cars-brand Dataset
Versions
2023-07-04 4:32pm
v32
· a year ago
2023-07-04 2:30pm
v31
· a year ago
2023-07-04 1:55pm
v30
· a year ago
2023-07-04 11:46am
v29
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2023-07-04 11:30am
v28
· a year ago
2023-07-04 8:25am
v27
· a year ago
2023-07-04 8:03am
v26
· a year ago
2023-07-03 4:39pm
v25
· a year ago
2023-06-23 10:25pm
v24
· a year ago
2023-06-23 8:08pm
v23
· a year ago
2023-06-23 5:21pm
v22
· a year ago
2023-06-21 3:24pm
v21
· a year ago
2023-06-08 3:14pm
v4
· a year ago
2023-06-08 2:47pm
v3
· a year ago
v32
2023-07-04 4:32pm
Generated on Jul 4, 2023
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YOLOv9
TXT annotations and YAML config used with YOLOv9.
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TXT annotations and YAML config used with YOLOv5.
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TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
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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.
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4391 Total Images
View All Images
Dataset Split
Train Set 90%
3942Images
Valid Set 10%
449Images
Test Set %
0Images
Preprocessing
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Histogram Equalization
Modify Classes: 17 remapped, 19 dropped
Filter Null: Require at least 75% of images to contain annotations.
Augmentations
Outputs per training example: 2
Grayscale: Apply to 20% of images
Hue: Between -91° and +91°
Saturation: Between -17% and +17%
Brightness: Between -15% and +15%
Blur: Up to 1.75px
Noise: Up to 8% of pixels
Bounding Box: Rotation: Between -14° and +14°
Bounding Box: Exposure: Between -15% and +15%