Dataset Versions
Versions
2024-05-28 11:41am
v26
· 6 months ago
2024-05-28 11:38am
v25
· 6 months ago
2024-04-18 5:35pm
v24
· 7 months ago
2024-04-11 12:39pm
v23
· 7 months ago
2024-04-11 12:19pm
v22
· 7 months ago
2024-04-11 12:00pm
v21
· 7 months ago
2024-04-10 8:06pm
v20
· 7 months ago
2024-04-08 1:05pm
v19
· 8 months ago
2024-04-06 12:05pm
v18
· 8 months ago
2024-04-03 6:24pm
v17
· 8 months ago
2024-04-03 6:24pm
v16
· 8 months ago
2024-04-03 6:23pm
v15
· 8 months ago
2024-04-03 6:22pm
v14
· 8 months ago
2024-04-03 6:22pm
v13
· 8 months ago
2024-04-03 1:12pm
v12
· 8 months ago
2024-04-01 11:32am
v11
· 8 months ago
2024-04-01 11:15am
v10
· 8 months ago
2024-03-30 11:10pm
v9
· 8 months ago
2024-03-30 11:04pm
v8
· 8 months ago
2024-03-29 3:40pm
v7
· 8 months ago
2024-03-28 7:46am
v6
· 8 months ago
2024-03-27 8:37am
v5
· 8 months ago
2024-03-26 7:45pm
v4
· 8 months ago
2024-03-26 3:51pm
v3
· 8 months ago
2024-03-24 5:40pm
v2
· 8 months ago
2024-03-12 4:06pm
v1
· 8 months ago
v18
2024-04-06 12:05pm
Generated on Apr 6, 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.
3439 Total Images
View All Images
Dataset Split
Train Set 87%
3009Images
Valid Set 8%
286Images
Test Set 4%
144Images
Preprocessing
Resize: Fit within 640x640
Augmentations
Outputs per training example: 3
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -20% and +20%
Exposure: Between -10% and +10%
Blur: Up to 1.5px
Noise: Up to 1.92% of pixels