STEM_DETECTION_DATASET

The stem detection dataset includes RGB images that were collected specifically for training and validation of stem detection algorithms. There are a total of 573 RGB images, 508 of which were used for training and 65 for validation. These images were taken with an Intel Realsense D435 camera positioned at a variable distance of 20 to 50 centimeters from the grapes. The images' resolution is set to 1920 x 1080 pixels, resulting in a detailed and comprehensive visual dataset for the development and evaluation of stem detection algorithms.  All of the data were collected at Ktima Gerovassiliou in Epanomi, Thessaloniki.

Below, there are three separate folders with the training data (which can be merged into one) and one folder containing the validation data. Every image has a txt file containing the image's stem annotations. The first number represents the annotation's class (0 for stem), and the remaining numbers are the normalized (in the image's shape) coordinates of the stem's mask.