Dataset Versions
Versions
2023-06-05 9:28am
v80
· a year ago
2023-06-04 11:42pm
v78
· a year ago
FINAL
v77
· 2 years ago
extractDataset
v76
· 2 years ago
preFinal640
v73
· 2 years ago
preFinal640AUG
v72
· 2 years ago
preFinalClear
v71
· 2 years ago
final1280
v69
· 2 years ago
final1280AUG
v68
· 2 years ago
final640AUG
v67
· 2 years ago
final640
v66
· 2 years ago
finalClear
v65
· 2 years ago
TestCreated
v63
· 2 years ago
RenamedClasses
v62
· 2 years ago
2023-04-04 6:15pm
v59
· 2 years ago
2023-04-04 6:10pm
v58
· 2 years ago
2023-04-04 4:34pm
v56
· 2 years ago
TEST-BACKGROUND
v55
· 2 years ago
2023-04-03 1:25pm
v54
· 2 years ago
YELLOWGREENv1.0.augmented
v53
· 2 years ago
YELLOWGREENv1.0
v52
· 2 years ago
AllClassesv1
v51
· 2 years ago
AllClassesResize640v1
v50
· 2 years ago
RFSupport-Test3
v27
· 2 years ago
RFSupport-Test2
v26
· 2 years ago
RFSupport-Test1
v25
· 2 years ago
-u2609 -2aef ONLY
v8
· 2 years ago
balanced dataset
v7
· 2 years ago
-u2609 ONLY - remapped
v6
· 2 years ago
2022-11-20 10:30pm
v5
· 2 years ago
2022-11-09 12:41am
v3
· 2 years ago
v53
YELLOWGREENv1.0.augmented
Generated on Apr 2, 2023
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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721 Total Images
View All Images
Dataset Split
Train Set 95%
686Images
Valid Set 3%
20Images
Test Set 2%
15Images
Preprocessing
Resize: Stretch to 640x640
Modify Classes: 0 remapped, 995 dropped
Augmentations
Outputs per training example: 7
Grayscale: Apply to 100% of images
Hue: Between -20° and +20°
Saturation: Between -70% and +70%
Brightness: Between -20% and +20%
Exposure: Between -12% and +12%
Blur: Up to 0.5px
Noise: Up to 1% of pixels