Error while camera pose testing

[ravikt]

I am using python geonet_main.py --mode=test_pose --dataset_dir=/path/to/kitti/odom/dataset/ --init_ckpt_file=/path/to/trained/model/ --batch_size=1 --seq_length=5 --pose_test_seq=9 --output_dir=/path/to/save/predictions/

with seq_length = 3 , I am getting the following

InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [1,1,256,12] rhs shape= [1,1,256,24] [[Node: save/Assign_29 = Assign[T=DT_FLOAT, _class=["loc:@pose_net/Conv_7/weights"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/gpu:0"](pose_net/Conv_7/weights, save/RestoreV2_29/_3)]] [[Node: save/RestoreV2_7/_50 = _Send[T=DT_FLOAT, client_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_143_save/RestoreV2_7", _device="/job:localhost/replica:0/task:0/cpu:0"](save/RestoreV2_7)]]

and with seq_length = 5, the following error

File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 48, in run _sys.exit(main(_sys.argv[:1] + flags_passthrough)) File "geonet_main.py", line 161, in main test_pose(opt) File "/ravikt/geonet/GeoNet/geonet_test_pose.py", line 60, in test_pose inputs[b] = image_seq ValueError: could not broadcast input array from shape (128,416,5) into shape (128,416,15)

Can you please help me address this error ?

[yzcjtr]

Hi, can you confirm if your python and tensorflow versions are consistent with ours?

[ravikt]

Python version is 2.7.12 and tensorflow is 1.1.0

[yzcjtr]

Can you post your test command here? Please make sure the seq_length is consistent between data preparation and test stage. Also, try to run the code within a single GPU.

[ravikt]

The full command is as follows python geonet_main.py --mode=test_pose --dataset_dir=/ravikt/geonet_data/processed/ --init_ckpt_file=/ravikt/geonet/geonet_posenet/model --batch_size=1 --seq_length=5 --pose_test_seq=8 --output_dir=/ravikt/geonet_data/predictions/ The code ran error free on the processed data on a single gpu with --seq_length=5. However, I did not get any output predictions. The image loading part in geonet_test_pose.py assumes the directory structure to be of the form sequences/08/image_2, but the after running prepare_train_data.py we do not obtain the data in that format. I am doubtful if the code is able to read the images at all. Do I need to to put all the images in separate image_2 folder ?

The processed data is in jpg, After I changed .png in https://github.com/yzcjtr/GeoNet/blob/5b176025bc63563ef53297aa3d20cc6e575fb833/geonet_test_pose.py#L31 to .jpg. I go the following inputs[b] = image_seq ValueError: could not broadcast input array from shape (128,416,5) into shape (128,416,15)

[yzcjtr]

I guess the data preprocessing is incorrect. Can you post your data preprocessing command here as well? Also, check your formatted data storage. If these files are generated properly, I'm pretty sure you will get reasonable results.

[ravikt]

python prepare_train_data.py --dataset_dir=/home/ravikt/geonet_data/original/ --dataset_name=kitti_odom --dump_root=/home/ravikt/geonet_data/processed/ --seq_length=5 --img_height=128 --img_width=416 --num_threads=16 --remove_static

the processed data has the following directory structure

├── sequences
│   ├── 00
│   ├── 01
│   ├── 02
│   ├── 03
│   ├── 04
│   ├── 05
│   ├── 06
│   ├── 07
│   └── 08
├── train.txt
└── val.txt

The directory structure inside 08 is as follows. times.txt is from the original KITTI odom dataset

.
├── image_0
│   ├── 000002_cam.txt
│   ├── 000002.jpg
│   ├── 000003_cam.txt
│   ├── 000003.jpg
 .    .
 .    .
│   ├── 004068_cam.txt
│   ├── 004068.jpg
└── times.txt

[yzcjtr]

You should pass the original KITTI odometry dataset to the --data_dir argument instead of the processed dataset. This was clarified in the readme file.

[ravikt]

I did pass the originals. The first post in this issue has output error messages for both seq_length of 3 and 5. Those errors are encountered at https://github.com/yzcjtr/GeoNet/blob/5b176025bc63563ef53297aa3d20cc6e575fb833/geonet_test_pose.py#L60

However, your readme clearly states "For replicating our results in all of the three tasks (monocular depth, camera pose and optical flow), you need to download the following datasets, and preprocess them into certain formats"

Are you suggesting that preprocessed data is only for training phase and the original data for testing ?

[yzcjtr]

Yes, please read the test part of our readme file more carefully. Your last posted command suggests the usage of the formatted dataset. There also exists inconsistency between different commands you posted. Again, use a single GPU and the original dataset for test.

[ravikt]

Ok, The last posted command is only for data preprocessing, since you asked if the formatted data is generated correctly. I am running the test on original dataset using the following python geonet_main.py --mode=test_pose --dataset_dir=/ravikt/geonet_data/original/ --init_ckpt_file=/ravikt/geonet/geonet_posenet/model --batch_size=1 --seq_length=5 --pose_test_seq=9 --output_dir=/ravikt/geonet_data/predictions/ it gives File "/ravikt/geonet/GeoNet/geonet_test_pose.py", line 60, in test_pose inputs[b] = image_seq ValueError: could not broadcast input array from shape (128,416,5) into shape (128,416,15)

[ravikt]

Hi @yzcjtr . Thank you for the patient answers. I will have look again on the codes and readme.