CAPTCHA images Dataset
Versions
2022-07-15 7:07pm
v41
· 2 years ago
1003-rotate-cutout-shear-noise
v40
· 2 years ago
2022-05-16 7:53pm
v39
· 2 years ago
2022-05-16 1:37pm
v38
· 2 years ago
1003-rotate-cutout-shear-noise
v37
· 2 years ago
2022-05-16 9:40am
v36
· 2 years ago
2022-04-18 5:29pm
v35
· 2 years ago
1003-rotate-cutout-shear-noise
v33
· 2 years ago
2022-04-12 3:59pm
v32
· 2 years ago
859-crop-rotate-noise-cutout-steven
v24
· 2 years ago
343
v22
· 2 years ago
601-underrepresented
v21
· 2 years ago
843-rotate-shear-noise-cutout
v20
· 2 years ago
2022-04-04 11:10am
v19
· 2 years ago
859-crop-rotate-shear-saturation-alex
v18
· 2 years ago
859-crop-rotatate-noise-steven-
v17
· 3 years ago
idk
v16
· 3 years ago
No augmentation
v15
· 3 years ago
859-rotate-shear
v14
· 3 years ago
859-rotate-shear-stretch
v13
· 3 years ago
786-rotate-shear-stretch
v12
· 3 years ago
786-rotate-shear
v11
· 3 years ago
369-rotate-shear
v10
· 3 years ago
Rotate and brightness
v9
· 3 years ago
rotate- brightness and noise
v8
· 3 years ago
2022-03-15 12:04pm
v7
· 3 years ago
train- test and val
v6
· 3 years ago
2022-03-13 7:31pm
v5
· 3 years ago
76
v4
· 3 years ago
2022-02-21 1:47pm
v3
· 3 years ago
v32
2022-04-12 3:59pm
Generated on Apr 12, 2022
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.
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859 Total Images
View All Images
Dataset Split
Train Set 90%
774Images
Valid Set 8%
70Images
Test Set 2%
15Images
Preprocessing
Resize: Fit (black edges) in 500x200
Augmentations
Outputs per training example: 3
Rotation: Between -8° and +8°
Cutout: 13 boxes with 6% size each
Bounding Box: Shear: ±8° Horizontal, ±8° Vertical
Bounding Box: Noise: Up to 8% of pixels