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TeaLabels
Object Detection
Overview
Images
392
Dataset
25
Model
2
API Docs
Analytics
Dataset Versions
Try Pre-Trained Model
Versions
2024-09-09 2:15pm
v27
·
6 months ago
2024-09-09 2:14pm
v26
·
6 months ago
2024-09-09 11:30am
v25
·
6 months ago
2024-09-09 11:29am
v24
·
6 months ago
2024-08-01 4:31pm
v23
·
7 months ago
2024-08-01 4:31pm
v22
·
7 months ago
2024-08-01 4:30pm
v21
·
7 months ago
2024-08-01 4:09pm
v20
·
7 months ago
2024-08-01 4:08pm
v19
·
7 months ago
2024-08-01 4:07pm
v18
·
7 months ago
2024-08-01 4:07pm
v17
·
7 months ago
2024-08-01 4:06pm
v16
·
7 months ago
2024-07-22 5:35pm
v15
·
7 months ago
2024-07-22 5:35pm
v14
·
7 months ago
2024-07-22 5:34pm
v13
·
7 months ago
2024-07-20 4:33pm
v11
·
7 months ago
2024-07-20 1:26pm
v10
·
7 months ago
2024-07-20 9:39am
v9
·
7 months ago
2024-07-20 8:54am
v8
·
7 months ago
2024-07-20 8:13am
v7
·
7 months ago
2024-07-17 5:41pm
v6
·
7 months ago
2024-07-10 9:09pm
v5
·
7 months ago
2024-07-10 9:07pm
v4
·
7 months ago
2024-07-10 8:52pm
v3
·
7 months ago
2024-07-10 8:21pm
v1
·
7 months ago
v1
2024-07-10 8:21pm
Generated on Jul 10, 2024
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Dataset
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.
Other Formats
Choose another format.
60
Total Images
View All Images
Dataset Split
Train Set
100%
60
Images
Valid Set
%
0
Images
Test Set
%
0
Images
Preprocessing
Auto-Orient:
Applied
Resize:
Stretch to 640x640
Augmentations
Outputs per training example:
3
Rotation:
Between -15° and +15°
Hue:
Between -12° and +12°
Saturation:
Between -33% and +33%
Exposure:
Between -15% and +15%
Blur:
Up to 1.4px
Noise:
Up to 2.2% of pixels
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