147 images 5 classes
by chocolate
244 images 31 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Random Gaussian blur of between 0 and 0.5 pixels * Random brigthness adjustment of between -16 and +16 percent * Random exposure adjustment of between -6 and +6 percent * Resize to 600x600 (Fit (white edges)) -black chocolate -brown chocolate -gift chocolate -wave chocolate -white chocolate 15 16 17 18 19 20 21
by nina
245 images 31 classes
chocolate * 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Random Gaussian blur of between 0 and 0.5 pixels * Random brigthness adjustment of between -16 and +16 percent * Random exposure adjustment of between -6 and +6 percent * Resize to 600x600 (Fit (white edges)) 15 16 17 18 19 20 21 ============================== Chocolates are annotated in YOLO v5 PyTorch format. It includes 267 images. The following augmentation was applied to create 5 versions of each source image:
1240 images 706 classes
102 images 3 classes
300 images 101 classes
Almond Toscani Altic Traditional Ardmona Chopped Tomatoes Arnott's Premier Aspro Clear Boag's Premium Boag's St George Brita Classic Brita Marella Cool Buckwheat Pancake Mix Butter Menthol CD Carbonell Coles Reliance Colgate Sensitive Coolabah Red Wine Dairy Milk Dandelion Natural Coffee Ease a cold Extra Virgin Olive Oil