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Python tool for working with the NOAA NOS Web Camera Applications Testbed (WebCAT)

Project description


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This repository provides a Pythonic way to interface with the NOAA National Ocean Service Web Camera Applications Testbed (WebCAT). The real-time data is hosted on the SECOORA site (The Southeast Coastal Ocean Observing Regional Association), on the dedicated WebCAT page. Historic data can also be accessed by retrieving files using specific HTTP requests (using a pattern described on the WebCAT page).

More details about WebCAT are available in this Open Access paper:

Dusek, G., Hernandez, D., Willis, M., Brown, J. A., Long, J. W., Porter, D. E., & Vance, T. C. (2019). WebCAT: Piloting the development of a web camera coastal observing network for diverse applications. Frontiers in Marine Science, 6, 353, 25 June 2019 |


pip install pywebcat



A key workflow for utilising WebCAT videos is to split videos into frames for further analysis. As a result, this functionality is exposed as a CLI with the command line argument pywebcat.

$ pywebcat --help
usage: [-h] -dir DIRECTORY -s STATION [STATION ...] -y YEAR
                       [YEAR ...] -m MONTH [MONTH ...] -d DAY [DAY ...] -t
                       TIME [TIME ...] [-i INTERVAL] [-n] [-v]

CLI for saving frames of webCAT video(s).

optional arguments:
  -h, --help            show this help message and exit
  -i INTERVAL, --interval INTERVAL
                        Interval in seconds between video frames to save
                        (default: 10).
  -n, --no_meta         Don't save .csv file of metadata of saved video
  -q QUALITY, --quality QUALITY
                        Quality of saved frames between 0 (lowest) and 100
                        (highest) (default: 95).
  -v, --verbose         Print program status.

required arguments:
  -dir DIRECTORY, --directory DIRECTORY
                        Absolute path of directory to save frames in.
  -s STATION [STATION ...], --station STATION [STATION ...]
                        The station name, e.g., buxtoncoastalcam.
  -y YEAR [YEAR ...], --year YEAR [YEAR ...]
                        The video year(s), e.g., 2019 2020.
  -m MONTH [MONTH ...], --month MONTH [MONTH ...]
                        The video month(s), e.g., 9 10 11.
  -d DAY [DAY ...], --day DAY [DAY ...]
                        The video day(s) e.g., 1 11 21.
  -t TIME [TIME ...], --time TIME [TIME ...]
                        The video time(s), e.g., 1000 1330 1510.

The CLI facilitates efficiently looping over input arguments to locate one or more WebCAT videos and split them into a desired number of frames which are then saved locally. Here's an example looping over several videos from the Buxton coastal camera on 13th Nov 2019 at different times (a 10 second interval is specified for saving the frames and verbosity is turned on):

$ pywebcat -dir /Users/tbeuzen/Downloads -s buxtoncoastalcam -y 2019 -m 11 -d 13 -t 1000 1210 1530 -i 10 -v
Saving frames of buxtoncoastalcam_2019_11_13_1000...
100%|██████████████████████████████████████████████| 62/62 [00:14<00:00,  4.22it/s]
Saving frames of buxtoncoastalcam_2019_11_13_1210...
100%|██████████████████████████████████████████████| 62/62 [00:13<00:00,  4.51it/s]
Saving frames of buxtoncoastalcam_2019_11_13_1530...
100%|██████████████████████████████████████████████| 62/62 [00:14<00:00,  4.38it/s]

The resultant directory structure looks like:

                └── buxtoncoastalcam
                    ├── buxtoncoastalcam_2019_11_13_1000
                    │   ├── buxtoncoastalcam_2019_11_13_1000.csv
                    │   └── jpg
                    │       ├── frame_0.jpg
                    │       ├── frame_280.jpg
                    │       ├── ...
                    ├── buxtoncoastalcam_2019_11_13_1210
                    │   ├── ...
                    └── buxtoncoastalcam_2019_11_13_1530
                        ├── ...

The outputted .csv file contains metadata for the saved frames:

url name frame path buxtoncoastalcam_2019_11_13_1000 0 /Users/tbeuzen/Downloads/buxtoncoastalcam/buxtoncoastalcam_2019_11_13_1000/jpg/frame_0.jpg buxtoncoastalcam_2019_11_13_1000 280 /Users/tbeuzen/Downloads/buxtoncoastalcam/buxtoncoastalcam_2019_11_13_1000/jpg/frame_280.jpg
... ... ... ...


The pywebcat utilities can also be imported through the pywebcat.utils for use in other libraries or workflows. See the demo Jupyter notebook for a worked example.

from pywebcat.utils import WebCAT
wc = WebCAT()
wc.generate_url("buxtoncoastalcam", 2019, 11, 13, 1000)  # create the video url

# attributes
wc.url     # the created url    # unique name for the video object
wc.width   # frame width in pixels
wc.height  # frame height in pixels
wc.frames  # total frames in video
wc.fps     # frames per second

# methods
wc.download_url()        # download the video at the url
wc.save_frames()         # save video frames as .jpg
wc.plot_frames()         # plot select video frames
wc.plot_average_frame()  # plot time-averaged frame


Contributions are welcome and greatly appreciated! If you're interested in contributing to this project, take a look at the contributor guide.


All contributions are welcomed and recognized! You can see a list of current contributors in the contributors tab.


Thanks to the Southeast Coastal Ocean Observing Regional Association (SECOORA) and the WebCAT project for making camera footage publicly available and supporting open science and data.

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