bborja / mods_evaluation Goto Github PK

I followed the steps and placed the results in the below folder structure.

I used the below YAML file for evaluation .

PATHS:
  # Results output folder
  RESULTS: 'D:/WACV2022/mods_new_output/'
  # Path to where the dataset is stored
  DATASET: 'D:/WACV2022/mods/'
  # Path to where calibration files are stored
  DATASET_CALIB: 'D:/WACV2022/mods/calibration'
  # Path to where the segmentation predictions are stored
  SEGMENTATIONS: 'D:/WACV2022/mods_new_output/'

SEGMENTATIONS:
  # Prediciton dir structure:
  #  - False: pred_dir/method/sequence/frame.png
  #  - True:  pred_dir/sequence/method/frame.png
  SEQ_FIRST: False
  # Specify which colors are used in segmentation maps
  INPUT_COLORS: 
    - [0, 0, 0]    #[247, 195,  37] # Obstacle
    - [255, 0, 0]  #[ 41, 167, 224] # Water
    - [0, 255, 0]  #[ 90,  75, 164] # Sky

VISUALIZATION:
  # Display per-sequence evaluation progress
  SEQUENCE_PROGRESS: True

overlap_percentages, overlap_percentages_d = run_evaluation_image(self.cfg, File "D:\WACV2022\mods_evaluation-master\mods_evaluation-master\modb_evaluation.py", line 407, in run_evaluation_image raise 'Missing number of something for sequence %s frame %d' % (seq_path_split[0], frame_number) TypeError: exceptions must derive from BaseException

Hi,

I would like to thank you for your massive contribution. I am only confused with the amount of data made available with MODS dataset.

The paper says: We present a new diverse maritime evaluation dataset containing approximately 81k stereo images synchronized with an on-board IMU, with over 60k objects annotated.

However, upon download I was only able to find 16350 frames, i.e. 8175 stereo images.

I am wondering, is this only a publicly available evaluation subset of it? Can the rest of the data be accessed?

In the paper you also state that you have merged the MODD1, MODD2 and SMD datasets into a single MODS training
dataset, but it sounds something different to me. Anyway, it results only in 24k images.

Hello,

Thank you for this great repository.
I modified the paths and downloaded data with the masks.
However, I'm getting this error.

Hello,

First of all - thank you for building and sharing this awesome resource!

Next, a few clarifying questions:

1. As far as I understand, the dataset that you have made publicly available is the 'evaluation dataset' from you arXiv paper (which contains 8,175 frames). Are you also planning on making your training set available too? (I'm particularly interested in the object-detection training set that you've created by merging and re-annotating MODD1, MODD2 and SMD.)
2. Would I be able to run the benchmark on video data that do not have associated IMU data (roll, pitch, yam)?

Finally, a couple of issues I've run into when running the modb_evaluation.py evaluation script.

i. I get a bunch of warnings such as this one

WARN:[email protected]] global /io/opencv/modules/imgcodecs/src/loadsave.cpp (239) findDecoder imread_('/stru02-00116500-00117000/frames/ignore_mask.png'): can't open/read file: check file path/integrity

(Indeed the ignore_mask.png files appear not to be included in the dataset I've downloaded.)

ii. The script terminates prematurely with the following error message:

Traceback (most recent call last):
  File "/home/oliskir/computer-vision/mods/mods_evaluation/modb_evaluation.py", line 471, in <module>
    run_evaluation()
  File "/home/oliskir/computer-vision/mods/mods_evaluation/modb_evaluation.py", line 324, in run_evaluation
    write_json_file(cfg.PATHS.RESULTS, args.method, evaluation_results)
  File "/home/oliskir/computer-vision/mods/mods_evaluation/utils/utils.py", line 197, in write_json_file
    with open(os.path.join(output_path, output_file_name), 'w') as json_file:
FileNotFoundError: [Errno 2] No such file or directory: '../mods_wasr/results_../wasr_augm0_plainmaster4.json'

Probably something to do with the automatic construction of the output folder path? I've attached my config file to give you an idea of what my directory structure looks like.
mods.txt

Thanks!
Oliver