Dataset Versions
Versions
2023-05-24 6:55pm
v33
· a year ago
2022-08-27 8:22pm
v32
· 2 years ago
gun dataset may_05_22_2nd
v31
· 3 years ago
gun dataset_may_05_22
v30
· 3 years ago
gun dataset_apr_29_22_2nd
v29
· 3 years ago
Rachel test 2022-04-29 11:34am
v28
· 3 years ago
gun dataset_apr_30_22
v27
· 3 years ago
gun dataset_apr_29_22
v26
· 3 years ago
gun dataset_apr_28_22
v25
· 3 years ago
gun dataset_apr_22_22
v24
· 3 years ago
gun dataset_apr_17_22
v23
· 3 years ago
gun dataset_apr_15_22_edit
v21
· 3 years ago
gun dataset_apr_15_22-4-
v20
· 3 years ago
gun dataset_apr_15_22 -3-
v19
· 3 years ago
gun dataset_apr_15_22-2-
v18
· 3 years ago
gun dataset_apr_15_22
v17
· 3 years ago
gun dataset_apr_12_22
v16
· 3 years ago
gun dataset_apr_08_22 -2-
v15
· 3 years ago
gun dataset_apr_08_22
v14
· 3 years ago
gun dataset_apr_07_22_2
v13
· 3 years ago
gun dataset_apr_07_22
v10
· 3 years ago
gun dataset_mar_25_22
v9
· 3 years ago
gun dataset_mar_16_22
v8
· 3 years ago
gun dataset_mar_03_22
v7
· 3 years ago
gun dataset_feb_24_22
v6
· 3 years ago
gun dataset_feb_22_22
v5
· 3 years ago
gun dataset_feb_18_22
v4
· 3 years ago
gun dataset_feb_17_22 -2-
v3
· 3 years ago
gun dataset_feb_17_22
v2
· 3 years ago
gun dataset_feb_16_22
v1
· 3 years ago
v2
gun dataset_feb_17_22
Generated on Feb 18, 2022
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YOLOv11
TXT annotations and YAML config used with YOLOv11.
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TXT annotations and YAML config used with YOLOv9.
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TXT annotations and YAML config used with YOLOv8.
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TXT annotations and YAML config used with YOLOv5.
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TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
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Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
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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.
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646 Total Images
View All Images
Dataset Split
Train Set 88%
570Images
Valid Set 8%
50Images
Test Set 4%
26Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 416x416
Augmentations
Outputs per training example: 3
Flip: Horizontal
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Blur: Up to 10px
Noise: Up to 5% of pixels
Cutout: 3 boxes with 10% size each