Dataset Versions
Versions
2023-05-02 4:07pm
v28
· 2 years ago
2023-03-17 3:06pm
v27
· 2 years ago
can_color_320
v26
· 2 years ago
2023-03-16 5:05pm
v25
· 2 years ago
2023-03-16 8:37am
v24
· 2 years ago
2023-03-15 3:05pm
v23
· 2 years ago
canlibv023
v22
· 2 years ago
2023-03-14 12:22pm
v21
· 2 years ago
2023-02-22 5:00pm
v20
· 2 years ago
2023-02-22 4:56pm
v19
· 2 years ago
-cans in color
v18
· 2 years ago
just cans
v17
· 2 years ago
2023-02-21 4:03pm
v16
· 2 years ago
2023-02-07 3:25pm
v15
· 2 years ago
2023-02-06 2:38pm
v14
· 2 years ago
2023-02-02 4:26pm
v13
· 2 years ago
2023-02-02 3:20pm
v12
· 2 years ago
2023-02-02 9:49am
v11
· 2 years ago
2023-01-31 3:16pm
v10
· 2 years ago
2023-01-31 3:03pm
v9
· 2 years ago
2023-01-30 10:18am
v8
· 2 years ago
2023-01-30 10:17am
v7
· 2 years ago
2023-01-30 10:16am
v6
· 2 years ago
2023-01-30 10:12am
v5
· 2 years ago
2023-01-19 1:27pm
v4
· 2 years ago
2023-01-17 3:59pm
v3
· 2 years ago
2023-01-17 3:40pm
v2
· 2 years ago
2023-01-17 3:38pm
v1
· 2 years ago
v28
2023-05-02 4:07pm
Generated on May 2, 2023
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.
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303 Total Images
View All Images
Dataset Split
Train Set 90%
273Images
Valid Set 5%
16Images
Test Set 5%
14Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (black edges) in 320x320
Auto-Adjust Contrast: Using Adaptive Equalization
Augmentations
Outputs per training example: 3
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Blur: Up to 1px
Noise: Up to 5% of pixels
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Exposure: Between -15% and +15%