Dataset Versions
Versions
2023-04-14 12:13pm
v30
· 2 years ago
2023-04-14 10:18am
v29
· 2 years ago
2023-04-13 9:04pm
v28
· 2 years ago
2023-04-12 12:46am
v27
· 2 years ago
2023-04-12 12:16am
v26
· 2 years ago
2023-04-11 6:59pm
v25
· 2 years ago
2023-04-10 3:24pm
v24
· 2 years ago
2023-04-09 9:58pm
v23
· 2 years ago
2023-04-09 12:33am
v22
· 2 years ago
2023-04-08 1:37pm
v21
· 2 years ago
2023-04-06 11:36pm
v20
· 2 years ago
2023-04-06 3:41pm
v19
· 2 years ago
2023-04-06 12:10am
v18
· 2 years ago
2023-04-03 3:55pm
v17
· 2 years ago
2023-04-03 12:37am
v16
· 2 years ago
2023-04-02 5:31pm
v15
· 2 years ago
2023-04-02 3:54pm
v14
· 2 years ago
2023-04-02 2:55pm
v13
· 2 years ago
2023-03-31 12:11am
v12
· 2 years ago
2023-03-28 7:45pm
v11
· 2 years ago
2023-03-28 6:46pm
v10
· 2 years ago
2023-03-28 5:20pm
v9
· 2 years ago
2023-03-28 9:09am
v8
· 2 years ago
2023-03-27 11:49pm
v7
· 2 years ago
2023-03-27 6:17pm
v6
· 2 years ago
2023-03-27 10:59am
v5
· 2 years ago
2023-03-27 9:51am
v4
· 2 years ago
2023-03-26 11:12pm
v3
· 2 years ago
2023-03-26 8:27pm
v2
· 2 years ago
2023-03-26 2:06pm
v1
· 2 years ago
v29
2023-04-14 10:18am
Generated on Apr 14, 2023
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.
1427 Total Images
View All Images
Dataset Split
Train Set 89%
1274Images
Valid Set 7%
102Images
Test Set 4%
51Images
Preprocessing
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 2
Cutout: 1 boxes with 33% size each
Mosaic: Applied
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical