This dataset is restricted and certain files cannot be downloaded yet. They will be made available on 2025-08-03
| Data File(s) | Type | Description | Action |
|---|---|---|---|
925893_v1_mysid-movies.csv (8.99 KB) | Comma Separated Values (.csv) | Collection and camera metadata associated with mysid movies (primary and secondary cameras). See "Parameters" section for column information (descriptions, units). | |
Mysid_movies_summer2023_Maine_P.zip (27.34 GB) | ZIP Archive (ZIP) | Zip package containing 39 videos (MP4 format) of the raw images from the primary camera. Each movie is a compilation of all the raw images in a single dataset (e.g. P80). See "Data processing" section for more details. File naming conventions: Maine_2023_Pxx_FPS_yy or Maine_2023_Sxx_FPS_yy as the naming protocol (for primary and secondary cameras, where xx represent the number of the dataset, e.g., P80, S80 and yy represents the frame rate at which the data is recorded). | |
Mysid_movies_summer2023_Maine_S.zip (27.11 GB) | ZIP Archive (ZIP) | Zip package containing 39 videos (MP4 format) of the raw images from the primary camera. Each movie is a compilation of all the raw images in a single dataset (e.g. P80). See "Data processing" section for more details. File naming conventions: Maine_2023_Pxx_FPS_yy or Maine_2023_Sxx_FPS_yy as the naming protocol (for primary and secondary cameras, where xx represent the number of the dataset, e.g., P80, S80 and yy represents the frame rate at which the data is recorded). | |
| Supplemental File(s) | Type | Description | Action |
file_inventory.csv (9.74 KB) | Comma Separated Values (.csv) | Inventory table for each of the .mp4 files provided in this dataset. Columns: filename, video filename filesize_bytes, filesize in bytes md5sum, checksum (md5) that can be used to verify integrity of the file after transfers within_zip_package, the name of the .zip package this file is within in the dataset | |
video_from_imgs.txt (2.90 KB) | Plain Text | Python script which converts a sequence of images into a video file using OpenCV library. Amber's edit: Python code which converts a sequence of images into a video file using OpenCV library. Code as used within a python notebook. |
Files
Filename: 925893_v1_mysid-movies.csv (8.99 KB)
Type: Comma Separated Values (.csv)
Description: Collection and camera metadata associated with mysid movies (primary and secondary cameras). See "Parameters" section for column information (descriptions, units).
Type: Comma Separated Values (.csv)
Description: Collection and camera metadata associated with mysid movies (primary and secondary cameras). See "Parameters" section for column information (descriptions, units).
Filename: Mysid_movies_summer2023_Maine_P.zip (27.34 GB)
Type: ZIP Archive (ZIP)
Description: Zip package containing 39 videos (MP4 format) of the raw images from the primary camera. Each movie is a compilation of all the raw images in a single dataset (e.g. P80). See "Data processing" section for more details. File naming conventions: Maine_2023_Pxx_FPS_yy or Maine_2023_Sxx_FPS_yy as the naming protocol (for primary and secondary cameras, where xx represent the number of the dataset, e.g., P80, S80 and yy represents the frame rate at which the data is recorded).
Type: ZIP Archive (ZIP)
Description: Zip package containing 39 videos (MP4 format) of the raw images from the primary camera. Each movie is a compilation of all the raw images in a single dataset (e.g. P80). See "Data processing" section for more details. File naming conventions: Maine_2023_Pxx_FPS_yy or Maine_2023_Sxx_FPS_yy as the naming protocol (for primary and secondary cameras, where xx represent the number of the dataset, e.g., P80, S80 and yy represents the frame rate at which the data is recorded).
Filename: Mysid_movies_summer2023_Maine_S.zip (27.11 GB)
Type: ZIP Archive (ZIP)
Description: Zip package containing 39 videos (MP4 format) of the raw images from the primary camera. Each movie is a compilation of all the raw images in a single dataset (e.g. P80). See "Data processing" section for more details. File naming conventions: Maine_2023_Pxx_FPS_yy or Maine_2023_Sxx_FPS_yy as the naming protocol (for primary and secondary cameras, where xx represent the number of the dataset, e.g., P80, S80 and yy represents the frame rate at which the data is recorded).
Type: ZIP Archive (ZIP)
Description: Zip package containing 39 videos (MP4 format) of the raw images from the primary camera. Each movie is a compilation of all the raw images in a single dataset (e.g. P80). See "Data processing" section for more details. File naming conventions: Maine_2023_Pxx_FPS_yy or Maine_2023_Sxx_FPS_yy as the naming protocol (for primary and secondary cameras, where xx represent the number of the dataset, e.g., P80, S80 and yy represents the frame rate at which the data is recorded).
Supplemental Files
Filename: file_inventory.csv (9.74 KB)
Type: Comma Separated Values (.csv)
Description: Inventory table for each of the .mp4 files provided in this dataset. Columns: filename, video filename filesize_bytes, filesize in bytes md5sum, checksum (md5) that can be used to verify integrity of the file after transfers within_zip_package, the name of the .zip package this file is within in the dataset
Type: Comma Separated Values (.csv)
Description: Inventory table for each of the .mp4 files provided in this dataset. Columns: filename, video filename filesize_bytes, filesize in bytes md5sum, checksum (md5) that can be used to verify integrity of the file after transfers within_zip_package, the name of the .zip package this file is within in the dataset
Filename: video_from_imgs.txt (2.90 KB)
Type: Plain Text
Description: Python script which converts a sequence of images into a video file using OpenCV library. Amber's edit: Python code which converts a sequence of images into a video file using OpenCV library. Code as used within a python notebook.
Type: Plain Text
Description: Python script which converts a sequence of images into a video file using OpenCV library. Amber's edit: Python code which converts a sequence of images into a video file using OpenCV library. Code as used within a python notebook.
