Dataset Versions
Versions
2024-04-24 1:44pm
v21
· 8 months ago
augmented_CaulastreaCR2
v20
· 8 months ago
augmented_AcanthophylliaCR_DS2
v19
· 8 months ago
augmented_BranchCR_DS2
v18
· 8 months ago
augmented_bushyCR_DS2
v17
· 8 months ago
augmented_CynarinaCR
v16
· 8 months ago
augmented_CaulastreaCR
v15
· 8 months ago
augmented_AcanthophylliaCR_DS
v14
· 8 months ago
augmented_bushyCR_DS
v13
· 8 months ago
augmented_BranchCR_DS
v12
· 8 months ago
2024-04-15 12:48pm
v11
· 8 months ago
AllDeadCoralReef_WithoutAugment
v10
· 9 months ago
2024-03-16 1:51am
v9
· 9 months ago
2024-03-15 8:14pm
v8
· 9 months ago
2024-03-14 10-36pm-BleachedExtra
v7
· 9 months ago
Bleach2
v6
· 9 months ago
2024-03-14 2:47am
v5
· 9 months ago
2024-03-13 11-35pm-Augmented Dead Coral Reef Extra3
v4
· 9 months ago
2024-03-13 9-51pm-Augmented Dead Coral Reef Extra2
v3
· 9 months ago
2024-03-12 8-48pm- Augmented Dead Coral Reef
v2
· 9 months ago
Bleach1
v1
· 9 months ago
v5
2024-03-14 2:47am
Generated on Mar 13, 2024
Popular Download Formats
YOLOv11
TXT annotations and YAML config used with YOLOv11.
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.
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653 Total Images
View All Images
Dataset Split
Train Set 92%
603Images
Valid Set 4%
25Images
Test Set 4%
25Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Saturation: Between -25% and +25%
Blur: Up to 2.5px
Noise: Up to 0.81% of pixels