bridge Image Dataset
Versions
2022-08-30 8:35pm
v41
Aug 30, 2022
2022-08-30 7:33pm
v40
Aug 30, 2022
Successful Augmentations
v39
Aug 30, 2022
Re-Mapping Successful
v38
Aug 30, 2022
No Pre-Procs- Successful Generation
v37
Aug 30, 2022
2022-08-30 11:02am
v36
Aug 30, 2022
2022-08-30 12:18pm
v35
Aug 30, 2022
2022-08-25 8:44pm
v34
Aug 25, 2022
2022-08-25 6:02pm
v33
Aug 25, 2022
2022-08-23 6:28pm
v32
Aug 23, 2022
2022-08-23 1:39pm
v31
Aug 23, 2022
2022-08-23 12:47pm
v30
Aug 23, 2022
2022-08-23 12:39pm
v29
Aug 23, 2022
2022-08-23 10:07am
v28
Aug 23, 2022
2022-08-20 12:18am
v26
Aug 20, 2022
2022-08-20 12:18am
v25
Aug 20, 2022
2022-08-19 6:57pm
v24
Aug 19, 2022
2022-08-19 8:09am
v23
Aug 19, 2022
2022-08-19 11:32am
v22
Aug 19, 2022
2022-08-19 1:42am
v21
Aug 19, 2022
2022-08-19 1:05am
v20
Aug 19, 2022
2022-08-18 11:56pm
v18
Aug 19, 2022
2022-08-18 11:02pm
v17
Aug 19, 2022
2022-08-18 10:05pm
v16
Aug 19, 2022
2022-08-18 9:25pm
v14
Aug 19, 2022
2022-08-14 11:59am
v3
Aug 14, 2022
2022-07-19 10:18am
v1
Jul 19, 2022
v3
2022-08-14 11:59am
Generated on Aug 14, 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.
4179 Total Images
View All ImagesDataset Split
Train Set 88%
3660Images
Valid Set 8%
322Images
Test Set 5%
197Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 3
Flip: Horizontal
Hue: Between -25° and +25°
Saturation: Between -25% and +25%
Brightness: Between -20% and +20%
Exposure: Between -6% and +6%
Blur: Up to 1px
Noise: Up to 5% of pixels
Mosaic: Applied
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