Dataset Versions
Versions
2024-09-06 8:06am
v24
· 3 months ago
2024-09-06 7:56am
v23
· 3 months ago
2024-09-05 2:30pm
v22
· 3 months ago
2024-09-05 7:24am
v21
· 3 months ago
2024-09-05 6:41am
v20
· 3 months ago
2024-09-05 6:37am
v19
· 3 months ago
2024-09-05 6:19am
v18
· 3 months ago
2024-09-05 5:59am
v17
· 3 months ago
2024-09-05 5:40am
v16
· 3 months ago
2024-09-04 9:12am
v15
· 3 months ago
2024-09-04 7:30am
v14
· 3 months ago
2024-09-04 7:27am
v13
· 3 months ago
2024-09-04 7:17am
v12
· 3 months ago
2024-09-04 7:14am
v11
· 3 months ago
2024-09-04 7:13am
v10
· 3 months ago
2024-09-04 7:11am
v9
· 3 months ago
2024-09-04 7:06am
v8
· 3 months ago
2024-09-04 7:03am
v7
· 3 months ago
2024-09-03 9:15am
v6
· 3 months ago
2024-09-03 8:46am
v5
· 3 months ago
2024-09-03 8:00am
v4
· 3 months ago
2024-09-02 1:27pm
v3
· 3 months ago
2024-09-02 1:18pm
v2
· 3 months ago
2024-09-02 1:11pm
v1
· 3 months ago
v4
2024-09-03 8:00am
Generated on Sep 3, 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.
20 Total Images
View All Images
Dataset Split
Train Set 90%
18Images
Valid Set 10%
2Images
Test Set %
0Images
Preprocessing
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 15% of images
Hue: Between -15° and +15°
Brightness: Between -15% and +15%
Blur: Up to 2.5px