This dataset presents a curated and preprocessed image collection of Indian apple fruits, specifically designed for machine learning and deep learning applications in fruit disease detection. It includes a total of 8,415 raw images, divided into 5,715 images of healthy apples and 2,700 images exhibiting rot disease symptoms. These images were captured in varied natural lighting and background conditions to ensure dataset diversity and real-world relevance.
While vision-based yield estimation systems are widely used for horticulture crops in recent days, accurately predicting yield in unstructured orchards remains a challenge. Automated UAV-based aerial data collection offers a scalable solution for such environments. This study utilizes UAVs to collect data from a target mango orchard, marking Points of Interest (PoIs) to ensure periodic video capture along the same path, maximizing coverage. A significant challenge addressed in this work is the detection of small mangoes in UAV-captured videos.
Images were collected manually using mobile phone cameras from two farms located in different regions. This introduces natural variance in lighting, soil, and background. Farm 1: Heera Recreation & Entertainment in Casarvane VP, Cansarvornem, Goa (Lat 15.704596° and Long 73.877316°). Farm 2: Mavlankar’s Cashew Plantation in Fakir patha, Goa (Lat 15.760858° and Long 73.885091°). Each image is labelled manually according to the visible maturity stage: Unripe: Green, hard, small cashew apples.
We created a 2563-image custom dragon fruit image dataset, with 1248 images of raw dragon fruits and 1315 photographs of ripe dragon fruits. The images were taken with the Nikon D5200 DSLR and OnePlus 6's Sony IMX 519 16 megapixel camera. The photographs taken with the DSLR camera had a resolution of 4000 by 6000 pixels, while those taken with the OnePlus6 had a resolution of 3456 by 4608 pixels. They were photographed in natural sunlight. The average temperature during that time was 28°C (84.2°F), with partly sunny skies, 65 percent humidity, and 17 km/h wind speeds.
