test3-LBC Image Dataset
Versions
B30N3B2C9 320 frames64 17k 7class
v60
Feb 21, 2023
B30N3B2C9 640 frames63 16k 7class
v59
Feb 10, 2023
B30N3B2C9 640 false5 15k 7class
v58
Feb 9, 2023
B60N3BC9 1024 false5 15k 7cls
v52
Jan 17, 2023
B60N3BC9 false5 15k 7cls 2022-07-05 8:53pm
v49
Jul 5, 2022
B60N3BC9 false5 15k 2cls 2022-07-04 12:15pm
v48
Jul 4, 2022
BNBC9 false5 15k 2cls 2022-07-01 9:41pm
v46
Jul 1, 2022
FBBNC9 false5 2cls 15k 2022-07-01 2:17pm
v45
Jul 1, 2022
BNBFC9 false5 2cls 15k 2022-06-27 9:02pm
v43
Jun 27, 2022
BNBFEC9 false5 v57 2cls 15k 2022-06-24 8:57pm
v42
Jun 24, 2022
no aug false5 v57 2cls 5k images 2022-06-19 10:26pm
v40
Jun 19, 2022
BNBC7 640x640 false5 v57 2 classes 15k 2022-06-19 10:50am
v38
Jun 19, 2022
BNBCF 1024x1024 false5 v57 2 classes 2022-06-18 10:57am
v36
Jun 18, 2022
BNBC 320x320 false5 v57 2 classes 2022-06-17 5:55pm
v34
Jun 17, 2022
BNBC false5 v57 2 classes 15k 2022-06-17 11:35am
v33
Jun 17, 2022
BNBCF false5 v57 2 classes 15k 2022-06-16 6:17pm
v32
Jun 16, 2022
BNBC false4 v57 2 classes 15k 2022-06-15 1:59pm
v31
Jun 15, 2022
BNBC false3 v57 2 classes 10k
v30
Jun 13, 2022
BNBC false3 v57 2 classes 2022-06-13 1:51pm
v29
Jun 13, 2022
BNBC false-3 v57 7 classes 2022-06-12 7:06am
v28
Jun 12, 2022
BNBC v57 3 classes 15k 2022-06-11 11:52am
v27
Jun 11, 2022
BNBC v57 640 2 classes 15k 2022-06-10 10:08pm
v26
Jun 10, 2022
BNBC false 2 v55 640 2 classes 15k 2022-06-04 4:29pm
v25
Jun 4, 2022
BNBC false detections 2 v55 640x640 3classes 15k 2022-06-04 6:55am
v24
Jun 4, 2022
false detections 2 v55 640x640 3classes 15k
v23
May 30, 2022
v55 false detections 640x640 3classes 15kImages 2022-05-26 10:14am
v22
May 26, 2022
BNB v55-false detections 1 class 2022-05-25 1:25pm
v20
May 25, 2022
BNB Augmented v55 3classes 9kImages Empty Images 15- 2022-05-23 9:32pm
v18
May 23, 2022
All Labelled Data till v55 2022-05-21 10:09am
v17
May 21, 2022
BNB Augmented v55 3 classes 15kImages 2022-05-20 10:40pm
v16
May 20, 2022
B65N2B5 Augmented v54 7 classes 9kImages 2022-05-20 4:15pm
v15
May 20, 2022
B65N2B3 Augmented v54 3 classes 9kImages 2022-05-18 8:22pm
v14
May 18, 2022
BNB Augmented v54 3 classes 9kImages 2022-05-16 4:22pm
v13
May 16, 2022
BNB Augmented v54 2 classes 9kImages 2022-05-15 10:07pm
v12
May 15, 2022
BrightnessNoiseBlur Augmented v52 2 classes 8kImages 2022-05-15 4:10pm
v11
May 15, 2022
BrightnessNoiseBlurCutout Augmented v52 3 classes 8kImages 2022-05-14 8:32pm
v10
May 14, 2022
BrightnessNoiseBlurCutout Augmented video52 3 classes 12kImages 2022-05-13 9:09am
v9
May 13, 2022
BrightnessNoiseBlur Augmented video52 7 classes 8kImages 2022-05-12 11:04pm
v8
May 12, 2022
BrightnessNoiseBlur Augmented video52 3 classes 12kImages 2022-05-12 9:55pm
v7
May 12, 2022
BrightnessNoiseBlur Augmented video52 3 classes 8kImages 2022-05-12 4:30pm
v6
May 12, 2022
Brightness Augmented to 65- till video 52 3 classes 2022-05-12 3:50pm
v5
May 12, 2022
Brightness Augmented Dataset till video52 3 classes 2022-05-08 10:08pm
v4
May 8, 2022
XML issue fixed Dataset till video52 7 classes2022-05-08 11:13am
v3
May 8, 2022
XML issue fixed Dataset till video52 3 classes 2022-05-07 10:34pm
v2
May 7, 2022
Dataset till video44 xml issues fixed 2022-05-06 10:30pm
v1
May 6, 2022
v60
B30N3B2C9 320 frames64 17k 7class
Generated on Feb 21, 2023
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.
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17477 Total Images
View All Images
Dataset Split
Train Set 95%
16680Images
Valid Set 4%
621Images
Test Set 1%
176Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (black edges) in 320x320
Filter Null: Require at least 90% of images to contain annotations.
Augmentations
Outputs per training example: 3
Brightness: Between -30% and +30%
Blur: Up to 2px
Noise: Up to 3% of pixels
Cutout: 9 boxes with 10% size each
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