safety cam1 Image Dataset
Versions
2024-06-04 9:43am
v28
Jun 4, 2024
2024-06-04 9:26am
v27
Jun 4, 2024
2024-06-03 12:30pm
v26
Jun 3, 2024
2024-06-03 10:10am
v25
Jun 3, 2024
2024-05-28 9:41am
v24
May 28, 2024
2024-05-27 11:51am
v23
May 27, 2024
2024-05-20 9:34am
v22
May 20, 2024
2024-04-09 10:56am
v21
Apr 9, 2024
2024-04-03 8:43am
v20
Apr 3, 2024
2024-04-03 8:42am
v19
Apr 3, 2024
2024-04-03 8:41am
v18
Apr 3, 2024
2024-03-20 2:40pm
v17
Mar 20, 2024
2024-03-20 11:58am
v16
Mar 20, 2024
2024-03-13 9:30am
v15
Mar 13, 2024
2024-02-08 12:08pm
v14
Feb 8, 2024
2024-02-06 9:54am
v13
Feb 6, 2024
2024-02-01 12:36pm
v12
Feb 1, 2024
2024-01-11 12:15pm
v11
Jan 11, 2024
2024-01-08 9:24am
v10
Jan 8, 2024
2024-01-05 4:36pm
v9
Jan 5, 2024
2024-01-05 4:28pm
v8
Jan 5, 2024
2024-01-05 1:43pm
v7
Jan 5, 2024
2024-01-05 1:25pm
v6
Jan 5, 2024
2024-01-05 12:25pm
v5
Jan 5, 2024
2024-01-05 12:05pm
v4
Jan 5, 2024
2024-01-05 11:47am
v3
Jan 5, 2024
2024-01-04 3:05pm
v2
Jan 4, 2024
2024-01-04 2:32pm
v1
Jan 4, 2024
v9
2024-01-05 4:36pm
Generated on Jan 5, 2024
Popular Download Formats
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.
3361 Total Images
View All Images
Dataset Split
Train Set 86%
2885Images
Valid Set 6%
190Images
Test Set 9%
286Images
Preprocessing
No preprocessing steps were applied.
Augmentations
Outputs per training example: 3
Grayscale: Apply to 15% of images
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