瀬戸内フィッシュカウンター
1+
Downloads
Everyone
info
About this app
[Main functions]
Automatic identification of fish type and quantity: Simply take a photo of the fish lined up on the boat deck and the type and number will be automatically identified.
Instant display of results: Even when you catch a lot of fish, you can instantly display the results on the screen by taking a photo on the spot.
Selecting from image files: If you have already taken photos, you can also select from local image files for analysis.
【how to use】
Open the app and take a photo directly with camera or select an image from Gallery.
If possible, take photos of the fish lined up on the deck of your boat from directly above. This provides the highest identification accuracy.
When you upload a photo to the app, it will perform image analysis and display the type and quantity of each fish on the screen.
[Feedback and Support]
This app is currently under development and we aim to improve its accuracy. If we receive actual fishing data from our users, we can use it to improve the app. Please use the in-app feedback function to provide feedback and image data.
Target fish (fish that can often be caught by boat in the Seto Inland Sea)
*Thailand
*Yamachi
*Akou
Etc.
【Notes】
Accuracy may deteriorate if the fish overlap.
The accuracy of the app is updated regularly to improve the user experience.
technical details
This app uses cutting-edge object detection technology "YOLOv8". YOLO (You Only Look Once) is a deep learning model that looks at the entire image at once to detect objects and predict their location and category. When identifying fish, it is possible to recognize the types and locations of multiple fish in real time from a single image.
We also use Roboflow for image annotation and dataset preparation. Roboflow is a platform that can centralize image preprocessing, annotation, and dataset management, supporting highly accurate model learning. The training data used is publicly available, allowing users to directly check its accuracy and approach. We use NoLang service for videos.
Automatic identification of fish type and quantity: Simply take a photo of the fish lined up on the boat deck and the type and number will be automatically identified.
Instant display of results: Even when you catch a lot of fish, you can instantly display the results on the screen by taking a photo on the spot.
Selecting from image files: If you have already taken photos, you can also select from local image files for analysis.
【how to use】
Open the app and take a photo directly with camera or select an image from Gallery.
If possible, take photos of the fish lined up on the deck of your boat from directly above. This provides the highest identification accuracy.
When you upload a photo to the app, it will perform image analysis and display the type and quantity of each fish on the screen.
[Feedback and Support]
This app is currently under development and we aim to improve its accuracy. If we receive actual fishing data from our users, we can use it to improve the app. Please use the in-app feedback function to provide feedback and image data.
Target fish (fish that can often be caught by boat in the Seto Inland Sea)
*Thailand
*Yamachi
*Akou
Etc.
【Notes】
Accuracy may deteriorate if the fish overlap.
The accuracy of the app is updated regularly to improve the user experience.
technical details
This app uses cutting-edge object detection technology "YOLOv8". YOLO (You Only Look Once) is a deep learning model that looks at the entire image at once to detect objects and predict their location and category. When identifying fish, it is possible to recognize the types and locations of multiple fish in real time from a single image.
We also use Roboflow for image annotation and dataset preparation. Roboflow is a platform that can centralize image preprocessing, annotation, and dataset management, supporting highly accurate model learning. The training data used is publicly available, allowing users to directly check its accuracy and approach. We use NoLang service for videos.
Updated on
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No data shared with third parties
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No data collected
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App support
About the developer
赤坂 佳紀
takebitfish@gmail.com
Japan
