Faster-Rcnn Image Dataset
Versions
Out of Frame
v41
Dec 31, 2022
FallDown2279
v40
Dec 31, 2022
Accident2279
v39
Dec 30, 2022
2022-12-30 1:30pm
v38
Dec 30, 2022
2022-12-30 1:28pm
v37
Dec 30, 2022
NewAgument
v34
Dec 13, 2022
New_BalanceDataser
v29
Dec 3, 2022
2022-12-04 6:30am
v28
Dec 3, 2022
balance-Newdataset
v27
Nov 29, 2022
2022-11-27 3:57pm
v26
Nov 27, 2022
2022-11-27 3:56pm
v25
Nov 27, 2022
2022-11-27 3:46pm
v24
Nov 27, 2022
2022-11-27 3:45pm
v23
Nov 27, 2022
2022-11-27 3:43pm
v22
Nov 27, 2022
2022-11-27 3:40pm
v21
Nov 27, 2022
2022-11-27 3:13pm
v20
Nov 27, 2022
2022-11-27 11:41am
v19
Nov 27, 2022
Adddata-nonIsolated-608
v18
Nov 27, 2022
Add-data-Isolate
v17
Nov 27, 2022
Old-Agument3.5k
v16
Nov 21, 2022
2022-11-21 9:55pm
v15
Nov 21, 2022
2022-11-21 9:45pm
v14
Nov 21, 2022
Use for test CM
v13
Apr 15, 2022
Train-Test-Agu2022
v12
Apr 5, 2022
Val-Aug2022
v11
Apr 5, 2022
Test-Aug2022
v10
Apr 5, 2022
Test-Augmentation2
v9
Apr 2, 2022
Test-Augmentation
v8
Apr 2, 2022
Resize-nonfiller
v7
Mar 7, 2022
non Fillter
v6
Mar 7, 2022
Modifly class
v5
Mar 7, 2022
Non Resize
v4
Mar 7, 2022
Fully Annotate
v3
Mar 7, 2022
2022-03-07 3:10pm
v1
Mar 7, 2022
v15
2022-11-21 9:55pm
Generated on Nov 21, 2022
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.
934 Total Images
View All Images
Dataset Split
Train Set 94%
876Images
Valid Set 6%
58Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Static Crop: 25-54% Horizontal Region, 11-52% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Contrast Stretching
Tile: 2 rows x 2 columns
Modify Classes: 1 remapped, 0 dropped
Filter Null: Require all images to contain annotations.
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Applied
Crop: 0% Minimum Zoom, 15% Maximum Zoom
Rotation: Between -20° and +20°
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Exposure: Between -25% and +25%
Bounding Box: Noise: Up to 5% of pixels
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