The UAV-CM dataset is a comprehensive collection of images captured from low-altitude drones. This dataset was meticulously annotated by the CM Laboratory of Wuhan University of Technology, ensuring accuracy and reliability.
Containing a total of 7666 images, the UAV-CM dataset covers 11 diverse categories, each representing a different type of plant or object commonly found in agricultural or rural environments. These categories include Banana, Betel Nut, Coconut Tree, Corn, House, Jackfruit, Longan, Mango, Pepper, Pitaya, and Stream.
Here are the number of images in each category:
- Banana: 163 images
- Betel Nut: 1956 images
- Coconut Tree: 1904 images
- Corn: 270 images
- House: 394 images
- Jackfruit: 203 images
- Longan: 482 images
- Mango: 977 images
- Pepper: 426 images
- Pitaya: 761 images
- Stream: 130 images
The UAV-CM dataset is designed to serve as a valuable resource for researchers, developers, and enthusiasts interested in areas such as object detection, image classification, and remote sensing. It offers a unique challenge due to the diverse range of categories and the high-resolution images captured from drones.
You can download the UAV-CM dataset from the following link: Download. Please note that you may need to have a Baidu account or follow specific instructions to access the download link.
We encourage you to explore the UAV-CM dataset and use it to further advance the field of computer vision and related technologies.