Dataset Versions
Versions
2022-09-29 9:53pm
v35
· 2 years ago
bank and coin 34
v34
· 2 years ago
bank and coin 33
v33
· 2 years ago
bank and coin 32
v32
· 2 years ago
bank and coin 31
v31
· 2 years ago
bank and coin 30
v30
· 2 years ago
bank and coin 29
v29
· 2 years ago
bank and coin 28
v28
· 2 years ago
bank and coin 27
v27
· 2 years ago
bank and coin 26
v26
· 2 years ago
bank and coin 25
v25
· 2 years ago
bank and coin 24
v24
· 2 years ago
bank and coin 23
v23
· 2 years ago
bank and coin 22
v22
· 2 years ago
bank and coin 21
v21
· 2 years ago
bank and coin 20
v20
· 2 years ago
bank and coin 19
v19
· 2 years ago
bank and coin 18
v18
· 2 years ago
bank and coin 17
v17
· 2 years ago
bank and coin 16
v16
· 2 years ago
bank and coin 15
v15
· 2 years ago
bank and coin 14
v14
· 2 years ago
bank and coin 13
v13
· 2 years ago
bank and coin 12
v12
· 2 years ago
bank and coin 11
v11
· 2 years ago
bank and coin 10
v10
· 2 years ago
bank and coin 9
v9
· 2 years ago
bank and coin 8
v8
· 2 years ago
bank and coin 7
v7
· 2 years ago
bank and coin 6
v6
· 2 years ago
bank and coin 5
v5
· 2 years ago
bank and coin 4
v4
· 2 years ago
bank and coin 3
v3
· 2 years ago
bank and coin 2
v2
· 2 years ago
bank and coin 1
v1
· 2 years ago
v31
bank and coin 31
Generated on Sep 25, 2022
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.
450 Total Images
View All Images
Dataset Split
Train Set 100%
450Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 800x416
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Noise: Up to 5% of pixels