Dataset Versions
Versions
2024-07-04 1:40am
v25
· 6 months ago
2024-07-04 1:34am
v24
· 6 months ago
2024-07-03 10:01pm
v23
· 6 months ago
2024-06-20 10:36pm
v22
· 6 months ago
2024-06-20 10:30pm
v21
· 6 months ago
Grey 2x2
v20
· 7 months ago
Color 2x2
v19
· 7 months ago
grey full size
v17
· 7 months ago
Color Full Size
v16
· 7 months ago
V14
v14
· 8 months ago
v13
v13
· 8 months ago
v12
v12
· 8 months ago
Test Case-3
v11
· 8 months ago
Test Case-2 - gray version - full size
v10
· 8 months ago
Test Case-1 - color version - 2x2
v9
· 8 months ago
Test Case-1 - gray version - 2x2
v8
· 8 months ago
2024-03-28 6:36pm
v6
· 9 months ago
2024-03-13 7:19pm
v5
· 9 months ago
2024-03-13 6:10pm
v4
· 9 months ago
2024-03-13 3:38pm
v3
· 9 months ago
2023-12-24 9:38am
v2
· a year ago
2023-12-24 9:33am
v1
· a year ago
v8
Test Case-1 - gray version - 2x2
Generated on Apr 17, 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.
Other Formats
Choose another format.
488 Total Images
View All ImagesDataset Split
Train Set 75%
368Images
Valid Set 8%
40Images
Test Set 16%
80Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Grayscale: Applied
Tile: 2 rows x 2 columns
Modify Classes: 0 remapped, 6 dropped
Augmentations
Outputs per training example: 2
Flip: Horizontal, Vertical
Saturation: Between -15% and +15%
Brightness: Between -25% and +25%