Coconut Logistics Dataset
v3
2023-11-02 3:08pm
Generated on Nov 2, 2023
Popular Download Formats
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
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2368 Total Images
View All Images
Dataset Split
Train Set 93%
2202Images
Valid Set 4%
83Images
Test Set 4%
83Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 10-90% Horizontal Region, 5-95% Vertical Region
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 5% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±6° Horizontal, ±6° Vertical
Exposure: Between -5% and +5%
Noise: Up to 1% of pixels
Cutout: 5 boxes with 10% size each
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±6° Horizontal, ±6° Vertical