Dataset Versions
Versions
2022-08-03 3:23pm
v34
· 2 years ago
2022-08-03 3:23pm
v33
· 2 years ago
OysterDatasetv7
v32
· 2 years ago
OysterDatasetv6Augmented
v31
· 2 years ago
OysterDatasetv6
v30
· 2 years ago
OysterDatasetv5
v29
· 2 years ago
OysterDatasetv5-1kImages
v28
· 2 years ago
1024x1024Augmented
v26
· 2 years ago
2022-07-15 10:21am
v25
· 2 years ago
2022-07-15 10:14am
v24
· 2 years ago
2022-07-15 8:33am
v23
· 2 years ago
2022-07-14 8:30pm
v22
· 2 years ago
2022-07-14 10:21am
v20
· 2 years ago
HeavyAugmentationv3
v19
· 2 years ago
2022-07-08 3:58pm
v17
· 2 years ago
2022-07-08 3:11pm
v16
· 2 years ago
2022-07-08 3:02pm
v15
· 2 years ago
2022-07-08 2:56pm
v14
· 2 years ago
2022-07-08 1:50pm
v13
· 2 years ago
2022-07-08 1:37pm
v12
· 2 years ago
NoAugmentationv2
v11
· 2 years ago
AugmentedContrastDataset
v10
· 2 years ago
2022-07-08 9:12am
v6
· 2 years ago
ThreeStatesv2Augmented
v4
· 2 years ago
ThreeStatesv1Augmented
v3
· 2 years ago
v31
OysterDatasetv6Augmented
Generated on Jul 21, 2022
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.
Other Formats
Choose another format.
2688 Total Images
View All Images
Dataset Split
Train Set 94%
2532Images
Valid Set 5%
125Images
Test Set 1%
31Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Rotation: Between -45° and +45°
Shear: ±45° Horizontal, ±45° Vertical
Brightness: Between -25% and +25%
Noise: Up to 5% of pixels
Cutout: 15 boxes with 5% size each