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6 results for “image SUITABILITY”
Metadata of a Large Sonar and Stereo Camera Dataset Suitable for Sonar-to-RGB Image Translation
<h1>Metadata of a Large Sonar and Stereo Camera Dataset Suitable for Sonar-to-RGB Image Translation</h1> <h2>Introduction</h2> <p>This is a set of metadata describing a large dataset of synchronized sonar and stereo camera recordings, that were captured between August 2021 and September 2023 during the project <a href="https://robotik.dfki-bremen.de/en/research/projects/deepersense/">DeeperSense</a> (https://robotik.dfki-bremen.de/en/research/projects/deepersense/), as training data for Sonar-to-RGB image translation. <a href="../records/7728089">Parts</a> <a href="../records/10220989">of</a> the sensor data have been published (https://zenodo.org/records/7728089, https://zenodo.org/records/10220989). Due to the size of the sensor data corpus, it is currently impractical to make the entire corpus accessible online. Instead, this metadatabase serves as a relatively compact representation, allowing interested researchers to inspect the data, and select relevant portions for their particular use case, which will be made available on demand. This is an effort to comply with the <a href="https://www.go-fair.org/fair-principles/">FAIR</a> principle A2 (https://www.go-fair.org/fair-principles/) that metadata shall be accessible, even when the base data is not immediately.</p> <h3>Locations and sensors</h3> <p>The sensor data was captured at four different locations, including one laboratory (Maritime Exploration Hall at DFKI RIC Bremen) and three field locations (Chalk Lake Hemmoor, Tank Wash Basin Neu-Ulm, Lake Starnberg). At all locations, a ZED camera and a Blueprint Oculus M1200d sonar were used. Additionally, a SeaVision camera was used at the Maritime Exploration Hall at DFKI RIC Bremen and at the Chalk Lake Hemmoor. The <code>examples/</code> directory holds a typical output image for each sensor at each available location.</p> <h3>Data volume per session</h3> <p>Six data collection sessions were conducted. The table below presents an overview of the amount of data captured in each session:</p> <table> <tbody> <tr> <th>Session dates</th> <th>Location</th> <th>Number of datasets</th> <th>Total duration of datasets [h]</th> <th>Total logfile size [GB]</th> <th>Number of images</th> <th>Total image size [GB]</th> </tr> <tr> <td>2021-08-09 - 2021-08-12</td> <td>Maritime Exploration Hall at DFKI RIC Bremen</td> <td>52</td> <td>10.8</td> <td>28.8</td> <td>389’047</td> <td>88.1</td> </tr> <tr> <td>2022-02-07 - 2022-02-08</td> <td>Maritime Exploration Hall at DFKI RIC Bremen</td> <td>35</td> <td>4.4</td> <td>54.1</td> <td>629’626</td> <td>62.3</td> </tr> <tr> <td>2022-04-26 - 2022-04-28</td> <td>Chalk Lake Hemmoor</td> <td>52</td> <td>8.1</td> <td>133.6</td> <td>1’114’281</td> <td>97.8</td> </tr> <tr> <td>2022-06-28 - 2022-06-29</td> <td>Tank Wash Basin Neu-Ulm</td> <td>42</td> <td>6.7</td> <td>144.2</td> <td>824’969</td> <td>26.9</td> </tr> <tr> <td>2023-04-26 - 2023-04-27</td> <td>Maritime Exploration Hall at DFKI RIC Bremen</td> <td>55</td> <td>7.4</td> <td>141.9</td> <td>739’613</td> <td>9.6</td> </tr> <tr> <td>2023-09-01 - 2023-09-02</td> <td>Lake Starnberg</td> <td>19</td> <td>2.9</td> <td>40.1</td> <td>217’385</td> <td>2.3</td> </tr> <tr> <th> </th> <th> </th> <th>255</th> <th>40.3</th> <th>542.7</th> <th>3’914’921</th> <th>287.0</th> </tr> </tbody> </table> <h2>Data and metadata structure</h2> <h3>Sensor data corpus</h3> <p>The sensor data corpus comprises two processing stages:</p> <ul> <li>raw data streams stored in ROS bagfiles (aka <strong>logfiles</strong>),</li> <li>camera and sonar images (aka <strong>datafiles</strong>) extracted from the logfiles.</li> </ul> <p>The files are stored in a file tree hierarchy which groups them by session, dataset, and modality:</p> <pre><code>${session_key}/ ${dataset_key}/ ${logfile_name} ${modality_key}/ ${datafile_name}</code></pre> <p>A typical logfile path has this form:</p> <pre><code>2023-09_starnberg_lake/ 2023-09-02-15-06_hydraulic_drill/ stereo_camera-zed-2023-09-02-15-06-07.bag</code></pre> <p>A typical datafile path has this form:</p> <pre><code>2023-09_starnberg_lake/ 2023-09-02-15-06_hydraulic_drill/ zed_right/ 1693660038_368077993.jpg</code></pre> <p>All directory and file names, and their particles, are designed to serve as identifiers in the metadatabase. Their formatting, as well as the definitions of all terms, are documented in the file <code>entities.json</code>.</p> <h3>Metadatabase</h3> <p>The metadatabase is provided in two equivalent forms:</p> <ul> <li>as a standalone <a href="https://www.sqlite.org/index.html">SQLite</a> (https://www.sqlite.org/index.html) database file <code>metadata.sqlite</code> for users familiar with SQLite,</li> <li>as a collection of CSV files in the <code>csv/</code> directory for users who prefer other tools.</li> </ul> <p>The database file has been generated from the CSV files, so each database table holds the same information as the corresponding CSV file. In addition, the metadatabase contains a series of convenience views that facilitate access to certain aggregate information.</p> <p>An entity relationship diagram of the metadatabase tables is stored in the file <code>entity_relationship_diagram.png</code>. Each entity, its attributes, and relations are documented in detail in the file <code>entities.json</code></p> <p>Some general design remarks:</p> <ul> <li>For convenience, timestamps are always given in both a human-readable form (ISO 8601 formatted datetime strings with explicit local time zone), and as seconds since the UNIX epoch.</li> <li>In practice, each logfile always contains a single stream, and each stream is stored always in a single logfile. Per database schema however, the entities <code>stream</code> and <code>logfile</code> are modeled separately, with a “many-streams-to-one-logfile” relationship. This design was chosen to be compatible with, and open for, data collections where a single logfile contains multiple streams.</li> <li>A <code>modality</code> is not an attribute of a <code>sensor</code> alone, but of a <code>datafile</code>: Because a <code>sensor</code> is an attribute of a <code>stream</code>, and a single stream may be the source of multiple modalities (e.g. RGB vs. grayscale images from the same camera, or cartesian vs. polar projection of the same sonar output). Conversely, the same modality may originate from different sensors.</li> </ul> <p>As a usage example, the data volume per session which is tabulated at the top of this document, can be extracted from the metadatabase with the following SQL query:</p> <div> <pre><code><span><span>SELECT</span></span> <span> PRINTF(</span> <span> <span>'%s - %s'</span>,</span> <span> <span>SUBSTR</span>(session_start, <span>1</span>, <span>10</span>),</span> <span> <span>SUBSTR</span>(session_end, <span>1</span>, <span>10</span>)) <span>AS</span> <span>'Session dates'</span>,</span> <span> location_name_english <span>AS</span> Location,</span> <span> number_of_datasets <span>AS</span> <span>'Number of datasets'</span>,</span> <span> total_duration_of_datasets_h <span>AS</span> <span>'Total duration of datasets [h]'</span>,</span> <span> total_logfile_size_gb <span>AS</span> <span>'Total logfile size [GB]'</span>,</span> <span> number_of_images <span>AS</span> <span>'Number of images'</span>,</span> <span> total_image_size_gb <span>AS</span> <span>'Total image size [GB]'</span></span> <span><span>FROM</span></span> <span> location</span> <span> <span>JOIN</span> <span>session</span> <span>USING</span> (location_id)</span> <span> <span>JOIN</span> (</span> <span> <span>SELECT</span></span> <span> session_id,</span> <span> <span>COUNT</span>(dataset_id) <span>AS</span> number_of_datasets,</span> <span> <span>ROUND</span>(</span> <span> <span>SUM</span>(dataset_duration) <span>/</span> <span>3600</span>,</span> <span> <span>1</span>) <span>AS</span> total_duration_of_datasets_h,</span> <span> <span>ROUND</span>(</span> <span> <span>SUM</span>(total_logfile_size) <span>/</span> <span>10e9</span>,</span> <span> <span>1</span>) <span>AS</span> total_logfile_size_gb</span> <span> <span>FROM</span></span> <span> location</span> <span> <span>JOIN</span> <span>session</span> <span>USING</span> (location_id)</span> <span> <span>JOIN</span> dataset <span>USING</span> (session_id)</span> <span> <span>JOIN</span> view__dataset_total_logfile_size <span>USING</span> (dataset_id)</span> <span> <span>GROUP</span> <span>BY</span></span> <span> session_id</span> <span> ) <span>USING</span> (session_id)</span> <span> <span>JOIN</span> (</span> <span> <span>SELECT</span></span> <span> session_id,</span> <span> <span>COUNT</span>(datafile_id) <span>AS</span> number_of_images,</span> <span> <span>ROUND</span>(<span>SUM</span>(datafile_size) <span>/</span> <span>10e9</span>, <span>1</span>) <span>AS</span> total_image_size_gb</span> <span> <span>FROM</span></span> <span> <span>session</span></span> <span> <span>JOIN</span> dataset <span>USING</span> (session_id)</span> <span> <span>JOIN</span> stream <span>USING</span> (dataset_id)</span> <span> <span>JOIN</span> <span>datafile</span> <span>USING</span> (stream_id)</span> <span> <span>GROUP</span> <span>BY</span></span> <span> session_id</span> <span> ) <span>USING</span> (session_id)</span> <span><span>ORDER</span> <span>BY</span> session_id;</span></code></pre> </div>
Data from: SLICE-MSI: A machine learning interface for system suitability testing of mass spectrometry imaging platforms
Open the record for dataset details and reuse information.
Image 2 in Habitat suitability, threats and conservation strategies of Hump-nosed Pit Viper Hypnale hypnale Merrem (Reptilia: Viperidae) found in Western Ghats, Goa, India
Image 2. Gravid female killed in cashew plantation during weed clearance
Image 1 in Habitat suitability, threats and conservation strategies of Hump-nosed Pit Viper Hypnale hypnale Merrem (Reptilia: Viperidae) found in Western Ghats, Goa, India
Image 1. Hypnale hypnale in natural habitat
Assessing the Suitability of an Imaging Probe for Use in Clinical Cell and Gene Therapy Trials in Cancer and Rheumatoid Arthritis
ClinicalTrials.gov study NCT00185848. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Is Eovist Suitable for Arterial-Phase MR Imaging of Liver
ClinicalTrials.gov study NCT02684526. IPD Sharing: NO. Countries: 1. Publications: 0.
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