Square Base Blocks Image Dataset
Versions
Tony Dataset - 320x320
v23
Apr 13, 2022
Dataset - YOLOv4 - Top 3 Image Level - 416px
v22
Feb 17, 2022
Dataset - YOLOv4 - Top 3 Image Level - 608px
v21
Feb 16, 2022
Dataset - Top 3 All Level Augmentation
v20
Feb 14, 2022
Dataset - Top 3 BB Level Augmentation
v19
Feb 14, 2022
Dataset - Top 3 Image Level Augmentation
v18
Feb 14, 2022
Sensitivity Analysis - BB - Noise
v17
Feb 10, 2022
Sensitivity Analysis - BB - Exposure
v16
Feb 10, 2022
Sensitivity Analysis - BB - Brightness
v15
Feb 10, 2022
Sensitivity Analysis - BB - Blur
v14
Feb 10, 2022
Sensitivity Analysis - BB - Flip
v13
Feb 10, 2022
Sensitivity Analysis - Hue
v12
Feb 10, 2022
Sensitivity Analysis - Cutout
v11
Feb 10, 2022
Sensitivity Analysis - Noise
v10
Feb 10, 2022
Sensitivity Analysis - Blur
v9
Feb 10, 2022
Sensitivity Analysis - Exposure
v8
Feb 10, 2022
Sensitivity Analysis - Brightness
v7
Feb 10, 2022
Sensitivity Analysis - Crop
v6
Feb 10, 2022
Sensitivity Analysis - Flip
v5
Feb 10, 2022
Sensitivity Analysis - Baseline
v4
Feb 9, 2022
2022-02-08 3:33pm
v3
Feb 8, 2022
2022-02-07 11:12am
v2
Feb 7, 2022
2022-02-03 10:54am
v1
Feb 3, 2022
v11
Sensitivity Analysis - Cutout
Generated on Feb 10, 2022
Popular Download Formats
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.
MT-YOLOv6
MT-YOLOv6 TXT annotations used with meituan/YOLOv6.
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.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
3629 Total Images
View All Images
Dataset Split
Train Set 87%
3171Images
Valid Set 8%
301Images
Test Set 4%
157Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 416x416
Augmentations
Outputs per training example: 3
Cutout: 3 boxes with 10% size each
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