Dataset Versions
Versions
Random Train YOLO 2024-06-20 6-45pm Saturation - brightness
v15
· 5 months ago
Train With V2 Roboflow 2024-06-20 6-43pm Saturation - brightness
v14
· 5 months ago
V10 2024-06-20 6-41pm saturation - brightness x5
v13
· 5 months ago
V9 2024-06-20 6-39pm saturation - brightness x5
v12
· 5 months ago
V8 2024-06-20 6-37pm saturation - brightness x3 YOLO
v11
· 5 months ago
V8 2024-06-20 6-35pm saturation - brightness x3
v10
· 5 months ago
V7 2024-06-20 7-32am Hue - Brightnessx2
v8
· 5 months ago
V6 2024-06-16 11-00am -Hue - Brightness x2-
v7
· 5 months ago
V5 2024-06-16 10-57am -Hue - Brightness x3-
v6
· 5 months ago
V4 2024-06-16 10-55am -Hue - Brightness x5-
v5
· 5 months ago
V3 2024-06-16 10-45am -Hue x5-
v4
· 5 months ago
V2 2024-06-16 10-11am -With Preprocess-
v2
· 5 months ago
V1 2024-06-16 10-09am -Without Preprocess-
v1
· 5 months ago
v12
V9 2024-06-20 6-39pm saturation - brightness x5
Generated on Jun 20, 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.
8187 Total Images
View All Images
Dataset Split
Train Set 88%
7224Images
Valid Set 7%
602Images
Test Set 4%
361Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 5
Saturation: Between -34% and +34%
Brightness: Between -25% and +25%