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  The **AUTOFISH** dataset comprises 1500 high-quality images of fish on a conveyor belt. It features 454 unique fish with class labels, IDs, manual length measurements,
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  and a total of 18,160 instance segmentation masks.
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- The fish are partitioned into 25 groups, with 14 to 24 fish in each group. The
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- number of fish and distribution of species in each group were pseudo-randomly selected to mimic real-world scenarios. Every group is partitioned
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- into three subsets: *Set1*, *Set2*, and *All*. *Set1* and *Set2* contain half of the fish each, and none of the
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- fish overlap or touch each other. *All* contains all the fish from the group, purposely placed in positions with high overlap. Every group directory contains 20 images for
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- each set, where variation is introduced by changing the position and orientation of the fish. Exactly half of every set is with the fish on their one side, while the other
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- half has the fish flipped.
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  The available classes are:
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  - Cod
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  - Horse mackerel
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  - Other
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- The annotations are in COCO format, with a structure as per the following example:
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- ```yaml
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  {
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  "images": [
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  {
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  },
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  ...
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  ],
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- }
 
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  The **AUTOFISH** dataset comprises 1500 high-quality images of fish on a conveyor belt. It features 454 unique fish with class labels, IDs, manual length measurements,
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  and a total of 18,160 instance segmentation masks.
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+ The fish are partitioned into 25 groups, with 14 to 24 fish in each group. Each fish only appears in one group, making it easy to create training splits. The
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+ number of fish and distribution of species in each group were pseudo-randomly selected to mimic real-world scenarios. In addition to all the labeled data, two high-overlap
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+ unlabeled groups, as well as camera calibration images are included.
 
 
 
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  The available classes are:
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  - Cod
 
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  - Horse mackerel
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  - Other
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+ Other information contained in the annotations:
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+ - Segmentation masks
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+ - Bounding boxes
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+ - Lengths
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+ - Unique fish IDs
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+ - 'Side up' referring to the side of the fish that is visible
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+
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+ Extra information: <br>
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+ Every group is partitioned into three subsets: *Set1*, *Set2*, and *All*. *Set1* and *Set2* contain half of the fish each, and none of the
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+ fish overlap or touch each other. *All* contains all the fish from the group, purposely placed in positions with high overlap. Every group directory contains 20 images for
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+ each set, where variation is introduced by changing the position and orientation of the fish. Exactly half of every set is with the fish on their one side, while the other
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+ half has the fish flipped.
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+
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+ In cases of high overlap, where fish occlude each other, some annotations might have multiple segmentation masks in a list of lists format.
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+
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+ <!-- The annotations are in COCO format, with a structure as per the following example: -->
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+ <!-- ```yaml
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  {
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  "images": [
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  {
 
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  },
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  ...
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  ],
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+ } -->