Mort Fish Image Dataset
Versions
2022-04-30 3:00am
v21
Apr 30, 2022
2022-04-29 10:57pm
v20
Apr 29, 2022
2022-04-29 10:56pm
v19
Apr 29, 2022
2022-04-29 10:55pm
v18
Apr 29, 2022
2022-04-29 8:07pm
v17
Apr 29, 2022
2022-04-29 8:06pm
v16
Apr 29, 2022
2022-04-29 7:53pm
v15
Apr 29, 2022
2022-04-23 8:14pm
v14
Apr 23, 2022
2022-04-23 6:16pm
v13
Apr 23, 2022
Optimized
v12
Apr 21, 2022
MIXED
v11
Apr 21, 2022
Sabarni_yarb
v10
Apr 8, 2022
2022-04-06 4:01pm
v9
Apr 6, 2022
2022-04-06 3:58pm
v8
Apr 6, 2022
2022-04-05 2:01am
v7
Apr 5, 2022
ROV_3
v6
Apr 2, 2022
ROV_2
v5
Mar 31, 2022
ROV
v4
Mar 30, 2022
Last_Version
v3
Mar 30, 2022
2022-03-19 3:49pm
v2
Mar 19, 2022
NEW MORT FISH MATE
v1
Mar 19, 2022
v21
2022-04-30 3:00am
Generated on Apr 30, 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.
570 Total Images
View All Images
Dataset Split
Train Set 82%
465Images
Valid Set 11%
63Images
Test Set 7%
42Images
Preprocessing
Auto-Orient: Applied
Static Crop: 25-72% Horizontal Region, 30-95% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 3
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Saturation: Between -25% and +25%
Brightness: Between -49% and +49%
Cutout: 3 boxes with 10% size each
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