mp4,NYUv2/test/home_office_0003/rgb_0364_disparity.npz
+NYUv2/test/home_office_0009/rgb_0384_rgb_left.mp4,NYUv2/test/home_office_0009/rgb_0384_disparity.npz
+NYUv2/test/home_office_0009/rgb_0385_rgb_left.mp4,NYUv2/test/home_office_0009/rgb_0385_disparity.npz
+NYUv2/test/home_office_0009/rgb_0386_rgb_left.mp4,NYUv2/test/home_office_0009/rgb_0386_disparity.npz
+NYUv2/test/home_office_0010/rgb_0387_rgb_left.mp4,NYUv2/test/home_office_0010/rgb_0387_disparity.npz
+NYUv2/test/home_office_0010/rgb_0388_rgb_left.mp4,NYUv2/test/home_office_0010/rgb_0388_disparity.npz
+NYUv2/test/home_office_0010/rgb_0389_rgb_left.mp4,NYUv2/test/home_office_0010/rgb_0389_disparity.npz
+NYUv2/test/home_office_0010/rgb_0390_rgb_left.mp4,NYUv2/test/home_office_0010/rgb_0390_disparity.npz
+NYUv2/test/home_office_0012/rgb_0395_rgb_left.mp4,NYUv2/test/home_office_0012/rgb_0395_disparity.npz
+NYUv2/test/home_office_0012/rgb_0396_rgb_left.mp4,NYUv2/test/home_office_0012/rgb_0396_disparity.npz
+NYUv2/test/home_office_0012/rgb_0397_rgb_left.mp4,NYUv2/test/home_office_0012/rgb_0397_disparity.npz
+NYUv2/test/office_kitchen_0002/rgb_0411_rgb_left.mp4,NYUv2/test/office_kitchen_0002/rgb_0411_disparity.npz
+NYUv2/test/office_kitchen_0002/rgb_0412_rgb_left.mp4,NYUv2/test/office_kitchen_0002/rgb_0412_disparity.npz
+NYUv2/test/office_kitchen_0002/rgb_0413_rgb_left.mp4,NYUv2/test/office_kitchen_0002/rgb_0413_disparity.npz
+NYUv2/test/office_kitchen_0002/rgb_0414_rgb_left.mp4,NYUv2/test/office_kitchen_0002/rgb_0414_disparity.npz
+NYUv2/test/playroom_0005/rgb_0430_rgb_left.mp4,NYUv2/test/playroom_0005/rgb_0430_disparity.npz
+NYUv2/test/playroom_0005/rgb_0431_rgb_left.mp4,NYUv2/test/playroom_0005/rgb_0431_disparity.npz
+NYUv2/test/playroom_0005/rgb_0432_rgb_left.mp4,NYUv2/test/playroom_0005/rgb_0432_disparity.npz
+NYUv2/test/playroom_0005/rgb_0433_rgb_left.mp4,NYUv2/test/playroom_0005/rgb_0433_disparity.npz
+NYUv2/test/playroom_0005/rgb_0434_rgb_left.mp4,NYUv2/test/playroom_0005/rgb_0434_disparity.npz
+NYUv2/test/playroom_0005/rgb_0435_rgb_left.mp4,NYUv2/test/playroom_0005/rgb_0435_disparity.npz
+NYUv2/test/playroom_0007/rgb_0441_rgb_left.mp4,NYUv2/test/playroom_0007/rgb_0441_disparity.npz
+NYUv2/test/playroom_0007/rgb_0442_rgb_left.mp4,NYUv2/test/playroom_0007/rgb_0442_disparity.npz
+NYUv2/test/playroom_0007/rgb_0443_rgb_left.mp4,NYUv2/test/playroom_0007/rgb_0443_disparity.npz
+NYUv2/test/playroom_0008/rgb_0444_rgb_left.mp4,NYUv2/test/playroom_0008/rgb_0444_disparity.npz
+NYUv2/test/playroom_0008/rgb_0445_rgb_left.mp4,NYUv2/test/playroom_0008/rgb_0445_disparity.npz
+NYUv2/test/playroom_0008/rgb_0446_rgb_left.mp4,NYUv2/test/playroom_0008/rgb_0446_disparity.npz
+NYUv2/test/playroom_0008/rgb_0447_rgb_left.mp4,NYUv2/test/playroom_0008/rgb_0447_disparity.npz
+NYUv2/test/playroom_0008/rgb_0448_rgb_left.mp4,NYUv2/test/playroom_0008/rgb_0448_disparity.npz
+NYUv2/test/reception_room_0003/rgb_0462_rgb_left.mp4,NYUv2/test/reception_room_0003/rgb_0462_disparity.npz
+NYUv2/test/reception_room_0003/rgb_0463_rgb_left.mp4,NYUv2/test/reception_room_0003/rgb_0463_disparity.npz
+NYUv2/test/reception_room_0003/rgb_0464_rgb_left.mp4,NYUv2/test/reception_room_0003/rgb_0464_disparity.npz
+NYUv2/test/reception_room_0003/rgb_0465_rgb_left.mp4,NYUv2/test/reception_room_0003/rgb_0465_disparity.npz
+NYUv2/test/reception_room_0003/rgb_0466_rgb_left.mp4,NYUv2/test/reception_room_0003/rgb_0466_disparity.npz
+NYUv2/test/study_0001/rgb_0469_rgb_left.mp4,NYUv2/test/study_0001/rgb_0469_disparity.npz
+NYUv2/test/study_0001/rgb_0470_rgb_left.mp4,NYUv2/test/study_0001/rgb_0470_disparity.npz
+NYUv2/test/study_0001/rgb_0471_rgb_left.mp4,NYUv2/test/study_0001/rgb_0471_disparity.npz
+NYUv2/test/study_0001/rgb_0472_rgb_left.mp4,NYUv2/test/study_0001/rgb_0472_disparity.npz
+NYUv2/test/study_0001/rgb_0473_rgb_left.mp4,NYUv2/test/study_0001/rgb_0473_disparity.npz
+NYUv2/test/study_0002/rgb_0474_rgb_left.mp4,NYUv2/test/study_0002/rgb_0474_disparity.npz
+NYUv2/test/study_0002/rgb_0475_rgb_left.mp4,NYUv2/test/study_0002/rgb_0475_disparity.npz
+NYUv2/test/study_0002/rgb_0476_rgb_left.mp4,NYUv2/test/study_0002/rgb_0476_disparity.npz
+NYUv2/test/study_0002/rgb_0477_rgb_left.mp4,NYUv2/test/study_0002/rgb_0477_disparity.npz
+NYUv2/test/bathroom_0058/rgb_0508_rgb_left.mp4,NYUv2/test/bathroom_0058/rgb_0508_disparity.npz
+NYUv2/test/bathroom_0058/rgb_0509_rgb_left.mp4,NYUv2/test/bathroom_0058/rgb_0509_disparity.npz
+NYUv2/test/bathroom_0058/rgb_0510_rgb_left.mp4,NYUv2/test/bathroom_0058/rgb_0510_disparity.npz
+NYUv2/test/bathroom_0060/rgb_0511_rgb_left.mp4,NYUv2/test/bathroom_0060/rgb_0511_disparity.npz
+NYUv2/test/bathroom_0060/rgb_0512_rgb_left.mp4,NYUv2/test/bathroom_0060/rgb_0512_disparity.npz
+NYUv2/test/bathroom_0060/rgb_0513_rgb_left.mp4,NYUv2/test/bathroom_0060/rgb_0513_disparity.npz
+NYUv2/test/bedroom_0133/rgb_0515_rgb_left.mp4,NYUv2/test/bedroom_0133/rgb_0515_disparity.npz
+NYUv2/test/bedroom_0133/rgb_0516_rgb_left.mp4,NYUv2/test/bedroom_0133/rgb_0516_disparity.npz
+NYUv2/test/bedroom_0133/rgb_0517_rgb_left.mp4,NYUv2/test/bedroom_0133/rgb_0517_disparity.npz
+NYUv2/test/bedroom_0133/rgb_0518_rgb_left.mp4,NYUv2/test/bedroom_0133/rgb_0518_disparity.npz
+NYUv2/test/bedroom_0133/rgb_0519_rgb_left.mp4,NYUv2/test/bedroom_0133/rgb_0519_disparity.npz
+NYUv2/test/bedroom_0134/rgb_0520_rgb_left.mp4,NYUv2/test/bedroom_0134/rgb_0520_disparity.npz
+NYUv2/test/bedroom_0134/rgb_0521_rgb_left.mp4,NYUv2/test/bedroom_0134/rgb_0521_disparity.npz
+NYUv2/test/bedroom_0134/rgb_0522_rgb_left.mp4,NYUv2/test/bedroom_0134/rgb_0522_disparity.npz
+NYUv2/test/bedroom_0135/rgb_0523_rgb_left.mp4,NYUv2/test/bedroom_0135/rgb_0523_disparity.npz
+NYUv2/test/bedroom_0135/rgb_0524_rgb_left.mp4,NYUv2/test/bedroom_0135/rgb_0524_disparity.npz
+NYUv2/test/bedroom_0135/rgb_0525_rgb_left.mp4,NYUv2/test/bedroom_0135/rgb_0525_disparity.npz
+NYUv2/test/bedroom_0135/rgb_0526_rgb_left.mp4,NYUv2/test/bedroom_0135/rgb_0526_disparity.npz
+NYUv2/test/bedroom_0137/rgb_0531_rgb_left.mp4,NYUv2/test/bedroom_0137/rgb_0531_disparity.npz
+NYUv2/test/bedroom_0137/rgb_0532_rgb_left.mp4,NYUv2/test/bedroom_0137/rgb_0532_disparity.npz
+NYUv2/test/bedroom_0137/rgb_0533_rgb_left.mp4,NYUv2/test/bedroom_0137/rgb_0533_disparity.npz
+NYUv2/test/bedroom_0139/rgb_0537_rgb_left.mp4,NYUv2/test/bedroom_0139/rgb_0537_disparity.npz
+NYUv2/test/bedroom_0139/rgb_0538_rgb_left.mp4,NYUv2/test/bedroom_0139/rgb_0538_disparity.npz
+NYUv2/test/bedroom_0139/rgb_0539_rgb_left.mp4,NYUv2/test/bedroom_0139/rgb_0539_disparity.npz
+NYUv2/test/dining_room_0038/rgb_0549_rgb_left.mp4,NYUv2/test/dining_room_0038/rgb_0549_disparity.npz
+NYUv2/test/dining_room_0038/rgb_0550_rgb_left.mp4,NYUv2/test/dining_room_0038/rgb_0550_disparity.npz
+NYUv2/test/dining_room_0038/rgb_0551_rgb_left.mp4,NYUv2/test/dining_room_0038/rgb_0551_disparity.npz
+NYUv2/test/home_office_0014/rgb_0555_rgb_left.mp4,NYUv2/test/home_office_0014/rgb_0555_disparity.npz
+NYUv2/test/home_office_0014/rgb_0556_rgb_left.mp4,NYUv2/test/home_office_0014/rgb_0556_disparity.npz
+NYUv2/test/home_office_0014/rgb_0557_rgb_left.mp4,NYUv2/test/home_office_0014/rgb_0557_disparity.npz
+NYUv2/test/home_office_0014/rgb_0558_rgb_left.mp4,NYUv2/test/home_office_0014/rgb_0558_disparity.npz
+NYUv2/test/kitchen_0055/rgb_0559_rgb_left.mp4,NYUv2/test/kitchen_0055/rgb_0559_disparity.npz
+NYUv2/test/kitchen_0055/rgb_0560_rgb_left.mp4,NYUv2/test/kitchen_0055/rgb_0560_disparity.npz
+NYUv2/test/kitchen_0056/rgb_0561_rgb_left.mp4,NYUv2/test/kitchen_0056/rgb_0561_disparity.npz
+NYUv2/test/kitchen_0056/rgb_0562_rgb_left.mp4,NYUv2/test/kitchen_0056/rgb_0562_disparity.npz
+NYUv2/test/kitchen_0056/rgb_0563_rgb_left.mp4,NYUv2/test/kitchen_0056/rgb_0563_disparity.npz
+NYUv2/test/kitchen_0056/rgb_0564_rgb_left.mp4,NYUv2/test/kitchen_0056/rgb_0564_disparity.npz
+NYUv2/test/kitchen_0057/rgb_0565_rgb_left.mp4,NYUv2/test/kitchen_0057/rgb_0565_disparity.npz
+NYUv2/test/kitchen_0057/rgb_0566_rgb_left.mp4,NYUv2/test/kitchen_0057/rgb_0566_disparity.npz
+NYUv2/test/kitchen_0057/rgb_0567_rgb_left.mp4,NYUv2/test/kitchen_0057/rgb_0567_disparity.npz
+NYUv2/test/kitchen_0057/rgb_0568_rgb_left.mp4,NYUv2/test/kitchen_0057/rgb_0568_disparity.npz
+NYUv2/test/kitchen_0058/rgb_0569_rgb_left.mp4,NYUv2/test/kitchen_0058/rgb_0569_disparity.npz
+NYUv2/test/kitchen_0058/rgb_0570_rgb_left.mp4,NYUv2/test/kitchen_0058/rgb_0570_disparity.npz
+NYUv2/test/kitchen_0058/rgb_0571_rgb_left.mp4,NYUv2/test/kitchen_0058/rgb_0571_disparity.npz
+NYUv2/test/living_room_0081/rgb_0579_rgb_left.mp4,NYUv2/test/living_room_0081/rgb_0579_disparity.npz
+NYUv2/test/living_room_0081/rgb_0580_rgb_left.mp4,NYUv2/test/living_room_0081/rgb_0580_disparity.npz
+NYUv2/test/living_room_0081/rgb_0581_rgb_left.mp4,NYUv2/test/living_room_0081/rgb_0581_disparity.npz
+NYUv2/test/living_room_0081/rgb_0582_rgb_left.mp4,NYUv2/test/living_room_0081/rgb_0582_disparity.npz
+NYUv2/test/living_room_0081/rgb_0583_rgb_left.mp4,NYUv2/test/living_room_0081/rgb_0583_disparity.npz
+NYUv2/test/living_room_0084/rgb_0591_rgb_left.mp4,NYUv2/test/living_room_0084/rgb_0591_disparity.npz
+NYUv2/test/living_room_0084/rgb_0592_rgb_left.mp4,NYUv2/test/living_room_0084/rgb_0592_disparity.npz
+NYUv2/test/living_room_0084/rgb_0593_rgb_left.mp4,NYUv2/test/living_room_0084/rgb_0593_disparity.npz
+NYUv2/test/living_room_0084/rgb_0594_rgb_left.mp4,NYUv2/test/living_room_0084/rgb_0594_disparity.npz
+NYUv2/test/living_room_0087/rgb_0603_rgb_left.mp4,NYUv2/test/living_room_0087/rgb_0603_disparity.npz
+NYUv2/test/living_room_0087/rgb_0604_rgb_left.mp4,NYUv2/test/living_room_0087/rgb_0604_disparity.npz
+NYUv2/test/living_room_0087/rgb_0605_rgb_left.mp4,NYUv2/test/living_room_0087/rgb_0605_disparity.npz
+NYUv2/test/living_room_0087/rgb_0606_rgb_left.mp4,NYUv2/test/living_room_0087/rgb_0606_disparity.npz
+NYUv2/test/living_room_0087/rgb_0607_rgb_left.mp4,NYUv2/test/living_room_0087/rgb_0607_disparity.npz
+NYUv2/test/office_0020/rgb_0612_rgb_left.mp4,NYUv2/test/office_0020/rgb_0612_disparity.npz
+NYUv2/test/office_0020/rgb_0613_rgb_left.mp4,NYUv2/test/office_0020/rgb_0613_disparity.npz
+NYUv2/test/office_0022/rgb_0617_rgb_left.mp4,NYUv2/test/office_0022/rgb_0617_disparity.npz
+NYUv2/test/office_0022/rgb_0618_rgb_left.mp4,NYUv2/test/office_0022/rgb_0618_disparity.npz
+NYUv2/test/office_0022/rgb_0619_rgb_left.mp4,NYUv2/test/office_0022/rgb_0619_disparity.npz
+NYUv2/test/office_0022/rgb_0620_rgb_left.mp4,NYUv2/test/office_0022/rgb_0620_disparity.npz
+NYUv2/test/office_0022/rgb_0621_rgb_left.mp4,NYUv2/test/office_0022/rgb_0621_disparity.npz
+NYUv2/test/office_0027/rgb_0633_rgb_left.mp4,NYUv2/test/office_0027/rgb_0633_disparity.npz
+NYUv2/test/office_0027/rgb_0634_rgb_left.mp4,NYUv2/test/office_0027/rgb_0634_disparity.npz
+NYUv2/test/office_0027/rgb_0635_rgb_left.mp4,NYUv2/test/office_0027/rgb_0635_disparity.npz
+NYUv2/test/office_0027/rgb_0636_rgb_left.mp4,NYUv2/test/office_0027/rgb_0636_disparity.npz
+NYUv2/test/office_0027/rgb_0637_rgb_left.mp4,NYUv2/test/office_0027/rgb_0637_disparity.npz
+NYUv2/test/office_0027/rgb_0638_rgb_left.mp4,NYUv2/test/office_0027/rgb_0638_disparity.npz
+NYUv2/test/study_0007/rgb_0644_rgb_left.mp4,NYUv2/test/study_0007/rgb_0644_disparity.npz
+NYUv2/test/study_0007/rgb_0645_rgb_left.mp4,NYUv2/test/study_0007/rgb_0645_disparity.npz
+NYUv2/test/bathroom_0008/rgb_0650_rgb_left.mp4,NYUv2/test/bathroom_0008/rgb_0650_disparity.npz
+NYUv2/test/bathroom_0009/rgb_0651_rgb_left.mp4,NYUv2/test/bathroom_0009/rgb_0651_disparity.npz
+NYUv2/test/bathroom_0012/rgb_0656_rgb_left.mp4,NYUv2/test/bathroom_0012/rgb_0656_disparity.npz
+NYUv2/test/bathroom_0012/rgb_0657_rgb_left.mp4,NYUv2/test/bathroom_0012/rgb_0657_disparity.npz
+NYUv2/test/bathroom_0012/rgb_0658_rgb_left.mp4,NYUv2/test/bathroom_0012/rgb_0658_disparity.npz
+NYUv2/test/bathroom_0015/rgb_0663_rgb_left.mp4,NYUv2/test/bathroom_0015/rgb_0663_disparity.npz
+NYUv2/test/bathroom_0015/rgb_0664_rgb_left.mp4,NYUv2/test/bathroom_0015/rgb_0664_disparity.npz
+NYUv2/test/bathroom_0017/rgb_0668_rgb_left.mp4,NYUv2/test/bathroom_0017/rgb_0668_disparity.npz
+NYUv2/test/bathroom_0017/rgb_0669_rgb_left.mp4,NYUv2/test/bathroom_0017/rgb_0669_disparity.npz
+NYUv2/test/bathroom_0017/rgb_0670_rgb_left.mp4,NYUv2/test/bathroom_0017/rgb_0670_disparity.npz
+NYUv2/test/bathroom_0018/rgb_0671_rgb_left.mp4,NYUv2/test/bathroom_0018/rgb_0671_disparity.npz
+NYUv2/test/bathroom_0018/rgb_0672_rgb_left.mp4,NYUv2/test/bathroom_0018/rgb_0672_disparity.npz
+NYUv2/test/bathroom_0018/rgb_0673_rgb_left.mp4,NYUv2/test/bathroom_0018/rgb_0673_disparity.npz
+NYUv2/test/bathroom_0020/rgb_0676_rgb_left.mp4,NYUv2/test/bathroom_0020/rgb_0676_disparity.npz
+NYUv2/test/bathroom_0020/rgb_0677_rgb_left.mp4,NYUv2/test/bathroom_0020/rgb_0677_disparity.npz
+NYUv2/test/bathroom_0021/rgb_0678_rgb_left.mp4,NYUv2/test/bathroom_0021/rgb_0678_disparity.npz
+NYUv2/test/bathroom_0021/rgb_0679_rgb_left.mp4,NYUv2/test/bathroom_0021/rgb_0679_disparity.npz
+NYUv2/test/bathroom_0022/rgb_0680_rgb_left.mp4,NYUv2/test/bathroom_0022/rgb_0680_disparity.npz
+NYUv2/test/bathroom_0022/rgb_0681_rgb_left.mp4,NYUv2/test/bathroom_0022/rgb_0681_disparity.npz
+NYUv2/test/bathroom_0025/rgb_0686_rgb_left.mp4,NYUv2/test/bathroom_0025/rgb_0686_disparity.npz
+NYUv2/test/bathroom_0025/rgb_0687_rgb_left.mp4,NYUv2/test/bathroom_0025/rgb_0687_disparity.npz
+NYUv2/test/bathroom_0026/rgb_0688_rgb_left.mp4,NYUv2/test/bathroom_0026/rgb_0688_disparity.npz
+NYUv2/test/bathroom_0026/rgb_0689_rgb_left.mp4,NYUv2/test/bathroom_0026/rgb_0689_disparity.npz
+NYUv2/test/bathroom_0026/rgb_0690_rgb_left.mp4,NYUv2/test/bathroom_0026/rgb_0690_disparity.npz
+NYUv2/test/bathroom_0029/rgb_0693_rgb_left.mp4,NYUv2/test/bathroom_0029/rgb_0693_disparity.npz
+NYUv2/test/bathroom_0029/rgb_0694_rgb_left.mp4,NYUv2/test/bathroom_0029/rgb_0694_disparity.npz
+NYUv2/test/bathroom_0031/rgb_0697_rgb_left.mp4,NYUv2/test/bathroom_0031/rgb_0697_disparity.npz
+NYUv2/test/bathroom_0031/rgb_0698_rgb_left.mp4,NYUv2/test/bathroom_0031/rgb_0698_disparity.npz
+NYUv2/test/bathroom_0031/rgb_0699_rgb_left.mp4,NYUv2/test/bathroom_0031/rgb_0699_disparity.npz
+NYUv2/test/bathroom_0036/rgb_0706_rgb_left.mp4,NYUv2/test/bathroom_0036/rgb_0706_disparity.npz
+NYUv2/test/bathroom_0036/rgb_0707_rgb_left.mp4,NYUv2/test/bathroom_0036/rgb_0707_disparity.npz
+NYUv2/test/bathroom_0036/rgb_0708_rgb_left.mp4,NYUv2/test/bathroom_0036/rgb_0708_disparity.npz
+NYUv2/test/bathroom_0037/rgb_0709_rgb_left.mp4,NYUv2/test/bathroom_0037/rgb_0709_disparity.npz
+NYUv2/test/bathroom_0037/rgb_0710_rgb_left.mp4,NYUv2/test/bathroom_0037/rgb_0710_disparity.npz
+NYUv2/test/bathroom_0038/rgb_0711_rgb_left.mp4,NYUv2/test/bathroom_0038/rgb_0711_disparity.npz
+NYUv2/test/bathroom_0038/rgb_0712_rgb_left.mp4,NYUv2/test/bathroom_0038/rgb_0712_disparity.npz
+NYUv2/test/bathroom_0038/rgb_0713_rgb_left.mp4,NYUv2/test/bathroom_0038/rgb_0713_disparity.npz
+NYUv2/test/bathroom_0040/rgb_0717_rgb_left.mp4,NYUv2/test/bathroom_0040/rgb_0717_disparity.npz
+NYUv2/test/bathroom_0040/rgb_0718_rgb_left.mp4,NYUv2/test/bathroom_0040/rgb_0718_disparity.npz
+NYUv2/test/bathroom_0043/rgb_0724_rgb_left.mp4,NYUv2/test/bathroom_0043/rgb_0724_disparity.npz
+NYUv2/test/bathroom_0043/rgb_0725_rgb_left.mp4,NYUv2/test/bathroom_0043/rgb_0725_disparity.npz
+NYUv2/test/bathroom_0043/rgb_0726_rgb_left.mp4,NYUv2/test/bathroom_0043/rgb_0726_disparity.npz
+NYUv2/test/bathroom_0044/rgb_0727_rgb_left.mp4,NYUv2/test/bathroom_0044/rgb_0727_disparity.npz
+NYUv2/test/bathroom_0044/rgb_0728_rgb_left.mp4,NYUv2/test/bathroom_0044/rgb_0728_disparity.npz
+NYUv2/test/bathroom_0046/rgb_0731_rgb_left.mp4,NYUv2/test/bathroom_0046/rgb_0731_disparity.npz
+NYUv2/test/bathroom_0046/rgb_0732_rgb_left.mp4,NYUv2/test/bathroom_0046/rgb_0732_disparity.npz
+NYUv2/test/bathroom_0047/rgb_0733_rgb_left.mp4,NYUv2/test/bathroom_0047/rgb_0733_disparity.npz
+NYUv2/test/bathroom_0047/rgb_0734_rgb_left.mp4,NYUv2/test/bathroom_0047/rgb_0734_disparity.npz
+NYUv2/test/bathroom_0052/rgb_0743_rgb_left.mp4,NYUv2/test/bathroom_0052/rgb_0743_disparity.npz
+NYUv2/test/bathroom_0052/rgb_0744_rgb_left.mp4,NYUv2/test/bathroom_0052/rgb_0744_disparity.npz
+NYUv2/test/kitchen_0021/rgb_0759_rgb_left.mp4,NYUv2/test/kitchen_0021/rgb_0759_disparity.npz
+NYUv2/test/kitchen_0021/rgb_0760_rgb_left.mp4,NYUv2/test/kitchen_0021/rgb_0760_disparity.npz
+NYUv2/test/kitchen_0021/rgb_0761_rgb_left.mp4,NYUv2/test/kitchen_0021/rgb_0761_disparity.npz
+NYUv2/test/kitchen_0022/rgb_0762_rgb_left.mp4,NYUv2/test/kitchen_0022/rgb_0762_disparity.npz
+NYUv2/test/kitchen_0022/rgb_0763_rgb_left.mp4,NYUv2/test/kitchen_0022/rgb_0763_disparity.npz
+NYUv2/test/kitchen_0022/rgb_0764_rgb_left.mp4,NYUv2/test/kitchen_0022/rgb_0764_disparity.npz
+NYUv2/test/kitchen_0022/rgb_0765_rgb_left.mp4,NYUv2/test/kitchen_0022/rgb_0765_disparity.npz
+NYUv2/test/kitchen_0022/rgb_0766_rgb_left.mp4,NYUv2/test/kitchen_0022/rgb_0766_disparity.npz
+NYUv2/test/kitchen_0023/rgb_0767_rgb_left.mp4,NYUv2/test/kitchen_0023/rgb_0767_disparity.npz
+NYUv2/test/kitchen_0023/rgb_0768_rgb_left.mp4,NYUv2/test/kitchen_0023/rgb_0768_disparity.npz
+NYUv2/test/kitchen_0023/rgb_0769_rgb_left.mp4,NYUv2/test/kitchen_0023/rgb_0769_disparity.npz
+NYUv2/test/kitchen_0023/rgb_0770_rgb_left.mp4,NYUv2/test/kitchen_0023/rgb_0770_disparity.npz
+NYUv2/test/kitchen_0023/rgb_0771_rgb_left.mp4,NYUv2/test/kitchen_0023/rgb_0771_disparity.npz
+NYUv2/test/kitchen_0024/rgb_0772_rgb_left.mp4,NYUv2/test/kitchen_0024/rgb_0772_disparity.npz
+NYUv2/test/kitchen_0024/rgb_0773_rgb_left.mp4,NYUv2/test/kitchen_0024/rgb_0773_disparity.npz
+NYUv2/test/kitchen_0024/rgb_0774_rgb_left.mp4,NYUv2/test/kitchen_0024/rgb_0774_disparity.npz
+NYUv2/test/kitchen_0024/rgb_0775_rgb_left.mp4,NYUv2/test/kitchen_0024/rgb_0775_disparity.npz
+NYUv2/test/kitchen_0024/rgb_0776_rgb_left.mp4,NYUv2/test/kitchen_0024/rgb_0776_disparity.npz
+NYUv2/test/kitchen_0025/rgb_0777_rgb_left.mp4,NYUv2/test/kitchen_0025/rgb_0777_disparity.npz
+NYUv2/test/kitchen_0025/rgb_0778_rgb_left.mp4,NYUv2/test/kitchen_0025/rgb_0778_disparity.npz
+NYUv2/test/kitchen_0025/rgb_0779_rgb_left.mp4,NYUv2/test/kitchen_0025/rgb_0779_disparity.npz
+NYUv2/test/kitchen_0026/rgb_0780_rgb_left.mp4,NYUv2/test/kitchen_0026/rgb_0780_disparity.npz
+NYUv2/test/kitchen_0026/rgb_0781_rgb_left.mp4,NYUv2/test/kitchen_0026/rgb_0781_disparity.npz
+NYUv2/test/kitchen_0026/rgb_0782_rgb_left.mp4,NYUv2/test/kitchen_0026/rgb_0782_disparity.npz
+NYUv2/test/kitchen_0027/rgb_0783_rgb_left.mp4,NYUv2/test/kitchen_0027/rgb_0783_disparity.npz
+NYUv2/test/kitchen_0027/rgb_0784_rgb_left.mp4,NYUv2/test/kitchen_0027/rgb_0784_disparity.npz
+NYUv2/test/kitchen_0027/rgb_0785_rgb_left.mp4,NYUv2/test/kitchen_0027/rgb_0785_disparity.npz
+NYUv2/test/kitchen_0027/rgb_0786_rgb_left.mp4,NYUv2/test/kitchen_0027/rgb_0786_disparity.npz
+NYUv2/test/kitchen_0027/rgb_0787_rgb_left.mp4,NYUv2/test/kitchen_0027/rgb_0787_disparity.npz
+NYUv2/test/kitchen_0030/rgb_0800_rgb_left.mp4,NYUv2/test/kitchen_0030/rgb_0800_disparity.npz
+NYUv2/test/kitchen_0030/rgb_0801_rgb_left.mp4,NYUv2/test/kitchen_0030/rgb_0801_disparity.npz
+NYUv2/test/kitchen_0030/rgb_0802_rgb_left.mp4,NYUv2/test/kitchen_0030/rgb_0802_disparity.npz
+NYUv2/test/kitchen_0030/rgb_0803_rgb_left.mp4,NYUv2/test/kitchen_0030/rgb_0803_disparity.npz
+NYUv2/test/kitchen_0030/rgb_0804_rgb_left.mp4,NYUv2/test/kitchen_0030/rgb_0804_disparity.npz
+NYUv2/test/kitchen_0032/rgb_0810_rgb_left.mp4,NYUv2/test/kitchen_0032/rgb_0810_disparity.npz
+NYUv2/test/kitchen_0032/rgb_0811_rgb_left.mp4,NYUv2/test/kitchen_0032/rgb_0811_disparity.npz
+NYUv2/test/kitchen_0032/rgb_0812_rgb_left.mp4,NYUv2/test/kitchen_0032/rgb_0812_disparity.npz
+NYUv2/test/kitchen_0032/rgb_0813_rgb_left.mp4,NYUv2/test/kitchen_0032/rgb_0813_disparity.npz
+NYUv2/test/kitchen_0032/rgb_0814_rgb_left.mp4,NYUv2/test/kitchen_0032/rgb_0814_disparity.npz
+NYUv2/test/kitchen_0034/rgb_0821_rgb_left.mp4,NYUv2/test/kitchen_0034/rgb_0821_disparity.npz
+NYUv2/test/kitchen_0034/rgb_0822_rgb_left.mp4,NYUv2/test/kitchen_0034/rgb_0822_disparity.npz
+NYUv2/test/kitchen_0034/rgb_0823_rgb_left.mp4,NYUv2/test/kitchen_0034/rgb_0823_disparity.npz
+NYUv2/test/kitchen_0038/rgb_0833_rgb_left.mp4,NYUv2/test/kitchen_0038/rgb_0833_disparity.npz
+NYUv2/test/kitchen_0038/rgb_0834_rgb_left.mp4,NYUv2/test/kitchen_0038/rgb_0834_disparity.npz
+NYUv2/test/kitchen_0038/rgb_0835_rgb_left.mp4,NYUv2/test/kitchen_0038/rgb_0835_disparity.npz
+NYUv2/test/kitchen_0038/rgb_0836_rgb_left.mp4,NYUv2/test/kitchen_0038/rgb_0836_disparity.npz
+NYUv2/test/kitchen_0039/rgb_0837_rgb_left.mp4,NYUv2/test/kitchen_0039/rgb_0837_disparity.npz
+NYUv2/test/kitchen_0039/rgb_0838_rgb_left.mp4,NYUv2/test/kitchen_0039/rgb_0838_disparity.npz
+NYUv2/test/kitchen_0039/rgb_0839_rgb_left.mp4,NYUv2/test/kitchen_0039/rgb_0839_disparity.npz
+NYUv2/test/kitchen_0039/rgb_0840_rgb_left.mp4,NYUv2/test/kitchen_0039/rgb_0840_disparity.npz
+NYUv2/test/kitchen_0039/rgb_0841_rgb_left.mp4,NYUv2/test/kitchen_0039/rgb_0841_disparity.npz
+NYUv2/test/kitchen_0039/rgb_0842_rgb_left.mp4,NYUv2/test/kitchen_0039/rgb_0842_disparity.npz
+NYUv2/test/kitchen_0040/rgb_0843_rgb_left.mp4,NYUv2/test/kitchen_0040/rgb_0843_disparity.npz
+NYUv2/test/kitchen_0040/rgb_0844_rgb_left.mp4,NYUv2/test/kitchen_0040/rgb_0844_disparity.npz
+NYUv2/test/kitchen_0040/rgb_0845_rgb_left.mp4,NYUv2/test/kitchen_0040/rgb_0845_disparity.npz
+NYUv2/test/kitchen_0040/rgb_0846_rgb_left.mp4,NYUv2/test/kitchen_0040/rgb_0846_disparity.npz
+NYUv2/test/kitchen_0042/rgb_0850_rgb_left.mp4,NYUv2/test/kitchen_0042/rgb_0850_disparity.npz
+NYUv2/test/kitchen_0042/rgb_0851_rgb_left.mp4,NYUv2/test/kitchen_0042/rgb_0851_disparity.npz
+NYUv2/test/kitchen_0042/rgb_0852_rgb_left.mp4,NYUv2/test/kitchen_0042/rgb_0852_disparity.npz
+NYUv2/test/kitchen_0044/rgb_0857_rgb_left.mp4,NYUv2/test/kitchen_0044/rgb_0857_disparity.npz
+NYUv2/test/kitchen_0044/rgb_0858_rgb_left.mp4,NYUv2/test/kitchen_0044/rgb_0858_disparity.npz
+NYUv2/test/kitchen_0044/rgb_0859_rgb_left.mp4,NYUv2/test/kitchen_0044/rgb_0859_disparity.npz
+NYUv2/test/kitchen_0044/rgb_0860_rgb_left.mp4,NYUv2/test/kitchen_0044/rgb_0860_disparity.npz
+NYUv2/test/kitchen_0044/rgb_0861_rgb_left.mp4,NYUv2/test/kitchen_0044/rgb_0861_disparity.npz
+NYUv2/test/kitchen_0044/rgb_0862_rgb_left.mp4,NYUv2/test/kitchen_0044/rgb_0862_disparity.npz
+NYUv2/test/kitchen_0046/rgb_0869_rgb_left.mp4,NYUv2/test/kitchen_0046/rgb_0869_disparity.npz
+NYUv2/test/kitchen_0046/rgb_0870_rgb_left.mp4,NYUv2/test/kitchen_0046/rgb_0870_disparity.npz
+NYUv2/test/kitchen_0046/rgb_0871_rgb_left.mp4,NYUv2/test/kitchen_0046/rgb_0871_disparity.npz
+NYUv2/test/kitchen_0054/rgb_0906_rgb_left.mp4,NYUv2/test/kitchen_0054/rgb_0906_disparity.npz
+NYUv2/test/kitchen_0054/rgb_0907_rgb_left.mp4,NYUv2/test/kitchen_0054/rgb_0907_disparity.npz
+NYUv2/test/kitchen_0054/rgb_0908_rgb_left.mp4,NYUv2/test/kitchen_0054/rgb_0908_disparity.npz
+NYUv2/test/bedroom_0027/rgb_0917_rgb_left.mp4,NYUv2/test/bedroom_0027/rgb_0917_disparity.npz
+NYUv2/test/bedroom_0027/rgb_0918_rgb_left.mp4,NYUv2/test/bedroom_0027/rgb_0918_disparity.npz
+NYUv2/test/bedroom_0027/rgb_0919_rgb_left.mp4,NYUv2/test/bedroom_0027/rgb_0919_disparity.npz
+NYUv2/test/bedroom_0030/rgb_0926_rgb_left.mp4,NYUv2/test/bedroom_0030/rgb_0926_disparity.npz
+NYUv2/test/bedroom_0030/rgb_0927_rgb_left.mp4,NYUv2/test/bedroom_0030/rgb_0927_disparity.npz
+NYUv2/test/bedroom_0030/rgb_0928_rgb_left.mp4,NYUv2/test/bedroom_0030/rgb_0928_disparity.npz
+NYUv2/test/bedroom_0032/rgb_0932_rgb_left.mp4,NYUv2/test/bedroom_0032/rgb_0932_disparity.npz
+NYUv2/test/bedroom_0032/rgb_0933_rgb_left.mp4,NYUv2/test/bedroom_0032/rgb_0933_disparity.npz
+NYUv2/test/bedroom_0032/rgb_0934_rgb_left.mp4,NYUv2/test/bedroom_0032/rgb_0934_disparity.npz
+NYUv2/test/bedroom_0032/rgb_0935_rgb_left.mp4,NYUv2/test/bedroom_0032/rgb_0935_disparity.npz
+NYUv2/test/bedroom_0037/rgb_0945_rgb_left.mp4,NYUv2/test/bedroom_0037/rgb_0945_disparity.npz
+NYUv2/test/bedroom_0037/rgb_0946_rgb_left.mp4,NYUv2/test/bedroom_0037/rgb_0946_disparity.npz
+NYUv2/test/bedroom_0037/rgb_0947_rgb_left.mp4,NYUv2/test/bedroom_0037/rgb_0947_disparity.npz
+NYUv2/test/bedroom_0043/rgb_0959_rgb_left.mp4,NYUv2/test/bedroom_0043/rgb_0959_disparity.npz
+NYUv2/test/bedroom_0043/rgb_0960_rgb_left.mp4,NYUv2/test/bedroom_0043/rgb_0960_disparity.npz
+NYUv2/test/bedroom_0044/rgb_0961_rgb_left.mp4,NYUv2/test/bedroom_0044/rgb_0961_disparity.npz
+NYUv2/test/bedroom_0044/rgb_0962_rgb_left.mp4,NYUv2/test/bedroom_0044/rgb_0962_disparity.npz
+NYUv2/test/bedroom_0046/rgb_0965_rgb_left.mp4,NYUv2/test/bedroom_0046/rgb_0965_disparity.npz
+NYUv2/test/bedroom_0046/rgb_0966_rgb_left.mp4,NYUv2/test/bedroom_0046/rgb_0966_disparity.npz
+NYUv2/test/bedroom_0046/rgb_0967_rgb_left.mp4,NYUv2/test/bedroom_0046/rgb_0967_disparity.npz
+NYUv2/test/bedroom_0048/rgb_0970_rgb_left.mp4,NYUv2/test/bedroom_0048/rgb_0970_disparity.npz
+NYUv2/test/bedroom_0048/rgb_0971_rgb_left.mp4,NYUv2/test/bedroom_0048/rgb_0971_disparity.npz
+NYUv2/test/bedroom_0048/rgb_0972_rgb_left.mp4,NYUv2/test/bedroom_0048/rgb_0972_disparity.npz
+NYUv2/test/bedroom_0048/rgb_0973_rgb_left.mp4,NYUv2/test/bedroom_0048/rgb_0973_disparity.npz
+NYUv2/test/bedroom_0048/rgb_0974_rgb_left.mp4,NYUv2/test/bedroom_0048/rgb_0974_disparity.npz
+NYUv2/test/bedroom_0049/rgb_0975_rgb_left.mp4,NYUv2/test/bedroom_0049/rgb_0975_disparity.npz
+NYUv2/test/bedroom_0049/rgb_0976_rgb_left.mp4,NYUv2/test/bedroom_0049/rgb_0976_disparity.npz
+NYUv2/test/bedroom_0049/rgb_0977_rgb_left.mp4,NYUv2/test/bedroom_0049/rgb_0977_disparity.npz
+NYUv2/test/bedroom_0054/rgb_0991_rgb_left.mp4,NYUv2/test/bedroom_0054/rgb_0991_disparity.npz
+NYUv2/test/bedroom_0054/rgb_0992_rgb_left.mp4,NYUv2/test/bedroom_0054/rgb_0992_disparity.npz
+NYUv2/test/bedroom_0054/rgb_0993_rgb_left.mp4,NYUv2/test/bedroom_0054/rgb_0993_disparity.npz
+NYUv2/test/bedroom_0055/rgb_0994_rgb_left.mp4,NYUv2/test/bedroom_0055/rgb_0994_disparity.npz
+NYUv2/test/bedroom_0055/rgb_0995_rgb_left.mp4,NYUv2/test/bedroom_0055/rgb_0995_disparity.npz
+NYUv2/test/bedroom_0058/rgb_1001_rgb_left.mp4,NYUv2/test/bedroom_0058/rgb_1001_disparity.npz
+NYUv2/test/bedroom_0058/rgb_1002_rgb_left.mp4,NYUv2/test/bedroom_0058/rgb_1002_disparity.npz
+NYUv2/test/bedroom_0058/rgb_1003_rgb_left.mp4,NYUv2/test/bedroom_0058/rgb_1003_disparity.npz
+NYUv2/test/bedroom_0058/rgb_1004_rgb_left.mp4,NYUv2/test/bedroom_0058/rgb_1004_disparity.npz
+NYUv2/test/bedroom_0061/rgb_1010_rgb_left.mp4,NYUv2/test/bedroom_0061/rgb_1010_disparity.npz
+NYUv2/test/bedroom_0061/rgb_1011_rgb_left.mp4,NYUv2/test/bedroom_0061/rgb_1011_disparity.npz
+NYUv2/test/bedroom_0061/rgb_1012_rgb_left.mp4,NYUv2/test/bedroom_0061/rgb_1012_disparity.npz
+NYUv2/test/bedroom_0064/rgb_1021_rgb_left.mp4,NYUv2/test/bedroom_0064/rgb_1021_disparity.npz
+NYUv2/test/bedroom_0064/rgb_1022_rgb_left.mp4,NYUv2/test/bedroom_0064/rgb_1022_disparity.npz
+NYUv2/test/bedroom_0064/rgb_1023_rgb_left.mp4,NYUv2/test/bedroom_0064/rgb_1023_disparity.npz
+NYUv2/test/bedroom_0068/rgb_1032_rgb_left.mp4,NYUv2/test/bedroom_0068/rgb_1032_disparity.npz
+NYUv2/test/bedroom_0068/rgb_1033_rgb_left.mp4,NYUv2/test/bedroom_0068/rgb_1033_disparity.npz
+NYUv2/test/bedroom_0068/rgb_1034_rgb_left.mp4,NYUv2/test/bedroom_0068/rgb_1034_disparity.npz
+NYUv2/test/bedroom_0070/rgb_1038_rgb_left.mp4,NYUv2/test/bedroom_0070/rgb_1038_disparity.npz
+NYUv2/test/bedroom_0070/rgb_1039_rgb_left.mp4,NYUv2/test/bedroom_0070/rgb_1039_disparity.npz
+NYUv2/test/bedroom_0073/rgb_1048_rgb_left.mp4,NYUv2/test/bedroom_0073/rgb_1048_disparity.npz
+NYUv2/test/bedroom_0073/rgb_1049_rgb_left.mp4,NYUv2/test/bedroom_0073/rgb_1049_disparity.npz
+NYUv2/test/bedroom_0075/rgb_1052_rgb_left.mp4,NYUv2/test/bedroom_0075/rgb_1052_disparity.npz
+NYUv2/test/bedroom_0075/rgb_1053_rgb_left.mp4,NYUv2/test/bedroom_0075/rgb_1053_disparity.npz
+NYUv2/test/bedroom_0077/rgb_1057_rgb_left.mp4,NYUv2/test/bedroom_0077/rgb_1057_disparity.npz
+NYUv2/test/bedroom_0077/rgb_1058_rgb_left.mp4,NYUv2/test/bedroom_0077/rgb_1058_disparity.npz
+NYUv2/test/bedroom_0083/rgb_1075_rgb_left.mp4,NYUv2/test/bedroom_0083/rgb_1075_disparity.npz
+NYUv2/test/bedroom_0083/rgb_1076_rgb_left.mp4,NYUv2/test/bedroom_0083/rgb_1076_disparity.npz
+NYUv2/test/bedroom_0084/rgb_1077_rgb_left.mp4,NYUv2/test/bedroom_0084/rgb_1077_disparity.npz
+NYUv2/test/bedroom_0084/rgb_1078_rgb_left.mp4,NYUv2/test/bedroom_0084/rgb_1078_disparity.npz
+NYUv2/test/bedroom_0084/rgb_1079_rgb_left.mp4,NYUv2/test/bedroom_0084/rgb_1079_disparity.npz
+NYUv2/test/bedroom_0084/rgb_1080_rgb_left.mp4,NYUv2/test/bedroom_0084/rgb_1080_disparity.npz
+NYUv2/test/bedroom_0085/rgb_1081_rgb_left.mp4,NYUv2/test/bedroom_0085/rgb_1081_disparity.npz
+NYUv2/test/bedroom_0085/rgb_1082_rgb_left.mp4,NYUv2/test/bedroom_0085/rgb_1082_disparity.npz
+NYUv2/test/bedroom_0085/rgb_1083_rgb_left.mp4,NYUv2/test/bedroom_0085/rgb_1083_disparity.npz
+NYUv2/test/bedroom_0085/rgb_1084_rgb_left.mp4,NYUv2/test/bedroom_0085/rgb_1084_disparity.npz
+NYUv2/test/bedroom_0087/rgb_1088_rgb_left.mp4,NYUv2/test/bedroom_0087/rgb_1088_disparity.npz
+NYUv2/test/bedroom_0087/rgb_1089_rgb_left.mp4,NYUv2/test/bedroom_0087/rgb_1089_disparity.npz
+NYUv2/test/bedroom_0087/rgb_1090_rgb_left.mp4,NYUv2/test/bedroom_0087/rgb_1090_disparity.npz
+NYUv2/test/bedroom_0088/rgb_1091_rgb_left.mp4,NYUv2/test/bedroom_0088/rgb_1091_disparity.npz
+NYUv2/test/bedroom_0088/rgb_1092_rgb_left.mp4,NYUv2/test/bedroom_0088/rgb_1092_disparity.npz
+NYUv2/test/bedroom_0088/rgb_1093_rgb_left.mp4,NYUv2/test/bedroom_0088/rgb_1093_disparity.npz
+NYUv2/test/bedroom_0089/rgb_1094_rgb_left.mp4,NYUv2/test/bedroom_0089/rgb_1094_disparity.npz
+NYUv2/test/bedroom_0089/rgb_1095_rgb_left.mp4,NYUv2/test/bedroom_0089/rgb_1095_disparity.npz
+NYUv2/test/bedroom_0089/rgb_1096_rgb_left.mp4,NYUv2/test/bedroom_0089/rgb_1096_disparity.npz
+NYUv2/test/bedroom_0091/rgb_1098_rgb_left.mp4,NYUv2/test/bedroom_0091/rgb_1098_disparity.npz
+NYUv2/test/bedroom_0091/rgb_1099_rgb_left.mp4,NYUv2/test/bedroom_0091/rgb_1099_disparity.npz
+NYUv2/test/bedroom_0092/rgb_1100_rgb_left.mp4,NYUv2/test/bedroom_0092/rgb_1100_disparity.npz
+NYUv2/test/bedroom_0092/rgb_1101_rgb_left.mp4,NYUv2/test/bedroom_0092/rgb_1101_disparity.npz
+NYUv2/test/bedroom_0092/rgb_1102_rgb_left.mp4,NYUv2/test/bedroom_0092/rgb_1102_disparity.npz
+NYUv2/test/bedroom_0093/rgb_1103_rgb_left.mp4,NYUv2/test/bedroom_0093/rgb_1103_disparity.npz
+NYUv2/test/bedroom_0093/rgb_1104_rgb_left.mp4,NYUv2/test/bedroom_0093/rgb_1104_disparity.npz
+NYUv2/test/bedroom_0095/rgb_1106_rgb_left.mp4,NYUv2/test/bedroom_0095/rgb_1106_disparity.npz
+NYUv2/test/bedroom_0095/rgb_1107_rgb_left.mp4,NYUv2/test/bedroom_0095/rgb_1107_disparity.npz
+NYUv2/test/bedroom_0095/rgb_1108_rgb_left.mp4,NYUv2/test/bedroom_0095/rgb_1108_disparity.npz
+NYUv2/test/bedroom_0095/rgb_1109_rgb_left.mp4,NYUv2/test/bedroom_0095/rgb_1109_disparity.npz
+NYUv2/test/bedroom_0099/rgb_1117_rgb_left.mp4,NYUv2/test/bedroom_0099/rgb_1117_disparity.npz
+NYUv2/test/bedroom_0099/rgb_1118_rgb_left.mp4,NYUv2/test/bedroom_0099/rgb_1118_disparity.npz
+NYUv2/test/bedroom_0099/rgb_1119_rgb_left.mp4,NYUv2/test/bedroom_0099/rgb_1119_disparity.npz
+NYUv2/test/bedroom_0101/rgb_1123_rgb_left.mp4,NYUv2/test/bedroom_0101/rgb_1123_disparity.npz
+NYUv2/test/bedroom_0101/rgb_1124_rgb_left.mp4,NYUv2/test/bedroom_0101/rgb_1124_disparity.npz
+NYUv2/test/bedroom_0101/rgb_1125_rgb_left.mp4,NYUv2/test/bedroom_0101/rgb_1125_disparity.npz
+NYUv2/test/bedroom_0101/rgb_1126_rgb_left.mp4,NYUv2/test/bedroom_0101/rgb_1126_disparity.npz
+NYUv2/test/bedroom_0102/rgb_1127_rgb_left.mp4,NYUv2/test/bedroom_0102/rgb_1127_disparity.npz
+NYUv2/test/bedroom_0102/rgb_1128_rgb_left.mp4,NYUv2/test/bedroom_0102/rgb_1128_disparity.npz
+NYUv2/test/bedroom_0103/rgb_1129_rgb_left.mp4,NYUv2/test/bedroom_0103/rgb_1129_disparity.npz
+NYUv2/test/bedroom_0103/rgb_1130_rgb_left.mp4,NYUv2/test/bedroom_0103/rgb_1130_disparity.npz
+NYUv2/test/bedroom_0103/rgb_1131_rgb_left.mp4,NYUv2/test/bedroom_0103/rgb_1131_disparity.npz
+NYUv2/test/bedroom_0105/rgb_1135_rgb_left.mp4,NYUv2/test/bedroom_0105/rgb_1135_disparity.npz
+NYUv2/test/bedroom_0105/rgb_1136_rgb_left.mp4,NYUv2/test/bedroom_0105/rgb_1136_disparity.npz
+NYUv2/test/bedroom_0108/rgb_1144_rgb_left.mp4,NYUv2/test/bedroom_0108/rgb_1144_disparity.npz
+NYUv2/test/bedroom_0108/rgb_1145_rgb_left.mp4,NYUv2/test/bedroom_0108/rgb_1145_disparity.npz
+NYUv2/test/bedroom_0108/rgb_1146_rgb_left.mp4,NYUv2/test/bedroom_0108/rgb_1146_disparity.npz
+NYUv2/test/bedroom_0109/rgb_1147_rgb_left.mp4,NYUv2/test/bedroom_0109/rgb_1147_disparity.npz
+NYUv2/test/bedroom_0109/rgb_1148_rgb_left.mp4,NYUv2/test/bedroom_0109/rgb_1148_disparity.npz
+NYUv2/test/bedroom_0109/rgb_1149_rgb_left.mp4,NYUv2/test/bedroom_0109/rgb_1149_disparity.npz
+NYUv2/test/bedroom_0110/rgb_1150_rgb_left.mp4,NYUv2/test/bedroom_0110/rgb_1150_disparity.npz
+NYUv2/test/bedroom_0110/rgb_1151_rgb_left.mp4,NYUv2/test/bedroom_0110/rgb_1151_disparity.npz
+NYUv2/test/bedroom_0110/rgb_1152_rgb_left.mp4,NYUv2/test/bedroom_0110/rgb_1152_disparity.npz
+NYUv2/test/bedroom_0111/rgb_1153_rgb_left.mp4,NYUv2/test/bedroom_0111/rgb_1153_disparity.npz
+NYUv2/test/bedroom_0111/rgb_1154_rgb_left.mp4,NYUv2/test/bedroom_0111/rgb_1154_disparity.npz
+NYUv2/test/bedroom_0111/rgb_1155_rgb_left.mp4,NYUv2/test/bedroom_0111/rgb_1155_disparity.npz
+NYUv2/test/bedroom_0112/rgb_1156_rgb_left.mp4,NYUv2/test/bedroom_0112/rgb_1156_disparity.npz
+NYUv2/test/bedroom_0112/rgb_1157_rgb_left.mp4,NYUv2/test/bedroom_0112/rgb_1157_disparity.npz
+NYUv2/test/bedroom_0112/rgb_1158_rgb_left.mp4,NYUv2/test/bedroom_0112/rgb_1158_disparity.npz
+NYUv2/test/bedroom_0114/rgb_1162_rgb_left.mp4,NYUv2/test/bedroom_0114/rgb_1162_disparity.npz
+NYUv2/test/bedroom_0114/rgb_1163_rgb_left.mp4,NYUv2/test/bedroom_0114/rgb_1163_disparity.npz
+NYUv2/test/bedroom_0114/rgb_1164_rgb_left.mp4,NYUv2/test/bedroom_0114/rgb_1164_disparity.npz
+NYUv2/test/bedroom_0115/rgb_1165_rgb_left.mp4,NYUv2/test/bedroom_0115/rgb_1165_disparity.npz
+NYUv2/test/bedroom_0115/rgb_1166_rgb_left.mp4,NYUv2/test/bedroom_0115/rgb_1166_disparity.npz
+NYUv2/test/bedroom_0115/rgb_1167_rgb_left.mp4,NYUv2/test/bedroom_0115/rgb_1167_disparity.npz
+NYUv2/test/bedroom_0117/rgb_1170_rgb_left.mp4,NYUv2/test/bedroom_0117/rgb_1170_disparity.npz
+NYUv2/test/bedroom_0117/rgb_1171_rgb_left.mp4,NYUv2/test/bedroom_0117/rgb_1171_disparity.npz
+NYUv2/test/bedroom_0119/rgb_1174_rgb_left.mp4,NYUv2/test/bedroom_0119/rgb_1174_disparity.npz
+NYUv2/test/bedroom_0119/rgb_1175_rgb_left.mp4,NYUv2/test/bedroom_0119/rgb_1175_disparity.npz
+NYUv2/test/bedroom_0119/rgb_1176_rgb_left.mp4,NYUv2/test/bedroom_0119/rgb_1176_disparity.npz
+NYUv2/test/bedroom_0121/rgb_1179_rgb_left.mp4,NYUv2/test/bedroom_0121/rgb_1179_disparity.npz
+NYUv2/test/bedroom_0121/rgb_1180_rgb_left.mp4,NYUv2/test/bedroom_0121/rgb_1180_disparity.npz
+NYUv2/test/bedroom_0122/rgb_1181_rgb_left.mp4,NYUv2/test/bedroom_0122/rgb_1181_disparity.npz
+NYUv2/test/bedroom_0122/rgb_1182_rgb_left.mp4,NYUv2/test/bedroom_0122/rgb_1182_disparity.npz
+NYUv2/test/bedroom_0123/rgb_1183_rgb_left.mp4,NYUv2/test/bedroom_0123/rgb_1183_disparity.npz
+NYUv2/test/bedroom_0123/rgb_1184_rgb_left.mp4,NYUv2/test/bedroom_0123/rgb_1184_disparity.npz
+NYUv2/test/bedroom_0127/rgb_1192_rgb_left.mp4,NYUv2/test/bedroom_0127/rgb_1192_disparity.npz
+NYUv2/test/bedroom_0127/rgb_1193_rgb_left.mp4,NYUv2/test/bedroom_0127/rgb_1193_disparity.npz
+NYUv2/test/bedroom_0127/rgb_1194_rgb_left.mp4,NYUv2/test/bedroom_0127/rgb_1194_disparity.npz
+NYUv2/test/bedroom_0128/rgb_1195_rgb_left.mp4,NYUv2/test/bedroom_0128/rgb_1195_disparity.npz
+NYUv2/test/bedroom_0128/rgb_1196_rgb_left.mp4,NYUv2/test/bedroom_0128/rgb_1196_disparity.npz
+NYUv2/test/living_room_0025/rgb_1201_rgb_left.mp4,NYUv2/test/living_room_0025/rgb_1201_disparity.npz
+NYUv2/test/living_room_0025/rgb_1202_rgb_left.mp4,NYUv2/test/living_room_0025/rgb_1202_disparity.npz
+NYUv2/test/living_room_0025/rgb_1203_rgb_left.mp4,NYUv2/test/living_room_0025/rgb_1203_disparity.npz
+NYUv2/test/living_room_0026/rgb_1204_rgb_left.mp4,NYUv2/test/living_room_0026/rgb_1204_disparity.npz
+NYUv2/test/living_room_0026/rgb_1205_rgb_left.mp4,NYUv2/test/living_room_0026/rgb_1205_disparity.npz
+NYUv2/test/living_room_0027/rgb_1206_rgb_left.mp4,NYUv2/test/living_room_0027/rgb_1206_disparity.npz
+NYUv2/test/living_room_0027/rgb_1207_rgb_left.mp4,NYUv2/test/living_room_0027/rgb_1207_disparity.npz
+NYUv2/test/living_room_0027/rgb_1208_rgb_left.mp4,NYUv2/test/living_room_0027/rgb_1208_disparity.npz
+NYUv2/test/living_room_0028/rgb_1209_rgb_left.mp4,NYUv2/test/living_room_0028/rgb_1209_disparity.npz
+NYUv2/test/living_room_0028/rgb_1210_rgb_left.mp4,NYUv2/test/living_room_0028/rgb_1210_disparity.npz
+NYUv2/test/living_room_0028/rgb_1211_rgb_left.mp4,NYUv2/test/living_room_0028/rgb_1211_disparity.npz
+NYUv2/test/living_room_0028/rgb_1212_rgb_left.mp4,NYUv2/test/living_room_0028/rgb_1212_disparity.npz
+NYUv2/test/living_room_0030/rgb_1216_rgb_left.mp4,NYUv2/test/living_room_0030/rgb_1216_disparity.npz
+NYUv2/test/living_room_0030/rgb_1217_rgb_left.mp4,NYUv2/test/living_room_0030/rgb_1217_disparity.npz
+NYUv2/test/living_room_0031/rgb_1218_rgb_left.mp4,NYUv2/test/living_room_0031/rgb_1218_disparity.npz
+NYUv2/test/living_room_0031/rgb_1219_rgb_left.mp4,NYUv2/test/living_room_0031/rgb_1219_disparity.npz
+NYUv2/test/living_room_0031/rgb_1220_rgb_left.mp4,NYUv2/test/living_room_0031/rgb_1220_disparity.npz
+NYUv2/test/living_room_0034/rgb_1226_rgb_left.mp4,NYUv2/test/living_room_0034/rgb_1226_disparity.npz
+NYUv2/test/living_room_0034/rgb_1227_rgb_left.mp4,NYUv2/test/living_room_0034/rgb_1227_disparity.npz
+NYUv2/test/living_room_0034/rgb_1228_rgb_left.mp4,NYUv2/test/living_room_0034/rgb_1228_disparity.npz
+NYUv2/test/living_room_0034/rgb_1229_rgb_left.mp4,NYUv2/test/living_room_0034/rgb_1229_disparity.npz
+NYUv2/test/living_room_0034/rgb_1230_rgb_left.mp4,NYUv2/test/living_room_0034/rgb_1230_disparity.npz
+NYUv2/test/living_room_0036/rgb_1233_rgb_left.mp4,NYUv2/test/living_room_0036/rgb_1233_disparity.npz
+NYUv2/test/living_room_0036/rgb_1234_rgb_left.mp4,NYUv2/test/living_room_0036/rgb_1234_disparity.npz
+NYUv2/test/living_room_0036/rgb_1235_rgb_left.mp4,NYUv2/test/living_room_0036/rgb_1235_disparity.npz
+NYUv2/test/living_room_0041/rgb_1247_rgb_left.mp4,NYUv2/test/living_room_0041/rgb_1247_disparity.npz
+NYUv2/test/living_room_0041/rgb_1248_rgb_left.mp4,NYUv2/test/living_room_0041/rgb_1248_disparity.npz
+NYUv2/test/living_room_0041/rgb_1249_rgb_left.mp4,NYUv2/test/living_room_0041/rgb_1249_disparity.npz
+NYUv2/test/living_room_0041/rgb_1250_rgb_left.mp4,NYUv2/test/living_room_0041/rgb_1250_disparity.npz
+NYUv2/test/living_room_0043/rgb_1254_rgb_left.mp4,NYUv2/test/living_room_0043/rgb_1254_disparity.npz
+NYUv2/test/living_room_0043/rgb_1255_rgb_left.mp4,NYUv2/test/living_room_0043/rgb_1255_disparity.npz
+NYUv2/test/living_room_0043/rgb_1256_rgb_left.mp4,NYUv2/test/living_room_0043/rgb_1256_disparity.npz
+NYUv2/test/living_room_0043/rgb_1257_rgb_left.mp4,NYUv2/test/living_room_0043/rgb_1257_disparity.npz
+NYUv2/test/living_room_0044/rgb_1258_rgb_left.mp4,NYUv2/test/living_room_0044/rgb_1258_disparity.npz
+NYUv2/test/living_room_0044/rgb_1259_rgb_left.mp4,NYUv2/test/living_room_0044/rgb_1259_disparity.npz
+NYUv2/test/living_room_0044/rgb_1260_rgb_left.mp4,NYUv2/test/living_room_0044/rgb_1260_disparity.npz
+NYUv2/test/living_room_0044/rgb_1261_rgb_left.mp4,NYUv2/test/living_room_0044/rgb_1261_disparity.npz
+NYUv2/test/living_room_0045/rgb_1262_rgb_left.mp4,NYUv2/test/living_room_0045/rgb_1262_disparity.npz
+NYUv2/test/living_room_0045/rgb_1263_rgb_left.mp4,NYUv2/test/living_room_0045/rgb_1263_disparity.npz
+NYUv2/test/living_room_0045/rgb_1264_rgb_left.mp4,NYUv2/test/living_room_0045/rgb_1264_disparity.npz
+NYUv2/test/living_room_0045/rgb_1265_rgb_left.mp4,NYUv2/test/living_room_0045/rgb_1265_disparity.npz
+NYUv2/test/living_room_0048/rgb_1275_rgb_left.mp4,NYUv2/test/living_room_0048/rgb_1275_disparity.npz
+NYUv2/test/living_room_0048/rgb_1276_rgb_left.mp4,NYUv2/test/living_room_0048/rgb_1276_disparity.npz
+NYUv2/test/living_room_0049/rgb_1277_rgb_left.mp4,NYUv2/test/living_room_0049/rgb_1277_disparity.npz
+NYUv2/test/living_room_0049/rgb_1278_rgb_left.mp4,NYUv2/test/living_room_0049/rgb_1278_disparity.npz
+NYUv2/test/living_room_0049/rgb_1279_rgb_left.mp4,NYUv2/test/living_room_0049/rgb_1279_disparity.npz
+NYUv2/test/living_room_0049/rgb_1280_rgb_left.mp4,NYUv2/test/living_room_0049/rgb_1280_disparity.npz
+NYUv2/test/living_room_0051/rgb_1285_rgb_left.mp4,NYUv2/test/living_room_0051/rgb_1285_disparity.npz
+NYUv2/test/living_room_0051/rgb_1286_rgb_left.mp4,NYUv2/test/living_room_0051/rgb_1286_disparity.npz
+NYUv2/test/living_room_0051/rgb_1287_rgb_left.mp4,NYUv2/test/living_room_0051/rgb_1287_disparity.npz
+NYUv2/test/living_room_0051/rgb_1288_rgb_left.mp4,NYUv2/test/living_room_0051/rgb_1288_disparity.npz
+NYUv2/test/living_room_0052/rgb_1289_rgb_left.mp4,NYUv2/test/living_room_0052/rgb_1289_disparity.npz
+NYUv2/test/living_room_0052/rgb_1290_rgb_left.mp4,NYUv2/test/living_room_0052/rgb_1290_disparity.npz
+NYUv2/test/living_room_0053/rgb_1291_rgb_left.mp4,NYUv2/test/living_room_0053/rgb_1291_disparity.npz
+NYUv2/test/living_room_0053/rgb_1292_rgb_left.mp4,NYUv2/test/living_room_0053/rgb_1292_disparity.npz
+NYUv2/test/living_room_0053/rgb_1293_rgb_left.mp4,NYUv2/test/living_room_0053/rgb_1293_disparity.npz
+NYUv2/test/living_room_0054/rgb_1294_rgb_left.mp4,NYUv2/test/living_room_0054/rgb_1294_disparity.npz
+NYUv2/test/living_room_0054/rgb_1295_rgb_left.mp4,NYUv2/test/living_room_0054/rgb_1295_disparity.npz
+NYUv2/test/living_room_0056/rgb_1297_rgb_left.mp4,NYUv2/test/living_room_0056/rgb_1297_disparity.npz
+NYUv2/test/living_room_0057/rgb_1298_rgb_left.mp4,NYUv2/test/living_room_0057/rgb_1298_disparity.npz
+NYUv2/test/living_room_0057/rgb_1299_rgb_left.mp4,NYUv2/test/living_room_0057/rgb_1299_disparity.npz
+NYUv2/test/living_room_0059/rgb_1302_rgb_left.mp4,NYUv2/test/living_room_0059/rgb_1302_disparity.npz
+NYUv2/test/living_room_0059/rgb_1303_rgb_left.mp4,NYUv2/test/living_room_0059/rgb_1303_disparity.npz
+NYUv2/test/living_room_0059/rgb_1304_rgb_left.mp4,NYUv2/test/living_room_0059/rgb_1304_disparity.npz
+NYUv2/test/living_room_0059/rgb_1305_rgb_left.mp4,NYUv2/test/living_room_0059/rgb_1305_disparity.npz
+NYUv2/test/living_room_0060/rgb_1306_rgb_left.mp4,NYUv2/test/living_room_0060/rgb_1306_disparity.npz
+NYUv2/test/living_room_0060/rgb_1307_rgb_left.mp4,NYUv2/test/living_room_0060/rgb_1307_disparity.npz
+NYUv2/test/living_room_0061/rgb_1308_rgb_left.mp4,NYUv2/test/living_room_0061/rgb_1308_disparity.npz
+NYUv2/test/living_room_0064/rgb_1314_rgb_left.mp4,NYUv2/test/living_room_0064/rgb_1314_disparity.npz
+NYUv2/test/living_room_0066/rgb_1315_rgb_left.mp4,NYUv2/test/living_room_0066/rgb_1315_disparity.npz
+NYUv2/test/living_room_0072/rgb_1329_rgb_left.mp4,NYUv2/test/living_room_0072/rgb_1329_disparity.npz
+NYUv2/test/living_room_0075/rgb_1330_rgb_left.mp4,NYUv2/test/living_room_0075/rgb_1330_disparity.npz
+NYUv2/test/living_room_0075/rgb_1331_rgb_left.mp4,NYUv2/test/living_room_0075/rgb_1331_disparity.npz
+NYUv2/test/living_room_0076/rgb_1332_rgb_left.mp4,NYUv2/test/living_room_0076/rgb_1332_disparity.npz
+NYUv2/test/living_room_0079/rgb_1335_rgb_left.mp4,NYUv2/test/living_room_0079/rgb_1335_disparity.npz
+NYUv2/test/living_room_0079/rgb_1336_rgb_left.mp4,NYUv2/test/living_room_0079/rgb_1336_disparity.npz
+NYUv2/test/living_room_0079/rgb_1337_rgb_left.mp4,NYUv2/test/living_room_0079/rgb_1337_disparity.npz
+NYUv2/test/living_room_0080/rgb_1338_rgb_left.mp4,NYUv2/test/living_room_0080/rgb_1338_disparity.npz
+NYUv2/test/living_room_0080/rgb_1339_rgb_left.mp4,NYUv2/test/living_room_0080/rgb_1339_disparity.npz
+NYUv2/test/living_room_0080/rgb_1340_rgb_left.mp4,NYUv2/test/living_room_0080/rgb_1340_disparity.npz
+NYUv2/test/dining_room_0003/rgb_1347_rgb_left.mp4,NYUv2/test/dining_room_0003/rgb_1347_disparity.npz
+NYUv2/test/dining_room_0003/rgb_1348_rgb_left.mp4,NYUv2/test/dining_room_0003/rgb_1348_disparity.npz
+NYUv2/test/dining_room_0003/rgb_1349_rgb_left.mp4,NYUv2/test/dining_room_0003/rgb_1349_disparity.npz
+NYUv2/test/dining_room_0005/rgb_1353_rgb_left.mp4,NYUv2/test/dining_room_0005/rgb_1353_disparity.npz
+NYUv2/test/dining_room_0005/rgb_1354_rgb_left.mp4,NYUv2/test/dining_room_0005/rgb_1354_disparity.npz
+NYUv2/test/dining_room_0006/rgb_1355_rgb_left.mp4,NYUv2/test/dining_room_0006/rgb_1355_disparity.npz
+NYUv2/test/dining_room_0006/rgb_1356_rgb_left.mp4,NYUv2/test/dining_room_0006/rgb_1356_disparity.npz
+NYUv2/test/dining_room_0009/rgb_1364_rgb_left.mp4,NYUv2/test/dining_room_0009/rgb_1364_disparity.npz
+NYUv2/test/dining_room_0009/rgb_1365_rgb_left.mp4,NYUv2/test/dining_room_0009/rgb_1365_disparity.npz
+NYUv2/test/dining_room_0011/rgb_1368_rgb_left.mp4,NYUv2/test/dining_room_0011/rgb_1368_disparity.npz
+NYUv2/test/dining_room_0011/rgb_1369_rgb_left.mp4,NYUv2/test/dining_room_0011/rgb_1369_disparity.npz
+NYUv2/test/dining_room_0017/rgb_1384_rgb_left.mp4,NYUv2/test/dining_room_0017/rgb_1384_disparity.npz
+NYUv2/test/dining_room_0017/rgb_1385_rgb_left.mp4,NYUv2/test/dining_room_0017/rgb_1385_disparity.npz
+NYUv2/test/dining_room_0017/rgb_1386_rgb_left.mp4,NYUv2/test/dining_room_0017/rgb_1386_disparity.npz
+NYUv2/test/dining_room_0018/rgb_1387_rgb_left.mp4,NYUv2/test/dining_room_0018/rgb_1387_disparity.npz
+NYUv2/test/dining_room_0018/rgb_1388_rgb_left.mp4,NYUv2/test/dining_room_0018/rgb_1388_disparity.npz
+NYUv2/test/dining_room_0018/rgb_1389_rgb_left.mp4,NYUv2/test/dining_room_0018/rgb_1389_disparity.npz
+NYUv2/test/dining_room_0018/rgb_1390_rgb_left.mp4,NYUv2/test/dining_room_0018/rgb_1390_disparity.npz
+NYUv2/test/dining_room_0018/rgb_1391_rgb_left.mp4,NYUv2/test/dining_room_0018/rgb_1391_disparity.npz
+NYUv2/test/dining_room_0020/rgb_1394_rgb_left.mp4,NYUv2/test/dining_room_0020/rgb_1394_disparity.npz
+NYUv2/test/dining_room_0020/rgb_1395_rgb_left.mp4,NYUv2/test/dining_room_0020/rgb_1395_disparity.npz
+NYUv2/test/dining_room_0020/rgb_1396_rgb_left.mp4,NYUv2/test/dining_room_0020/rgb_1396_disparity.npz
+NYUv2/test/dining_room_0021/rgb_1397_rgb_left.mp4,NYUv2/test/dining_room_0021/rgb_1397_disparity.npz
+NYUv2/test/dining_room_0021/rgb_1398_rgb_left.mp4,NYUv2/test/dining_room_0021/rgb_1398_disparity.npz
+NYUv2/test/dining_room_0021/rgb_1399_rgb_left.mp4,NYUv2/test/dining_room_0021/rgb_1399_disparity.npz
+NYUv2/test/dining_room_0022/rgb_1400_rgb_left.mp4,NYUv2/test/dining_room_0022/rgb_1400_disparity.npz
+NYUv2/test/dining_room_0022/rgb_1401_rgb_left.mp4,NYUv2/test/dining_room_0022/rgb_1401_disparity.npz
+NYUv2/test/dining_room_0025/rgb_1407_rgb_left.mp4,NYUv2/test/dining_room_0025/rgb_1407_disparity.npz
+NYUv2/test/dining_room_0025/rgb_1408_rgb_left.mp4,NYUv2/test/dining_room_0025/rgb_1408_disparity.npz
+NYUv2/test/dining_room_0025/rgb_1409_rgb_left.mp4,NYUv2/test/dining_room_0025/rgb_1409_disparity.npz
+NYUv2/test/dining_room_0025/rgb_1410_rgb_left.mp4,NYUv2/test/dining_room_0025/rgb_1410_disparity.npz
+NYUv2/test/dining_room_0025/rgb_1411_rgb_left.mp4,NYUv2/test/dining_room_0025/rgb_1411_disparity.npz
+NYUv2/test/dining_room_0026/rgb_1412_rgb_left.mp4,NYUv2/test/dining_room_0026/rgb_1412_disparity.npz
+NYUv2/test/dining_room_0026/rgb_1413_rgb_left.mp4,NYUv2/test/dining_room_0026/rgb_1413_disparity.npz
+NYUv2/test/dining_room_0026/rgb_1414_rgb_left.mp4,NYUv2/test/dining_room_0026/rgb_1414_disparity.npz
+NYUv2/test/dining_room_0030/rgb_1421_rgb_left.mp4,NYUv2/test/dining_room_0030/rgb_1421_disparity.npz
+NYUv2/test/dining_room_0030/rgb_1422_rgb_left.mp4,NYUv2/test/dining_room_0030/rgb_1422_disparity.npz
+NYUv2/test/dining_room_0030/rgb_1423_rgb_left.mp4,NYUv2/test/dining_room_0030/rgb_1423_disparity.npz
+NYUv2/test/dining_room_0030/rgb_1424_rgb_left.mp4,NYUv2/test/dining_room_0030/rgb_1424_disparity.npz
+NYUv2/test/dining_room_0032/rgb_1430_rgb_left.mp4,NYUv2/test/dining_room_0032/rgb_1430_disparity.npz
+NYUv2/test/dining_room_0032/rgb_1431_rgb_left.mp4,NYUv2/test/dining_room_0032/rgb_1431_disparity.npz
+NYUv2/test/dining_room_0032/rgb_1432_rgb_left.mp4,NYUv2/test/dining_room_0032/rgb_1432_disparity.npz
+NYUv2/test/dining_room_0032/rgb_1433_rgb_left.mp4,NYUv2/test/dining_room_0032/rgb_1433_disparity.npz
+NYUv2/test/dining_room_0035/rgb_1441_rgb_left.mp4,NYUv2/test/dining_room_0035/rgb_1441_disparity.npz
+NYUv2/test/dining_room_0035/rgb_1442_rgb_left.mp4,NYUv2/test/dining_room_0035/rgb_1442_disparity.npz
+NYUv2/test/dining_room_0035/rgb_1443_rgb_left.mp4,NYUv2/test/dining_room_0035/rgb_1443_disparity.npz
+NYUv2/test/dining_room_0036/rgb_1444_rgb_left.mp4,NYUv2/test/dining_room_0036/rgb_1444_disparity.npz
+NYUv2/test/dining_room_0036/rgb_1445_rgb_left.mp4,NYUv2/test/dining_room_0036/rgb_1445_disparity.npz
+NYUv2/test/dining_room_0036/rgb_1446_rgb_left.mp4,NYUv2/test/dining_room_0036/rgb_1446_disparity.npz
+NYUv2/test/dining_room_0036/rgb_1447_rgb_left.mp4,NYUv2/test/dining_room_0036/rgb_1447_disparity.npz
+NYUv2/test/dining_room_0036/rgb_1448_rgb_left.mp4,NYUv2/test/dining_room_0036/rgb_1448_disparity.npz
+NYUv2/test/dining_room_0036/rgb_1449_rgb_left.mp4,NYUv2/test/dining_room_0036/rgb_1449_disparity.npz

benchmark/csv/meta_scannet_test.csv

@@ -0,0 +1,101 @@
+filepath_left,filepath_disparity
+scannet/scene0707_00_rgb_left.mp4,scannet/scene0707_00_disparity.npz
+scannet/scene0708_00_rgb_left.mp4,scannet/scene0708_00_disparity.npz
+scannet/scene0709_00_rgb_left.mp4,scannet/scene0709_00_disparity.npz
+scannet/scene0710_00_rgb_left.mp4,scannet/scene0710_00_disparity.npz
+scannet/scene0711_00_rgb_left.mp4,scannet/scene0711_00_disparity.npz
+scannet/scene0712_00_rgb_left.mp4,scannet/scene0712_00_disparity.npz
+scannet/scene0713_00_rgb_left.mp4,scannet/scene0713_00_disparity.npz
+scannet/scene0714_00_rgb_left.mp4,scannet/scene0714_00_disparity.npz
+scannet/scene0715_00_rgb_left.mp4,scannet/scene0715_00_disparity.npz
+scannet/scene0716_00_rgb_left.mp4,scannet/scene0716_00_disparity.npz
+scannet/scene0717_00_rgb_left.mp4,scannet/scene0717_00_disparity.npz
+scannet/scene0718_00_rgb_left.mp4,scannet/scene0718_00_disparity.npz
+scannet/scene0719_00_rgb_left.mp4,scannet/scene0719_00_disparity.npz
+scannet/scene0720_00_rgb_left.mp4,scannet/scene0720_00_disparity.npz
+scannet/scene0721_00_rgb_left.mp4,scannet/scene0721_00_disparity.npz
+scannet/scene0722_00_rgb_left.mp4,scannet/scene0722_00_disparity.npz
+scannet/scene0723_00_rgb_left.mp4,scannet/scene0723_00_disparity.npz
+scannet/scene0724_00_rgb_left.mp4,scannet/scene0724_00_disparity.npz
+scannet/scene0725_00_rgb_left.mp4,scannet/scene0725_00_disparity.npz
+scannet/scene0726_00_rgb_left.mp4,scannet/scene0726_00_disparity.npz
+scannet/scene0727_00_rgb_left.mp4,scannet/scene0727_00_disparity.npz
+scannet/scene0728_00_rgb_left.mp4,scannet/scene0728_00_disparity.npz
+scannet/scene0729_00_rgb_left.mp4,scannet/scene0729_00_disparity.npz
+scannet/scene0730_00_rgb_left.mp4,scannet/scene0730_00_disparity.npz
+scannet/scene0731_00_rgb_left.mp4,scannet/scene0731_00_disparity.npz
+scannet/scene0732_00_rgb_left.mp4,scannet/scene0732_00_disparity.npz
+scannet/scene0733_00_rgb_left.mp4,scannet/scene0733_00_disparity.npz
+scannet/scene0734_00_rgb_left.mp4,scannet/scene0734_00_disparity.npz
+scannet/scene0735_00_rgb_left.mp4,scannet/scene0735_00_disparity.npz
+scannet/scene0736_00_rgb_left.mp4,scannet/scene0736_00_disparity.npz
+scannet/scene0737_00_rgb_left.mp4,scannet/scene0737_00_disparity.npz
+scannet/scene0738_00_rgb_left.mp4,scannet/scene0738_00_disparity.npz
+scannet/scene0739_00_rgb_left.mp4,scannet/scene0739_00_disparity.npz
+scannet/scene0740_00_rgb_left.mp4,scannet/scene0740_00_disparity.npz
+scannet/scene0741_00_rgb_left.mp4,scannet/scene0741_00_disparity.npz
+scannet/scene0742_00_rgb_left.mp4,scannet/scene0742_00_disparity.npz
+scannet/scene0743_00_rgb_left.mp4,scannet/scene0743_00_disparity.npz
+scannet/scene0744_00_rgb_left.mp4,scannet/scene0744_00_disparity.npz
+scannet/scene0745_00_rgb_left.mp4,scannet/scene0745_00_disparity.npz
+scannet/scene0746_00_rgb_left.mp4,scannet/scene0746_00_disparity.npz
+scannet/scene0747_00_rgb_left.mp4,scannet/scene0747_00_disparity.npz
+scannet/scene0748_00_rgb_left.mp4,scannet/scene0748_00_disparity.npz
+scannet/scene0749_00_rgb_left.mp4,scannet/scene0749_00_disparity.npz
+scannet/scene0750_00_rgb_left.mp4,scannet/scene0750_00_disparity.npz
+scannet/scene0751_00_rgb_left.mp4,scannet/scene0751_00_disparity.npz
+scannet/scene0752_00_rgb_left.mp4,scannet/scene0752_00_disparity.npz
+scannet/scene0753_00_rgb_left.mp4,scannet/scene0753_00_disparity.npz
+scannet/scene0754_00_rgb_left.mp4,scannet/scene0754_00_disparity.npz
+scannet/scene0755_00_rgb_left.mp4,scannet/scene0755_00_disparity.npz
+scannet/scene0756_00_rgb_left.mp4,scannet/scene0756_00_disparity.npz
+scannet/scene0757_00_rgb_left.mp4,scannet/scene0757_00_disparity.npz
+scannet/scene0758_00_rgb_left.mp4,scannet/scene0758_00_disparity.npz
+scannet/scene0759_00_rgb_left.mp4,scannet/scene0759_00_disparity.npz
+scannet/scene0760_00_rgb_left.mp4,scannet/scene0760_00_disparity.npz
+scannet/scene0761_00_rgb_left.mp4,scannet/scene0761_00_disparity.npz
+scannet/scene0762_00_rgb_left.mp4,scannet/scene0762_00_disparity.npz
+scannet/scene0763_00_rgb_left.mp4,scannet/scene0763_00_disparity.npz
+scannet/scene0764_00_rgb_left.mp4,scannet/scene0764_00_disparity.npz
+scannet/scene0765_00_rgb_left.mp4,scannet/scene0765_00_disparity.npz
+scannet/scene0766_00_rgb_left.mp4,scannet/scene0766_00_disparity.npz
+scannet/scene0767_00_rgb_left.mp4,scannet/scene0767_00_disparity.npz
+scannet/scene0768_00_rgb_left.mp4,scannet/scene0768_00_disparity.npz
+scannet/scene0769_00_rgb_left.mp4,scannet/scene0769_00_disparity.npz
+scannet/scene0770_00_rgb_left.mp4,scannet/scene0770_00_disparity.npz
+scannet/scene0771_00_rgb_left.mp4,scannet/scene0771_00_disparity.npz
+scannet/scene0772_00_rgb_left.mp4,scannet/scene0772_00_disparity.npz
+scannet/scene0773_00_rgb_left.mp4,scannet/scene0773_00_disparity.npz
+scannet/scene0774_00_rgb_left.mp4,scannet/scene0774_00_disparity.npz
+scannet/scene0775_00_rgb_left.mp4,scannet/scene0775_00_disparity.npz
+scannet/scene0776_00_rgb_left.mp4,scannet/scene0776_00_disparity.npz
+scannet/scene0777_00_rgb_left.mp4,scannet/scene0777_00_disparity.npz
+scannet/scene0778_00_rgb_left.mp4,scannet/scene0778_00_disparity.npz
+scannet/scene0779_00_rgb_left.mp4,scannet/scene0779_00_disparity.npz
+scannet/scene0780_00_rgb_left.mp4,scannet/scene0780_00_disparity.npz
+scannet/scene0781_00_rgb_left.mp4,scannet/scene0781_00_disparity.npz
+scannet/scene0782_00_rgb_left.mp4,scannet/scene0782_00_disparity.npz
+scannet/scene0783_00_rgb_left.mp4,scannet/scene0783_00_disparity.npz
+scannet/scene0784_00_rgb_left.mp4,scannet/scene0784_00_disparity.npz
+scannet/scene0785_00_rgb_left.mp4,scannet/scene0785_00_disparity.npz
+scannet/scene0786_00_rgb_left.mp4,scannet/scene0786_00_disparity.npz
+scannet/scene0787_00_rgb_left.mp4,scannet/scene0787_00_disparity.npz
+scannet/scene0788_00_rgb_left.mp4,scannet/scene0788_00_disparity.npz
+scannet/scene0789_00_rgb_left.mp4,scannet/scene0789_00_disparity.npz
+scannet/scene0790_00_rgb_left.mp4,scannet/scene0790_00_disparity.npz
+scannet/scene0791_00_rgb_left.mp4,scannet/scene0791_00_disparity.npz
+scannet/scene0792_00_rgb_left.mp4,scannet/scene0792_00_disparity.npz
+scannet/scene0793_00_rgb_left.mp4,scannet/scene0793_00_disparity.npz
+scannet/scene0794_00_rgb_left.mp4,scannet/scene0794_00_disparity.npz
+scannet/scene0795_00_rgb_left.mp4,scannet/scene0795_00_disparity.npz
+scannet/scene0796_00_rgb_left.mp4,scannet/scene0796_00_disparity.npz
+scannet/scene0797_00_rgb_left.mp4,scannet/scene0797_00_disparity.npz
+scannet/scene0798_00_rgb_left.mp4,scannet/scene0798_00_disparity.npz
+scannet/scene0799_00_rgb_left.mp4,scannet/scene0799_00_disparity.npz
+scannet/scene0800_00_rgb_left.mp4,scannet/scene0800_00_disparity.npz
+scannet/scene0801_00_rgb_left.mp4,scannet/scene0801_00_disparity.npz
+scannet/scene0802_00_rgb_left.mp4,scannet/scene0802_00_disparity.npz
+scannet/scene0803_00_rgb_left.mp4,scannet/scene0803_00_disparity.npz
+scannet/scene0804_00_rgb_left.mp4,scannet/scene0804_00_disparity.npz
+scannet/scene0805_00_rgb_left.mp4,scannet/scene0805_00_disparity.npz
+scannet/scene0806_00_rgb_left.mp4,scannet/scene0806_00_disparity.npz

benchmark/csv/meta_sintel.csv

@@ -0,0 +1,24 @@
+filepath_left,filepath_disparity
+sintel/ambush_5_rgb_left.mp4,sintel/ambush_5_disparity.npz
+sintel/bamboo_2_rgb_left.mp4,sintel/bamboo_2_disparity.npz
+sintel/mountain_1_rgb_left.mp4,sintel/mountain_1_disparity.npz
+sintel/bamboo_1_rgb_left.mp4,sintel/bamboo_1_disparity.npz
+sintel/shaman_2_rgb_left.mp4,sintel/shaman_2_disparity.npz
+sintel/ambush_6_rgb_left.mp4,sintel/ambush_6_disparity.npz
+sintel/bandage_1_rgb_left.mp4,sintel/bandage_1_disparity.npz
+sintel/alley_1_rgb_left.mp4,sintel/alley_1_disparity.npz
+sintel/temple_3_rgb_left.mp4,sintel/temple_3_disparity.npz
+sintel/shaman_3_rgb_left.mp4,sintel/shaman_3_disparity.npz
+sintel/ambush_2_rgb_left.mp4,sintel/ambush_2_disparity.npz
+sintel/cave_4_rgb_left.mp4,sintel/cave_4_disparity.npz
+sintel/cave_2_rgb_left.mp4,sintel/cave_2_disparity.npz
+sintel/alley_2_rgb_left.mp4,sintel/alley_2_disparity.npz
+sintel/market_5_rgb_left.mp4,sintel/market_5_disparity.npz
+sintel/sleeping_2_rgb_left.mp4,sintel/sleeping_2_disparity.npz
+sintel/ambush_4_rgb_left.mp4,sintel/ambush_4_disparity.npz
+sintel/sleeping_1_rgb_left.mp4,sintel/sleeping_1_disparity.npz
+sintel/market_6_rgb_left.mp4,sintel/market_6_disparity.npz
+sintel/market_2_rgb_left.mp4,sintel/market_2_disparity.npz
+sintel/bandage_2_rgb_left.mp4,sintel/bandage_2_disparity.npz
+sintel/ambush_7_rgb_left.mp4,sintel/ambush_7_disparity.npz
+sintel/temple_2_rgb_left.mp4,sintel/temple_2_disparity.npz

benchmark/demo.sh

@@ -0,0 +1,18 @@
+#!/bin/sh
+set -x
+set -e
+
+test_case=$1
+gpu_id=$2
+process_length=$3
+saved_root=$4
+saved_dataset_folder=$5
+overlap=$6
+dataset=$7
+
+CUDA_VISIBLE_DEVICES=${gpu_id} PYTHONPATH=. python run.py \
+  --video-path ${test_case} \
+  --save-folder ${saved_root}/${saved_dataset_folder} \
+  --process-length ${process_length} \
+  --dataset ${dataset} \
+  --overlap ${overlap}

benchmark/eval/eval.py

@@ -0,0 +1,282 @@
+import numpy as np
+import os
+import torch
+import cv2
+import csv
+from metric import * 
+import metric
+import argparse
+from tqdm import tqdm
+import json
+
+
+device = 'cuda'
+eval_metrics = [
+    "abs_relative_difference",
+    "rmse_linear",
+    "delta1_acc",
+    # "squared_relative_difference",
+    # "rmse_log",
+    # "log10",
+    # "delta2_acc",
+    # "delta3_acc",
+    # "i_rmse",
+    # "silog_rmse",
+]
+
+
+def depth2disparity(depth, return_mask=False):
+    if isinstance(depth, torch.Tensor):
+        disparity = torch.zeros_like(depth)
+    elif isinstance(depth, np.ndarray):
+        disparity = np.zeros_like(depth)
+    non_negtive_mask = depth > 0
+    disparity[non_negtive_mask] = 1.0 / depth[non_negtive_mask]
+    if return_mask:
+        return disparity, non_negtive_mask
+    else:
+        return disparity
+
+
+def resize_images(images, new_size):
+    resized_images = np.empty(
+        (images.shape[0], new_size[0], new_size[1], images.shape[3])
+    )
+
+    for i, image in enumerate(images):
+        if image.shape[2]==1:
+            resized_images[i] = cv2.resize(image, (new_size[1], new_size[0]))[..., None]
+        else:
+            resized_images[i] = cv2.resize(image, (new_size[1], new_size[0]))
+
+    return resized_images
+    
+
+def eval_single(
+    pred_disp_path, 
+    gt_disp_path, 
+    seq_len=98, 
+    domain='depth', 
+    method_type="ours",
+    dataset_max_depth="70"
+):
+    # load data
+    gt_disp = np.load(gt_disp_path)['disparity'] \
+        if 'disparity' in np.load(gt_disp_path).files else \
+        np.load(gt_disp_path)['arr_0']  # (t, 1, h, w)
+
+    if method_type=="ours":
+        pred_disp = np.load(pred_disp_path)['depth'] # (t, h, w)
+    if method_type=="depth_anything":
+        pred_disp = np.load(pred_disp_path)['disparity'] # (t, h, w)
+    
+    # seq_len
+    if pred_disp.shape[0] < seq_len:
+         seq_len = pred_disp.shape[0]
+
+    # preprocess
+    pred_disp = resize_images(pred_disp[..., None], (gt_disp.shape[-2], gt_disp.shape[-1])) # (t, h, w)
+    pred_disp = pred_disp[..., 0] # (t, h, w)
+    pred_disp = pred_disp[:seq_len]
+    gt_disp = gt_disp[:seq_len, 0] # (t, h, w)
+
+    # valid mask
+    valid_mask = np.logical_and(
+            (gt_disp > 1e-3), 
+            (gt_disp < dataset_max_depth)
+        )
+    pred_disp = np.clip(pred_disp, a_min=1e-3, a_max=None) 
+    pred_disp_masked = pred_disp[valid_mask].reshape((-1, 1))
+    
+    # choose evaluation domain
+    DOMAIN = domain
+    if DOMAIN=='disp':
+        # align in real disp, calc in disp
+        gt_disp_maksed = gt_disp[valid_mask].reshape((-1, 1)).astype(np.float64)
+    elif DOMAIN=='depth':
+        # align in disp = 1/depth, calc in depth
+        gt_disp_maksed = 1. / (gt_disp[valid_mask].reshape((-1, 1)).astype(np.float64) + 1e-8)
+    else:
+        pass
+
+
+    # calc scale and shift
+    _ones = np.ones_like(pred_disp_masked)
+    A = np.concatenate([pred_disp_masked, _ones], axis=-1)
+    X = np.linalg.lstsq(A, gt_disp_maksed, rcond=None)[0]
+    scale, shift = X # gt = scale * pred + shift
+    
+    # align
+    aligned_pred = scale * pred_disp + shift
+    aligned_pred = np.clip(aligned_pred, a_min=1e-3, a_max=None) 
+
+
+    # align in real disp, calc in disp
+    if DOMAIN=='disp':
+        pred_depth = aligned_pred
+        gt_depth = gt_disp
+    # align in disp = 1/depth, calc in depth
+    elif DOMAIN=='depth':
+        pred_depth = depth2disparity(aligned_pred)
+        gt_depth = gt_disp
+    else:
+        pass
+
+    # metric evaluation, clip to dataset min max
+    pred_depth = np.clip(
+            pred_depth, a_min=1e-3, a_max=dataset_max_depth
+        )
+
+    # evaluate metric 
+    sample_metric = []
+    metric_funcs = [getattr(metric, _met) for _met in eval_metrics]
+
+    # Evaluate 
+    sample_metric = []
+    pred_depth_ts = torch.from_numpy(pred_depth).to(device)
+    gt_depth_ts = torch.from_numpy(gt_depth).to(device)
+    valid_mask_ts = torch.from_numpy(valid_mask).to(device)
+
+    n = valid_mask.sum((-1, -2))
+    valid_frame = (n > 0)
+    pred_depth_ts = pred_depth_ts[valid_frame]
+    gt_depth_ts = gt_depth_ts[valid_frame]
+    valid_mask_ts = valid_mask_ts[valid_frame]
+
+    for met_func in metric_funcs:
+        _metric_name = met_func.__name__
+        _metric = met_func(pred_depth_ts, gt_depth_ts, valid_mask_ts).item()
+        sample_metric.append(_metric)
+
+    return sample_metric
+
+
+
+if __name__=="__main__":
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "--seq_len", 
+        type=int,
+        default=50,
+        help="Max video frame length for evaluation."
+    )
+
+    parser.add_argument(
+        "--domain",
+        type=str,
+        default="depth",
+        choices=["depth", "disp"],
+        help="Domain of metric calculation."
+    )
+
+    parser.add_argument(
+        "--method_type",
+        type=str,
+        default="ours",
+        choices=["ours", "depth_anything"],
+        help="Choose the methods."
+    )
+
+    parser.add_argument(
+        "--dataset_max_depth",
+        type=int,
+        default=70,
+        help="Dataset max depth clip."
+    )
+
+    parser.add_argument(
+        "--pred_disp_root",
+        type=str,
+        default="./demo_output",
+        help="Predicted output directory."
+    )
+
+    parser.add_argument(
+        "--gt_disp_root",
+        type=str,
+        required=True,
+        help="GT depth directory."
+    )
+
+    parser.add_argument(
+        "--dataset",
+        type=str,
+        required=True,
+        help="Choose the datasets."
+    )
+
+    parser.add_argument(
+        "--meta_path",
+        type=str,
+        required=True,
+        help="Path of test dataset csv file."
+    )
+
+
+    args = parser.parse_args()
+
+    SEQ_LEN = args.seq_len
+    method_type = args.method_type
+    if method_type == "ours":
+        pred_disp_root = os.path.join(args.pred_disp_root, f'results_{args.dataset}')
+    else:
+        # pred_disp_root = args.pred_disp_root
+        pred_disp_root = os.path.join(args.pred_disp_root, f'results_{args.dataset}')
+    domain = args.domain
+    dataset_max_depth = args.dataset_max_depth
+    saved_json_path = os.path.join(args.pred_disp_root, f"results_{args.dataset}.json")
+
+    meta_path = args.meta_path
+
+    assert method_type in ["depth_anything", "ours"], "Invalid method type, must be in ['depth_anything', 'ours']"
+    assert domain in ["depth", "disp"], "Invalid domain type, must be in ['depth', 'disp']"
+        
+    with open(meta_path, mode="r", encoding="utf-8") as csvfile:
+        csv_reader = csv.DictReader(csvfile)
+        samples = list(csv_reader)
+
+    # iterate all cases
+    results_all = []
+    for i, sample in enumerate(tqdm(samples)):
+        gt_disp_path = os.path.join(args.gt_disp_root, samples[i]['filepath_disparity'])
+        if method_type=="ours":
+            pred_disp_path = os.path.join(pred_disp_root, samples[i]['filepath_disparity'])
+            pred_disp_path = pred_disp_path.replace("disparity", "rgb_left")
+        
+        if method_type=="depth_anything":
+            pred_disp_path = os.path.join(pred_disp_root, samples[i]['filepath_disparity'])
+            pred_disp_path = pred_disp_path.replace("disparity", "rgb_left_depth")
+        
+        results_single = eval_single(
+            pred_disp_path, 
+            gt_disp_path, 
+            seq_len=SEQ_LEN, 
+            domain=domain, 
+            method_type=method_type, 
+            dataset_max_depth=dataset_max_depth
+        )
+
+        results_all.append(results_single)
+
+    # avarage
+    final_results =  np.array(results_all)
+    final_results_mean = np.mean(final_results, axis=0)
+    print("")
+
+    # save mean to json
+    result_dict = { 'name': method_type }
+    for i, metric in enumerate(eval_metrics):
+        result_dict[metric] = final_results_mean[i]
+        print(f"{metric}: {final_results_mean[i]:04f}")
+
+    # save each case to json
+    for i, results in enumerate(results_all):
+        result_dict[samples[i]['filepath_disparity']] = results
+
+    # write json
+    with open(saved_json_path, 'w') as f:
+        json.dump(result_dict, f, indent=4)
+    print("")
+    print(f"Evaluation results json are saved to {saved_json_path}")
+    

benchmark/eval/eval.sh

@@ -0,0 +1,51 @@
+#!/bin/sh
+set -x
+set -e
+
+pred_disp_root=/path/to/saved/root_directory # The parent directory that contaning [sintel, scannet, KITTI, bonn, NYUv2] prediction
+gt_disp_root=/path/to/gt_depth/root_directory # The parent directory that contaning [sintel, scannet, KITTI, bonn, NYUv2] ground truth
+
+# eval sintel
+python benchmark/eval/eval.py \
+    --meta_path ./eval/csv/meta_sintel.csv \
+    --dataset_max_depth 70 \
+    --dataset sintel \
+    --seq_len 50 \
+    --pred_disp_root ${pred_disp_root} \
+    --gt_disp_root ${gt_disp_root} \
+
+# eval scannet
+python benchmark/eval/eval.py \
+    --meta_path ./eval/csv/meta_scannet_test.csv \
+    --dataset_max_depth 10 \
+    --dataset scannet \
+    --seq_len 90 \
+    --pred_disp_root ${pred_disp_root} \
+    --gt_disp_root ${gt_disp_root} \
+
+# eval kitti
+python benchmark/eval/eval.py \
+    --meta_path ./eval/csv/meta_kitti_val.csv \
+    --dataset_max_depth 80 \
+    --dataset kitti \
+    --seq_len 110 \
+    --pred_disp_root ${pred_disp_root} \
+    --gt_disp_root ${gt_disp_root} \
+
+# eval bonn
+python benchmark/eval/eval.py \
+    --meta_path ./eval/csv/meta_bonn.csv \
+    --dataset_max_depth 10 \
+    --dataset bonn \
+    --seq_len 110 \
+    --pred_disp_root ${pred_disp_root} \
+    --gt_disp_root ${gt_disp_root} \
+
+# eval nyu
+python benchmark/eval/eval.py \
+    --meta_path ./eval/csv/meta_nyu_test.csv \
+    --dataset_max_depth 10 \
+    --dataset nyu \
+    --seq_len 1 \
+    --pred_disp_root ${pred_disp_root} \
+    --gt_disp_root ${gt_disp_root} \

benchmark/eval/metric.py

@@ -0,0 +1,128 @@
+import torch
+
+
+def abs_relative_difference(output, target, valid_mask=None):
+    actual_output = output
+    actual_target = target
+    abs_relative_diff = torch.abs(actual_output - actual_target) / actual_target
+    if valid_mask is not None:
+        abs_relative_diff[~valid_mask] = 0
+        n = valid_mask.sum((-1, -2))
+    else:
+        n = output.shape[-1] * output.shape[-2]
+    abs_relative_diff = torch.sum(abs_relative_diff, (-1, -2)) / n
+    return abs_relative_diff.mean()
+
+
+def squared_relative_difference(output, target, valid_mask=None):
+    actual_output = output
+    actual_target = target
+    square_relative_diff = (
+        torch.pow(torch.abs(actual_output - actual_target), 2) / actual_target
+    )
+    if valid_mask is not None:
+        square_relative_diff[~valid_mask] = 0
+        n = valid_mask.sum((-1, -2))
+    else:
+        n = output.shape[-1] * output.shape[-2]
+    square_relative_diff = torch.sum(square_relative_diff, (-1, -2)) / n
+    return square_relative_diff.mean()
+
+
+def rmse_linear(output, target, valid_mask=None):
+    actual_output = output
+    actual_target = target
+    diff = actual_output - actual_target
+    if valid_mask is not None:
+        diff[~valid_mask] = 0
+        n = valid_mask.sum((-1, -2))
+    else:
+        n = output.shape[-1] * output.shape[-2]
+    diff2 = torch.pow(diff, 2)
+    mse = torch.sum(diff2, (-1, -2)) / n
+    rmse = torch.sqrt(mse)
+    return rmse.mean()
+
+
+def rmse_log(output, target, valid_mask=None):
+    diff = torch.log(output) - torch.log(target)
+    if valid_mask is not None:
+        diff[~valid_mask] = 0
+        n = valid_mask.sum((-1, -2))
+    else:
+        n = output.shape[-1] * output.shape[-2]
+    diff2 = torch.pow(diff, 2)
+    mse = torch.sum(diff2, (-1, -2)) / n  # [B]
+    rmse = torch.sqrt(mse)
+    return rmse.mean()
+
+
+def log10(output, target, valid_mask=None):
+    if valid_mask is not None:
+        diff = torch.abs(
+            torch.log10(output[valid_mask]) - torch.log10(target[valid_mask])
+        )
+    else:
+        diff = torch.abs(torch.log10(output) - torch.log10(target))
+    return diff.mean()
+
+
+# adapt from: https://github.com/imran3180/depth-map-prediction/blob/master/main.py
+def threshold_percentage(output, target, threshold_val, valid_mask=None):
+    d1 = output / target
+    d2 = target / output
+    max_d1_d2 = torch.max(d1, d2)
+    zero = torch.zeros(*output.shape)
+    one = torch.ones(*output.shape)
+    bit_mat = torch.where(max_d1_d2.cpu() < threshold_val, one, zero)
+    if valid_mask is not None:
+        bit_mat[~valid_mask] = 0
+        n = valid_mask.sum((-1, -2))
+    else:
+        n = output.shape[-1] * output.shape[-2]
+    count_mat = torch.sum(bit_mat, (-1, -2))
+    threshold_mat = count_mat / n.cpu()
+    return threshold_mat.mean()
+
+
+def delta1_acc(pred, gt, valid_mask):
+    return threshold_percentage(pred, gt, 1.25, valid_mask)
+
+
+def delta2_acc(pred, gt, valid_mask):
+    return threshold_percentage(pred, gt, 1.25**2, valid_mask)
+
+
+def delta3_acc(pred, gt, valid_mask):
+    return threshold_percentage(pred, gt, 1.25**3, valid_mask)
+
+
+def i_rmse(output, target, valid_mask=None):
+    output_inv = 1.0 / output
+    target_inv = 1.0 / target
+    diff = output_inv - target_inv
+    if valid_mask is not None:
+        diff[~valid_mask] = 0
+        n = valid_mask.sum((-1, -2))
+    else:
+        n = output.shape[-1] * output.shape[-2]
+    diff2 = torch.pow(diff, 2)
+    mse = torch.sum(diff2, (-1, -2)) / n  # [B]
+    rmse = torch.sqrt(mse)
+    return rmse.mean()
+
+
+def silog_rmse(depth_pred, depth_gt, valid_mask=None):
+    diff = torch.log(depth_pred) - torch.log(depth_gt)
+    if valid_mask is not None:
+        diff[~valid_mask] = 0
+        n = valid_mask.sum((-1, -2))
+    else:
+        n = depth_gt.shape[-2] * depth_gt.shape[-1]
+
+    diff2 = torch.pow(diff, 2)
+
+    first_term = torch.sum(diff2, (-1, -2)) / n
+    second_term = torch.pow(torch.sum(diff, (-1, -2)), 2) / (n**2)
+    loss = torch.sqrt(torch.mean(first_term - second_term)) * 100
+    return loss

benchmark/infer/infer.sh

@@ -0,0 +1,59 @@
+#!/bin/sh
+set -x
+set -e
+
+input_rgb_root=/path/to/input/RGB/root_directory # The parent directory that contaning [sintel, scannet, KITTI, bonn, NYUv2] input RGB
+saved_root=/path/to/saved/root_directory # The parent directory that saving [sintel, scannet, KITTI, bonn, NYUv2] prediction
+gpus=0,1,2,3 # Using 4 GPU, you can adjust it according to your device
+
+
+# infer sintel
+python benchmark/infer/infer_batch.py \
+    --meta_path ./eval/csv/meta_sintel.csv \
+    --saved_root ${saved_root} \
+    --saved_dataset_folder results_sintel \
+    --input_rgb_root ${input_rgb_root} \
+    --process_length 50 \
+    --gpus ${gpus} \
+    --dataset sintel \
+
+# infer scannet
+python benchmark/infer/infer_batch.py \
+    --meta_path ./eval/csv/meta_scannet_test.csv \
+    --saved_root ${saved_root} \
+    --saved_dataset_folder results_scannet \
+    --input_rgb_root ${input_rgb_root} \
+    --process_length 90 \
+    --gpus ${gpus} \
+    --dataset scannet \
+
+# infer kitti
+python benchmark/infer/infer_batch.py \
+    --meta_path ./eval/csv/meta_kitti_val.csv \
+    --saved_root ${saved_root} \
+    --saved_dataset_folder results_kitti \
+    --input_rgb_root ${input_rgb_root} \
+    --process_length 110 \
+    --gpus ${gpus} \
+    --dataset kitti \
+
+# infer bonn
+python benchmark/infer/infer_batch.py \
+    --meta_path ./eval/csv/meta_bonn.csv \
+    --saved_root ${saved_root} \
+    --saved_dataset_folder results_bonn \
+    --input_rgb_root ${input_rgb_root} \
+    --process_length 110 \
+    --gpus ${gpus} \
+    --dataset bonn \
+
+# infer nyu
+python benchmark/infer/infer_batch.py \
+    --meta_path ./eval/csv/meta_nyu_test.csv \
+    --saved_root ${saved_root} \
+    --saved_dataset_folder results_nyu \
+    --input_rgb_root ${input_rgb_root} \
+    --process_length 1 \
+    --gpus ${gpus} \
+    --overlap 0 \
+    --dataset nyu \

benchmark/infer/infer_batch.py

@@ -0,0 +1,46 @@
+import os
+import multiprocessing as mp
+import csv
+import argparse
+
+
+def process_video(video_path, gpu_id, save_folder, args):
+    os.system(f'sh ./benchmark/demo.sh {video_path} {gpu_id} {int(args.process_length)} {args.saved_root} {save_folder} {args.overlap} {args.dataset}')
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser()
+    
+    parser.add_argument('--meta_path', type=str)
+    parser.add_argument('--saved_dataset_folder', type=str)
+    parser.add_argument('--saved_root', type=str, default="./output")
+    parser.add_argument('--input_rgb_root', type=str)
+
+    parser.add_argument('--process_length', type=int, default=110)
+    parser.add_argument('--gpus', type=str, default="0,1,2,3")
+    
+    parser.add_argument('--overlap', type=int, default=1)
+    parser.add_argument('--dataset', type=str, default="open")
+    
+    args = parser.parse_args()
+    gpus = args.gpus.strip().split(',')
+
+    with open(args.meta_path, mode="r", encoding="utf-8") as csvfile:
+        csv_reader = csv.DictReader(csvfile)
+        test_samples = list(csv_reader)
+    batch_size = len(gpus)
+    video_batches = [test_samples[i:i+batch_size] for i in range(0, len(test_samples), batch_size)]
+    print("gpus+++: ", gpus)
+
+    processes = []
+    for video_batch in video_batches:
+        for i, sample in enumerate(video_batch):
+            video_path = os.path.join(args.input_rgb_root, sample["filepath_left"])
+            save_folder = os.path.join(args.saved_dataset_folder, os.path.dirname(sample["filepath_left"]))
+            gpu_id = gpus[i % len(gpus)]
+            p = mp.Process(target=process_video, args=(video_path, gpu_id, save_folder, args))
+            p.start()
+            processes.append(p)
+        
+        for p in processes: 
+            p.join()

depthcrafter/utils.py

@@ -1,67 +1,27 @@
+from typing import Union, List
+import tempfile
 import numpy as np
-import cv2
+import PIL.Image
 import matplotlib.cm as cm
+import mediapy
 import torch
 
 
-def read_video_frames(video_path, process_length, target_fps, max_res):
-    # a simple function to read video frames
-    cap = cv2.VideoCapture(video_path)
-    original_fps = cap.get(cv2.CAP_PROP_FPS)
-    original_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-    original_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-    # round the height and width to the nearest multiple of 64
-    height = round(original_height / 64) * 64
-    width = round(original_width / 64) * 64
-
-    # resize the video if the height or width is larger than max_res
-    if max(height, width) > max_res:
-        scale = max_res / max(original_height, original_width)
-        height = round(original_height * scale / 64) * 64
-        width = round(original_width * scale / 64) * 64
-
-    if target_fps < 0:
-        target_fps = original_fps
-
-    stride = max(round(original_fps / target_fps), 1)
-
-    frames = []
-    frame_count = 0
-    while cap.isOpened():
-        ret, frame = cap.read()
-        if not ret or (process_length > 0 and frame_count >= process_length):
-            break
-        if frame_count % stride == 0:
-            frame = cv2.resize(frame, (width, height))
-            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)  # Convert BGR to RGB
-            frames.append(frame.astype("float32") / 255.0)
-        frame_count += 1
-    cap.release()
-
-    frames = np.array(frames)
-    return frames, target_fps
-
-
 def save_video(
-    video_frames,
-    output_video_path,
-    fps: int = 15,
+    video_frames: Union[List[np.ndarray], List[PIL.Image.Image]],
+    output_video_path: str = None,
+    fps: int = 10,
+    crf: int = 18,
 ) -> str:
-    # a simple function to save video frames
-    height, width = video_frames[0].shape[:2]
-    is_color = video_frames[0].ndim == 3
-    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
-    video_writer = cv2.VideoWriter(
-        output_video_path, fourcc, fps, (width, height), isColor=is_color
-    )
+    if output_video_path is None:
+        output_video_path = tempfile.NamedTemporaryFile(suffix=".mp4").name
 
-    for frame in video_frames:
-        frame = (frame * 255).astype(np.uint8)
-        if is_color:
-            frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
-        video_writer.write(frame)
+    if isinstance(video_frames[0], np.ndarray):
+        video_frames = [(frame * 255).astype(np.uint8) for frame in video_frames]
 
-    video_writer.release()
+    elif isinstance(video_frames[0], PIL.Image.Image):
+        video_frames = [np.array(frame) for frame in video_frames]
+    mediapy.write_video(output_video_path, video_frames, fps=fps, crf=crf)
     return output_video_path
 
 

requirements.txt

@@ -2,7 +2,9 @@ torch==2.0.1
 diffusers==0.29.1
 numpy==1.26.4
 matplotlib==3.8.4
-opencv-python==4.8.1.78
 transformers==4.41.2
 accelerate==0.30.1
 xformers==0.0.20
+mediapy==1.2.0
+fire==0.6.0
+decord==0.6.0

run.py

@@ -2,12 +2,22 @@ import gc
 import os
 import numpy as np
 import torch
-import argparse
+
+from decord import VideoReader, cpu
 from diffusers.training_utils import set_seed
+from fire import Fire
 
 from depthcrafter.depth_crafter_ppl import DepthCrafterPipeline
 from depthcrafter.unet import DiffusersUNetSpatioTemporalConditionModelDepthCrafter
-from depthcrafter.utils import vis_sequence_depth, save_video, read_video_frames
+from depthcrafter.utils import vis_sequence_depth, save_video
+
+dataset_res_dict = {
+    "sintel": [448, 1024],
+    "scannet": [640, 832],
+    "KITTI": [384, 1280],
+    "bonn": [512, 640],
+    "NYUv2": [448, 640],
+}
 
 
 class DepthCrafterDemo:
@@ -49,6 +59,45 @@ class DepthCrafterDemo:
             print("Xformers is not enabled")
         self.pipe.enable_attention_slicing()
 
+    @staticmethod
+    def read_video_frames(
+        video_path, process_length, target_fps, max_res, dataset="open"
+    ):
+        if dataset == "open":
+            print("==> processing video: ", video_path)
+            vid = VideoReader(video_path, ctx=cpu(0))
+            print(
+                "==> original video shape: ", (len(vid), *vid.get_batch([0]).shape[1:])
+            )
+            original_height, original_width = vid.get_batch([0]).shape[1:3]
+            height = round(original_height / 64) * 64
+            width = round(original_width / 64) * 64
+            if max(height, width) > max_res:
+                scale = max_res / max(original_height, original_width)
+                height = round(original_height * scale / 64) * 64
+                width = round(original_width * scale / 64) * 64
+        else:
+            height = dataset_res_dict[dataset][0]
+            width = dataset_res_dict[dataset][1]
+
+        vid = VideoReader(video_path, ctx=cpu(0), width=width, height=height)
+
+        fps = vid.get_avg_fps() if target_fps == -1 else target_fps
+        stride = round(vid.get_avg_fps() / fps)
+        stride = max(stride, 1)
+        frames_idx = list(range(0, len(vid), stride))
+        print(
+            f"==> downsampled shape: {len(frames_idx), *vid.get_batch([0]).shape[1:]}, with stride: {stride}"
+        )
+        if process_length != -1 and process_length < len(frames_idx):
+            frames_idx = frames_idx[:process_length]
+        print(
+            f"==> final processing shape: {len(frames_idx), *vid.get_batch([0]).shape[1:]}"
+        )
+        frames = vid.get_batch(frames_idx).asnumpy().astype("float32") / 255.0
+
+        return frames, fps
+
     def infer(
         self,
         video: str,
@@ -59,6 +108,7 @@ class DepthCrafterDemo:
         process_length: int = 195,
         overlap: int = 25,
         max_res: int = 1024,
+        dataset: str = "open",
         target_fps: int = 15,
         seed: int = 42,
         track_time: bool = True,
@@ -66,11 +116,13 @@ class DepthCrafterDemo:
     ):
         set_seed(seed)
 
-        frames, target_fps = read_video_frames(
-            video, process_length, target_fps, max_res
+        frames, target_fps = self.read_video_frames(
+            video,
+            process_length,
+            target_fps,
+            max_res,
+            dataset,
         )
-        print(f"==> video name: {video}, frames shape: {frames.shape}")
-
         # inference the depth map using the DepthCrafter pipeline
         with torch.inference_mode():
             res = self.pipe(
@@ -127,83 +179,55 @@ class DepthCrafterDemo:
         return res_path[:2]
 
 
-if __name__ == "__main__":
-    # running configs
-    # the most important arguments for memory saving are `cpu_offload`, `enable_xformers`, `max_res`, and `window_size`
-    # the most important arguments for trade-off between quality and speed are
-    # `num_inference_steps`, `guidance_scale`, and `max_res`
-    parser = argparse.ArgumentParser(description="DepthCrafter")
-    parser.add_argument(
-        "--video-path", type=str, required=True, help="Path to the input video file(s)"
-    )
-    parser.add_argument(
-        "--save-folder",
-        type=str,
-        default="./demo_output",
-        help="Folder to save the output",
-    )
-    parser.add_argument(
-        "--unet-path",
-        type=str,
-        default="tencent/DepthCrafter",
-        help="Path to the UNet model",
-    )
-    parser.add_argument(
-        "--pre-train-path",
-        type=str,
-        default="stabilityai/stable-video-diffusion-img2vid-xt",
-        help="Path to the pre-trained model",
-    )
-    parser.add_argument(
-        "--process-length", type=int, default=195, help="Number of frames to process"
-    )
-    parser.add_argument(
-        "--cpu-offload",
-        type=str,
-        default="model",
-        choices=["model", "sequential", None],
-        help="CPU offload option",
-    )
-    parser.add_argument(
-        "--target-fps", type=int, default=15, help="Target FPS for the output video"
-    )  # -1 for original fps
-    parser.add_argument("--seed", type=int, default=42, help="Random seed")
-    parser.add_argument(
-        "--num-inference-steps", type=int, default=25, help="Number of inference steps"
-    )
-    parser.add_argument(
-        "--guidance-scale", type=float, default=1.2, help="Guidance scale"
-    )
-    parser.add_argument("--window-size", type=int, default=110, help="Window size")
-    parser.add_argument("--overlap", type=int, default=25, help="Overlap size")
-    parser.add_argument("--max-res", type=int, default=1024, help="Maximum resolution")
-    parser.add_argument("--save_npz", type=bool, default=True, help="Save npz file")
-    parser.add_argument("--track_time", type=bool, default=False, help="Track time")
-
-    args = parser.parse_args()
-
+def main(
+    video_path: str,
+    save_folder: str = "./demo_output",
+    unet_path: str = "tencent/DepthCrafter",
+    pre_train_path: str = "stabilityai/stable-video-diffusion-img2vid-xt",
+    process_length: int = -1,
+    cpu_offload: str = "model",
+    target_fps: int = -1,
+    seed: int = 42,
+    num_inference_steps: int = 5,
+    guidance_scale: float = 1.0,
+    window_size: int = 110,
+    overlap: int = 25,
+    max_res: int = 1024,
+    dataset: str = "open",
+    save_npz: bool = True,
+    track_time: bool = False,
+):
     depthcrafter_demo = DepthCrafterDemo(
-        unet_path=args.unet_path,
-        pre_train_path=args.pre_train_path,
-        cpu_offload=args.cpu_offload,
+        unet_path=unet_path,
+        pre_train_path=pre_train_path,
+        cpu_offload=cpu_offload,
     )
     # process the videos, the video paths are separated by comma
-    video_paths = args.video_path.split(",")
+    video_paths = video_path.split(",")
     for video in video_paths:
         depthcrafter_demo.infer(
             video,
-            args.num_inference_steps,
-            args.guidance_scale,
-            save_folder=args.save_folder,
-            window_size=args.window_size,
-            process_length=args.process_length,
-            overlap=args.overlap,
-            max_res=args.max_res,
-            target_fps=args.target_fps,
-            seed=args.seed,
-            track_time=args.track_time,
-            save_npz=args.save_npz,
+            num_inference_steps,
+            guidance_scale,
+            save_folder=save_folder,
+            window_size=window_size,
+            process_length=process_length,
+            overlap=overlap,
+            max_res=max_res,
+            dataset=dataset,
+            target_fps=target_fps,
+            seed=seed,
+            track_time=track_time,
+            save_npz=save_npz,
         )
         # clear the cache for the next video
         gc.collect()
         torch.cuda.empty_cache()
+
+
+if __name__ == "__main__":
+    # running configs
+    # the most important arguments for memory saving are `cpu_offload`, `enable_xformers`, `max_res`, and `window_size`
+    # the most important arguments for trade-off between quality and speed are
+    # `num_inference_steps`, `guidance_scale`, and `max_res`
+    Fire(main)