Dataset Versions
Versions
2024-10-21 12:52am
v28
· 2 months ago
2024-10-02 3:14pm
v27
· 3 months ago
2024-08-20 1:42pm
v26
· 4 months ago
2024-08-20 1:42pm
v25
· 4 months ago
2024-08-20 1:37pm
v24
· 4 months ago
2024-08-19 2:54pm
v23
· 4 months ago
2024-08-15 7:04pm
v22
· 4 months ago
2024-08-14 11:30am
v21
· 4 months ago
2024-08-13 11:59am
v20
· 4 months ago
2024-08-12 8:07pm
v19
· 4 months ago
2024-08-12 5:07pm
v18
· 4 months ago
2024-08-12 5:03pm
v17
· 4 months ago
2024-08-11 11:08pm
v16
· 4 months ago
2024-08-10 1:32pm
v15
· 5 months ago
2024-08-10 1:28pm
v14
· 5 months ago
2024-08-10 2:41am
v13
· 5 months ago
2024-08-09 6:56pm
v12
· 5 months ago
2024-08-09 6:47pm
v11
· 5 months ago
2024-08-09 6:40pm
v10
· 5 months ago
Broken
v9
· 5 months ago
2024-08-09 3:54pm
v8
· 5 months ago
2024-08-08 7:53pm
v7
· 5 months ago
2024-08-07 4:10pm
v6
· 5 months ago
2024-08-06 7:20pm
v5
· 5 months ago
2024-08-06 3:58pm
v4
· 5 months ago
2024-08-06 4:11am
v3
· 5 months ago
2024-08-06 2:21am
v2
· 5 months ago
2024-08-06 2:17am
v1
· 5 months ago
v10
2024-08-09 6:40pm
Generated on Aug 9, 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.
21 Total Images
View All Images
Dataset Split
Train Set 100%
21Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Dynamic Crop: Class: target_selected
Resize: Stretch to 1280x720
Augmentations
Outputs per training example: 3
Noise: Up to 1.33% of pixels