Stall Detection Image Dataset
Versions
2023-10-13 6:50am
v32
Oct 13, 2023
2023-10-12 9:41pm
v31
Oct 13, 2023
2023-10-12 9:19pm
v30
Oct 13, 2023
2023-10-12 9:12pm
v29
Oct 13, 2023
2023-10-10 3:10pm
v28
Oct 10, 2023
2023-10-09 9:04pm
v27
Oct 10, 2023
2023-10-09 8:45pm
v26
Oct 10, 2023
2023-10-09 11:31am
v25
Oct 9, 2023
2023-10-09 6:16am
v24
Oct 9, 2023
2023-10-08 8:58pm
v23
Oct 9, 2023
2023-10-08 8:06pm
v22
Oct 9, 2023
2023-10-08 7:30pm
v21
Oct 9, 2023
2023-10-07 4:17pm
v20
Oct 7, 2023
2023-10-07 10:00am
v19
Oct 7, 2023
2023-10-07 9:53am
v18
Oct 7, 2023
2023-10-07 9:37am
v17
Oct 7, 2023
2023-10-07 8:05am
v16
Oct 7, 2023
2023-10-07 7:54am
v15
Oct 7, 2023
2023-10-07 7:45am
v14
Oct 7, 2023
2023-10-07 7:41am
v13
Oct 7, 2023
2023-10-07 7:29am
v12
Oct 7, 2023
2023-10-07 7:19am
v11
Oct 7, 2023
2023-10-07 7:06am
v10
Oct 7, 2023
2023-10-06 11:27pm
v9
Oct 7, 2023
2023-10-06 11:21pm
v8
Oct 7, 2023
2023-10-06 10:12pm
v7
Oct 7, 2023
2023-10-06 7:43pm
v6
Oct 7, 2023
2023-10-06 7:35pm
v5
Oct 7, 2023
2023-10-06 7:24pm
v4
Oct 7, 2023
2023-10-06 7:14pm
v3
Oct 7, 2023
2023-10-06 7:05pm
v2
Oct 7, 2023
v14
2023-10-07 7:45am
Generated on Oct 7, 2023
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.
540 Total Images
View All Images
Dataset Split
Train Set 83%
446Images
Valid Set 12%
63Images
Test Set 6%
31Images
Preprocessing
Auto-Orient: Applied
Augmentations
Outputs per training example: 2
90° Rotate: Counter-Clockwise
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