Investigating automated bird detection from webcams using machine learning

We provide a dataset of images(.jpeg) with their corresponding annotations files(.xml) used to train a bird detection deep learning model. These images were collected from the live stream feeds of  Cornell Lab of Ornithology (https://www.allaboutbirds.org/cams/) situated in 6 unique locations around the world as follows:

• Treman bird feeding garden at the Cornell Ornithology Laboratory in Ithaca, New York. At this station, Axis P11448-LE cameras are used to capture the recordings from feeders perched on the edge of both sapsucker woods and its 10-acre ponds. This site mainly attracts forest species like chickadees (Poecile atricapillus), red-winged blackbirds (Agelaius phoeniceus), and woodpeckers (Picidae). A total of 2065 images were captured from this location.
•  Fort Davis in Western Texas, USA. At this site, a total of 30  hummingbird feeder cams are hosted at an elevation of over 5500 feet. From this site, 1440 images were captured.
• Sachatamia Lodge in Mindo, Ecuador. This site has a live hummingbird feed watcher that attracts over 132 species of hummingbirds including: Fawn-breasted Brilliant, White-necked Jacobin, Purple-bibbed Whitetip, Violet-tailed Sylph, Velvet-purple Coronet, and many others. A total of 2063 images were captured from this location.
• Morris County, New Jersey, USA. Feeders at this location attract over 39 species including Red-bellied Woodpecker, Red-winged Blackbird, Purple Finch, Blue Jay, Pine Siskin, Hairy Woodpecker, and others. Footage at this site is captured by an Axis P1448-LE Camera and Axis T8351 Microphone. A total of 1876 images were recorded from this site.
• Canopy Lodge in El Valle de Anton, Panama. Over 158 bird species visit this location annually and these include Gray-headed Chachalaca, Ruddy Ground-Dove, White-tipped Dove, Green Hermit, and others. A total of 1600 images were captured.
• Southeast tip of South Island, New Zealand. At this site, nearly 10000 seabirds visit this location annually and a total of 1548 images were captured.

 The Cornell Lab of Ornithology is an institute dedicated to biodiversity conversation with the main focus on birds through research, citizen science, and education. The autoscreen software was used to capture the images from the live feeds and images of approximately 1 Megapixel (Joint Photographic Experts Group) JPEG coloured images of resolution $1366\times 768 \times 3$ pixels were collected (https://sourceforge.net/projects/autoscreen/). The software was taking a new image every 30 seconds and were captured during different times of the day in order to avoid a sample biased dataset. In total, 10592 images were collected for this study.

Files provided

Train.zip – contains 6779 image files(.jpeg) and 6779 annotation files (.xml)

Validation.zip – contains 1695 image files(.jpeg) and 1695 annotation files (.xml)

Test.zip –contains 2118 image files(.jpeg)

Scripts.zip - Contains scripts needed in manipulating the dataset like dataset partitioning, creation of CSV and tfrecords files. 

This dataset was used in the MSc thesis titled “Investigating automated bird detection from webcams using machine learning” by Alex Mirugwe, University of Cape Town – South Africa.