Fish Image Dataset
Versions
2023-02-21 1:58pm
v44
Feb 21, 2023
2020-08-26 9:46am
v43
Aug 26, 2020
2020-08-26 9:32am
v42
Aug 26, 2020
2020-08-26 9:27am
v41
Aug 26, 2020
2020-08-18 12:39pm
v40
Aug 18, 2020
2020-08-18 10:26am
v39
Aug 18, 2020
2020-08-18 10:08am
v38
Aug 18, 2020
2020-08-18 10:06am
v37
Aug 18, 2020
2020-08-18 9:56am
v36
Aug 18, 2020
2020-08-18 9:32am
v35
Aug 18, 2020
2020-08-18 9:31am
v34
Aug 18, 2020
2020-08-18 8:55am
v33
Aug 18, 2020
2020-08-18 8:47am
v32
Aug 18, 2020
2020-08-17 11:02pm
v31
Aug 18, 2020
2020-08-17 10:56pm
v30
Aug 18, 2020
2020-08-17 10:53pm
v29
Aug 18, 2020
2020-08-17 4:07pm
v28
Aug 17, 2020
2020-08-17 3:51pm
v27
Aug 17, 2020
2020-08-17 2:45pm
v26
Aug 17, 2020
2020-08-17 2:30pm
v25
Aug 17, 2020
2020-08-12 1:24am
v24
Aug 12, 2020
filter-mosaic
v23
Aug 3, 2020
2020-08-02 6:31pm
v22
Aug 2, 2020
crop-filter
v21
Aug 1, 2020
crop-filter-mosaic
v20
Aug 1, 2020
crop-filter
v17
Aug 1, 2020
static-crop
v16
Aug 1, 2020
mosaic
v10
Jul 29, 2020
2020-07-28 10:52pm
v9
Jul 29, 2020
2020-07-15 10:09pm
v8
Jul 16, 2020
2020-07-15 10:08pm
v7
Jul 16, 2020
2020-07-15 5:06pm
v6
Jul 15, 2020
mosaic+cutout
v5
Jul 15, 2020
2020-07-15 11:45am
v4
Jul 15, 2020
2020-07-15 11:45am
v3
Jul 15, 2020
2020-07-15 11:44am
v2
Jul 15, 2020
416x416
v1
Jul 10, 2020
v16
static-crop
Generated on Aug 1, 2020
Popular Download Formats
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.
MT-YOLOv6
MT-YOLOv6 TXT annotations used with meituan/YOLOv6.
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.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
680 Total Images
View All Images
Dataset Split
Train Set 70%
476Images
Valid Set 20%
136Images
Test Set 10%
68Images
Preprocessing
Auto-Orient: Applied
Static Crop: 67-98% Horizontal Region, 55-91% Vertical Region
Augmentations
No augmentations were applied.
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