Dataset Versions
Versions
2024-10-24 11:33pm
v38
· a month ago
2024-10-24 11:18pm
v37
· a month ago
2024-10-24 4:18pm
v36
· a month ago
2024-10-24 2:44am
v35
· a month ago
2024-10-24 2:35am
v34
· a month ago
2024-10-24 1:50am
v33
· a month ago
2024-10-24 1:36am
v32
· a month ago
2024-10-24 1:16am
v31
· a month ago
2024-10-24 12:53am
v30
· a month ago
2024-10-24 12:50am
v29
· a month ago
2024-10-23 9:09pm
v28
· a month ago
2024-10-23 8:44pm
v27
· a month ago
2024-10-23 4:42pm
v26
· a month ago
2024-10-23 1:17pm
v25
· a month ago
2024-10-22 3:49pm
v23
· a month ago
2024-10-22 3:16pm
v22
· a month ago
2024-10-20 12:08am
v21
· a month ago
2024-10-19 10:11pm
v10
· a month ago
2024-10-19 8:31pm
v9
· a month ago
2024-10-19 3:00pm
v8
· a month ago
2024-10-15 3:02am
v7
· a month ago
2024-10-14 6:59pm
v6
· a month ago
2024-10-14 6:49pm
v5
· a month ago
2024-10-14 12:38am
v4
· a month ago
2024-10-14 12:36am
v3
· a month ago
2024-10-14 12:31am
v2
· a month ago
Bad_Example
v1
· a month ago
v38
2024-10-24 11:33pm
Generated on Oct 24, 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.
122 Total Images
View All ImagesDataset Split
Train Set 91%
111Images
Valid Set 9%
11Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Fit within 1216x240
Auto-Adjust Contrast: Using Contrast Stretching
Modify Classes: 2 remapped, 4 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Saturation: Between -10% and +10%
Brightness: Between -10% and +10%