DOI: 10.5281/zenodo.4726662
title: Dolphins-Detection-and-Tracking from Aerial Videos and Images

description: Dataset includes aerial images and videos of dolphins, being taken by drones. The data was captured from few places (Italy and Israel coast lines). The datsaset was collected in aim to perform automated dolphins detection of aerial images, and dolphins tracking from aerial videos. The Project description and results in the github link, which describes and visualizes the paper (link to the paper). The dataset includes two zip files: Detection.zip Tracking.zip For both files, the data annotation format is identical, and described below. In aim to watch each file content, use the preview option, in addition a description appears later on this section.<br> <strong>Annotations format</strong> The data annotation format is inspired by the requested format of Keras RetinaNet Implementation, which was used for training in the Dolphins Detection Phase. Each object is annotated by a bounding box. All data was annotated using Labelbox application. For each subset there are two corresponded CSV files: Annotation file Class mapping file Each line in the <strong>Annotations CSV</strong> file contains an annotation (bounding box) in an image or frame.<br> The format of each line of the CSV annotation is: <pre><code>path/to/image.jpg,x1,y1,x2,y2,class_name</code></pre> <em>path/to/image.jpg -</em> a path to the image/frame <em>x1, y1 - </em>image coordinates of the left upper corner of the bounding box <em>x2, y2 - </em>image coordinates of the right bottom corner of the bounding box <em>class_name</em> - class name of the annotated object An example from <em>`train_set.csv`</em>: <pre><code>.\train_set\1146_20170730101_ce1_sc_GOPR3047 103.jpg,506,644,599,681,Dolphin .\train_set\1146_20170730101_ce1_sc_GOPR3047 103.jpg,394,754,466,826,Dolphin .\train_set\1147_20170730101_ce1_sc_GOPR3047 104.jpg,613,699,682,781,Dolphin .\train_set\1147_20170730101_ce1_sc_GOPR3047 104.jpg,528,354,586,443,Dolphin .\train_set\1147_20170730101_ce1_sc_GOPR3047 104.jpg,633,250,723,307,Dolphin</code></pre> This defines a dataset with 2 images: <em>`1146_20170730101_ce1_sc_GOPR3047 103.jpg`</em> contains 2 bounding boxes which contains dolphins. <em>`1146_20170730101_ce1_sc_GOPR3047 104.jpg`</em> contains 3 bounding boxes which contains dolphins. Each line in the <strong>Class Mapping CSV</strong> file contains a mapping: <pre><code>class_name,id</code></pre> An example: <pre><code>Dolphin,0</code></pre> <strong>Detection</strong> The data for dolphins' detection is separated to three sub-directories: train, validation and test sets. Since all files contain only one class - `Dolphin`, there is one `class_mapping.csv` which is can be used for all the three subsets. Detection dataset folder includes: A folder for each - train, validation and test sets, which includes the images An annotations CSV file for each - train, validation and test sets A class mapping csv file (for all the sets) There is an annotation CSV file for each of the subset. <strong>Tracking</strong> For the tracking phase, trackers were examined and evaluated on 5 videos. Each video has its annotation and class mapping CSV files. In addition, extracted each video's frames are available in the <em>frames </em>directory. Tracking dataset folder includes a folder for each video (5 videos), which contain: frames directory, which includes extracted frames of the video An annotations CSV A class mapping csv file The original video The examined videos description and details: <strong>Detection and Tracking dataset structure:</strong> <pre><code>Detection |——————train_set (images) |——————train_set.csv |——————validation_set (images) |——————train_set.csv |——————test_set (images) |——————train_set.csv └——————class_mapping.csv Tracking |——————DJI_0195_trim_0015_0045 | └——————frames (images) | └——————annotations_DJI_0195_trim_0015_0045.csv | └——————class_mapping_DJI_0195_trim_0015_0045.csv | └——————DJI_0195_trim_0015_0045.MP4 |——————DJI_0395_trim_0010_0025 | └——————frames (images) | └——————annotations_DJI_0395_trim_0010_0025.csv | └——————class_mapping_DJI_0395_trim_0010_0025.csv | └——————DJI_0195_trim_0015_0045.MP4 |——————DJI_0395_trim_00140_00150 | └——————frames (images) | └——————annotations_DJI_0395_trim_00140_00150.csv | └——————class_mapping_DJI_0395_trim_00140_00150.csv | └——————DJI_0395_trim_00140_00150.MP4 |——————DJI_0395_trim_0055_0085 | └——————frames (images) | └——————annotations_DJI_0395_trim_0055_0085.csv | └——————class_mapping_DJI_0395_trim_0055_0085.csv | └——————DJI_0395_trim_0055_0085.MP4 └——————HighToLow_trim_0045_0070 └—————frames (images) └—————annotations_HighToLow_trim_0045_0070.csv └—————class_mapping_HighToLow_trim_0045_0070.csv └—————HighToLow_trim_0045_0070.MP4 </code></pre>
description: Project Description and Results: https://github.com/opherbambi/Dolphins-Detection-and-Tracking (github)