Dataset Versions
Versions
4x5 tiles
v38
· 7 months ago
3x3 tiles
v37
· 7 months ago
Full images
v36
· 7 months ago
2024-04-25 2-09pm - for pre-labelling model -no resize-
v35
· 8 months ago
2024-04-24 9-50am - for pre-labelling model
v34
· 8 months ago
2023-04-25 11:20am
v33
· 2 years ago
3x3 tiles
v32
· 2 years ago
4x5 tiles
v31
· 2 years ago
Full images
v30
· 2 years ago
4x5 tiled images 2023-01-04 12-58pm
v29
· 2 years ago
3x3 tiled images 2023-01-04 12-56pm
v28
· 2 years ago
Full images 2023-01-04 12-54pm
v27
· 2 years ago
rotifer_parts
v26
· 2 years ago
RF-Support-Test_tiling
v25
· 2 years ago
rotifer_parts_for_keypoint2
v24
· 2 years ago
rotifer_parts_for_keypoint
v23
· 2 years ago
no_tiling
v22
· 2 years ago
beadClusterOmitted_raw-images
v20
· 2 years ago
raw-images_allClasses
v19
· 2 years ago
bug-fix_TEST
v15
· 3 years ago
2022-05-31 2:21pm
v9
· 3 years ago
2022-05-31 tiling 4 -no resizing-
v8
· 3 years ago
2022-05-31 tiling 3
v7
· 3 years ago
2022-05-31 with tiling 2
v6
· 3 years ago
2022-05-31 with tiling
v5
· 3 years ago
2022-05-31
v4
· 3 years ago
joyce_2022-05-24
v3
· 3 years ago
joyce_drop_class
v2
· 3 years ago
joyce_data
v1
· 3 years ago
v7
2022-05-31 tiling 3
Generated on May 31, 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
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368 Total Images
View All Images
Dataset Split
Train Set 83%
304Images
Valid Set 4%
16Images
Test Set 13%
48Images
Preprocessing
Auto-Orient: Applied
Tile: 2 rows x 2 columns
Modify Classes: 0 remapped, 0 dropped
Augmentations
Outputs per training example: 4
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -12° and +12°