High Resolution Rose Growth Stage Image Dataset from Golap Gram, Savar, Bangladesh for Machine Learning and Precision Agriculture

The Rose Growth Stage data was sampled in Golap Gram, Savar, Dhaka, Bangladesh, which is among the most popular rose growing regions in Bangladesh. 565 images of rose plants were taken using high resolution with natural light conditions in the natural growth settings. Real rose gardens were directly photographed to capture natural variation in the appearance of plants, background as well as lighting conditions that are significant in the development of strong computer vision models. The dataset consists of various stages of growth of roses, and researchers can study the patterns of development and growth of plants through machine learning and deep learning methods. The data will be broken down into three stages of rose development in the following manner: 1. Early Stage: 98 2. Middle Stage: 289 3. Final Stage: 178 Total Images: 565 Geographical Location The images of all the rose growth stages were captured at Golap Gram, Savar, Dhaka, Bangladesh, a popular rose growing area in the nation where a large scale commercial flower production of roses is practiced. The place offers a wide range of natural environments that assist it in capturing natural life stages of plants. Place: Golap Gram, Savar, Dhaka, Bangladesh. Latitude: 23°48'5.808''N Longitude: 90°19'30.4908''E Use of the Dataset 1. To construct and test machine learning and deep learning models to classify the stage of growth in rose growth. 2. To assist with precision agriculture and plant phenotyping computer vision studies. 3. To assist in the creation of automated mechanisms to monitor the growth of rose plants by analyzing the images. 4. To help scientists develop AI-powered smart agriculture systems. 5. To offer a benchmark data-set in recognition of rose growth stage tasks. 6. To facilitate the design of mobile or web-based software to monitor plant growth.