3D Shapes Image Dataset
Versions
2023-06-26 11:11am
v33
Jun 26, 2023
2023-06-16 1:51pm
v32
Jun 16, 2023
2023-06-10 3:11pm
v31
Jun 10, 2023
2023-06-10 2:09pm
v30
Jun 10, 2023
2023-06-10 1:40pm
v28
Jun 10, 2023
2023-06-09 1:48pm
v27
Jun 9, 2023
2023-05-22 7:13am
v26
May 21, 2023
2023-05-20 7:49pm
v25
May 20, 2023
2023-05-20 7:07pm
v24
May 20, 2023
2023-05-20 6:34pm
v23
May 20, 2023
2023-05-20 5:00pm
v22
May 20, 2023
2023-05-20 8:39am
v21
May 20, 2023
2023-05-19 3:47pm
v20
May 19, 2023
2023-05-18 2:52pm
v19
May 18, 2023
2023-05-08 8:59am
v18
May 8, 2023
2023-05-08 8:26am
v17
May 8, 2023
2023-05-08 7:51am
v16
May 7, 2023
2023-05-07 8:45pm
v15
May 7, 2023
2023-05-07 8:10pm
v14
May 7, 2023
2023-05-07 7:34pm
v13
May 7, 2023
2023-05-07 7:14pm
v12
May 7, 2023
2023-05-07 6:09pm
v11
May 7, 2023
2023-05-05 1:49pm
v10
May 5, 2023
2023-05-05 1:16pm
v9
May 5, 2023
2023-05-05 1:15pm
v8
May 5, 2023
2023-03-07 12:19pm
v7
Mar 7, 2023
2023-03-07 12:18pm
v6
Mar 7, 2023
2023-03-07 12:17pm
v5
Mar 7, 2023
2023-03-07 12:11pm
v4
Mar 7, 2023
2023-03-07 12:02pm
v1
Mar 7, 2023
v33
2023-06-26 11:11am
Generated on Jun 26, 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.
480 Total Images
View All ImagesDataset Split
Train Set 88%
420Images
Valid Set 8%
40Images
Test Set 4%
20Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal
Exposure: Between -25% and +25%
Noise: Up to 5% of pixels
Mosaic: Applied
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