Dataset Versions
Versions
18.Cleaning Tree 2024-12-10 2-14pm
v30
· 15 days ago
17.Export Dataset 16 - 2024-12-10 9-29am
v29
· 15 days ago
16.Cleaning Building 2024-12-09 4-34pm
v27
· 16 days ago
15.Refreshing 2024-12-09 10-03am
v26
· 16 days ago
14.Export Dataset 13 - 2024-12-07 12-10pm
v25
· 18 days ago
13.Clearing 2024-12-06 8-15pm
v24
· 19 days ago
12.Remove Big Images 2024-12-03 10-35pm
v23
· 22 days ago
11.Additional 2024-12-03 4-11pm
v22
· 22 days ago
10.Additional Label 2024-12-03 1-04pm
v21
· 22 days ago
9.Re-Label Building and Tree 2024-12-01 5-51pm
v20
· 24 days ago
8.Add Building and Tree 2024-11-30 5-05pm
v18
· 25 days ago
7.Merg Mobile Crane and Crane 2024-11-30 9-19am
v16
· 25 days ago
6.Add Yolo Fong 2024-11-30 6-31am
v15
· 25 days ago
5.Add Mobile Crane 2024-11-29 4-42pm
v13
· a month ago
2021-09-14 2-44pm For Export-Non-Augmentations
v11
· 3 years ago
4.Add Mark Null - Resize Imgs 2021-09-09 3:01pm
v10
· 3 years ago
3.Clean confusing backhoe 2021-09-08 10:57am
v9
· 3 years ago
2.Scale x3 imgs 2021-09-07 6:16pm
v6
· 3 years ago
1.Add RegionX 2021-09-07 11:57am
v4
· 3 years ago
2021-09-05 2:13pm Not Resize
v2
· 3 years ago
v18
8.Add Building and Tree 2024-11-30 5-05pm
Generated on Nov 30, 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.
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5810 Total Images
View All Images
Dataset Split
Train Set 85%
4926Images
Valid Set 9%
506Images
Test Set 7%
378Images
Preprocessing
Resize: Stretch to 640x640
Filter Null: Require at least 50% of images to contain annotations.
Augmentations
Outputs per training example: 3
Rotation: Between -8° and +8°
Saturation: Between -25% and +25%
Exposure: Between -7% and +7%
Blur: Up to 1.5px
Noise: Up to 1.13% of pixels