only_kaale_laale Image Dataset
Versions
2024-06-26 5:01am
v35
· 4 days ago
2024-06-26 4:55am
v34
· 4 days ago
2024-06-26 4:36am
v33
· 4 days ago
2024-06-26 4:36am
v32
· 4 days ago
2024-06-23 2:34pm
v28
· 6 days ago
2024-06-23 2:33pm
v27
· 6 days ago
2024-06-23 2:29pm
v25
· 6 days ago
2024-06-23 2:24pm
v22
· 6 days ago
2024-06-23 2:22pm
v21
· 6 days ago
2024-06-23 1:12pm
v20
· 6 days ago
2024-06-23 1:12pm
v19
· 6 days ago
2024-06-23 1:11pm
v18
· 6 days ago
2024-06-23 1:07pm
v17
· 6 days ago
2024-06-23 11:32am
v16
· 6 days ago
2024-06-23 11:21am
v15
· 6 days ago
2024-06-22 5:57am
v14
· 8 days ago
2024-06-21 5:04am
v13
· 9 days ago
2024-06-16 9:43am
v12
· 14 days ago
2024-06-16 5:48am
v11
· 14 days ago
2024-06-15 6:57pm
v10
· 14 days ago
2024-06-13 11:16am
v9
· 16 days ago
2024-06-13 11:01am
v8
· 16 days ago
2024-06-13 10:47am
v7
· 16 days ago
2024-06-11 8:08pm
v5
· 18 days ago
2024-06-11 8:01pm
v4
· 18 days ago
2024-06-03 12:22pm
v3
· a month ago
2024-06-03 9:53am
v2
· a month ago
2024-06-03 12:54am
v1
· a month ago
v2
2024-06-03 9:53am
Generated on Jun 3, 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.
954 Total Images
View All Images
Dataset Split
Train Set 82%
786Images
Valid Set 10%
97Images
Test Set 7%
71Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x480
Augmentations
Outputs per training example: 3
Blur: Up to 1px
Noise: Up to 0.46% of pixels
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