Datasets
Standard Dataset
BirDrone
- Citation Author(s):
-
Fatin NajihahMuhammad Zamri
IIUMTeddy SuryaGunawanIIUM - Submitted by:
- Teddy Surya Gunawan
- Last updated:
- Mon, 09/30/2024 - 11:26
- DOI:
- 10.21227/ettb-0w28
- Data Format:
- Research Article Link:
- Links:
- License:
1212 Views- Categories:
- Keywords:
1 rating - Please login to submit your rating.
Abstract
The BirDrone dataset is compiled by aggregating images of small drones and birds sourced from various online datasets. It comprises 2970 high-resolution images (640x640 pixels), each featuring unique backdrops and lighting conditions. This dataset is designed to enhance machine learning models by simulating real-world scenarios.
Dataset Specifications:
- Image Count: 2970 images, with 2617 drone images and 353 bird images.
- Image Resolution: Each image is uniformly sized at 640x640 pixels.
- Annotation Details: The dataset includes 6162 annotations with the smallest bounding box sized at 7x14 pixels and the largest at 65x182 pixels.
- Classes: Two categories are represented—drones and birds.
- Annotation Format: Annotations are formatted according to YOLOv8 specifications.
Pre-processing and Augmentation:
- Pre-processing Techniques: Images have undergone auto-orientation, resizing, and auto-contrast adjustments to standardize and enhance visual clarity.
- Augmentation Techniques: To increase variability and robustness, the images have been augmented with rotation and exposure adjustments, preparing the dataset for diverse environmental and lighting conditions.
Dataset Distribution:
- Training Set: 80% (2376 images)
- Validation Set: 20% (594 images)
File Size: 96.3 MB
Instructions:
The RAR file contains the train and valid folder. In each folder, there are images and labels folders, with data.yaml compatible with Roboflow.
Comments
I am interested in accessing the BirDrone dataset for a machine learning project. Could you please provide the necessary access or instructions on how to obtain it?
Thank you!