X-00Ver0.001 Dataset
Versions
2024-08-16 12:28pm
v27
· a month ago
2024-08-13 2:55pm
v26
· a month ago
2024-08-04 2:30pm
v25
· 2 months ago
2024-07-26 9:26am
v24
· 2 months ago
2024-07-14 4:08pm
v23
· 2 months ago
2024-06-29 6:48am
v22
· 3 months ago
2024-06-27 4:38am
v21
· 3 months ago
2024-06-25 8:02pm
v20
· 3 months ago
2024-06-25 4:23pm
v19
· 3 months ago
2024-06-21 8:03am
v18
· 3 months ago
2024-06-05 9:53am
v17
· 4 months ago
2024-06-04 2:47pm
v16
· 4 months ago
2024-05-31 8:09am
v15
· 4 months ago
2024-05-12 4:02am
v14
· 4 months ago
2024-04-30 7:22am
v13
· 5 months ago
2024-04-30 7:07am
v12
· 5 months ago
Last_verstion
v11
· 5 months ago
2024-04-27 6:47am
v10
· 5 months ago
2024-04-26 5:41am
v9
· 5 months ago
930x
v8
· 5 months ago
2024-03-27 3:13am
v7
· 6 months ago
2024-03-26 9:49am
v6
· 6 months ago
2024-03-26 2:48am
v5
· 6 months ago
2024-03-26 2:36am
v4
· 6 months ago
2024-03-25 7:21am
v3
· 6 months ago
2024-03-25 3:27am
v2
· 6 months ago
2024-03-25 3:22am
v1
· 6 months ago
v4
2024-03-26 2:36am
Generated on Mar 26, 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.
384 Total Images
View All Images
Dataset Split
Train Set 88%
336Images
Valid Set 8%
31Images
Test Set 4%
17Images
Preprocessing
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 3
Rotation: Between -15° and +15°
Grayscale: Apply to 15% of images
Hue: Between -15° and +15°
Noise: Up to 0.1% of pixels