Fish Measure Computer Vision Dataset

bySakrTask:
Instance Segmentation
License:CC BY 4.0243 views8 downloads

About Fish Measure Dataset

Here are a few use cases for this project:

  1. Fishery Management and Conservation: Fish Measure can be used by marine biologists and researchers to monitor Pagrus-Pagrus populations, ensuring their sustainability and adherence to fishing regulations. The model can quickly identify and measure the size of the Pagrus-Pagrus species on trays, helping to evaluate whether the catch is within the permissible limits, leading to more effective conservation efforts.

  2. Quality Control in Seafood Processing: The computer vision model can assist in automating quality control checks in seafood processing plants, ensuring that the Pagrus-Pagrus on trays meet size and weight standards. This will aid in maintaining high-quality products for consumers and meeting industry regulations.

  3. Seafood Retail and Restaurants: Fish Measure can be implemented in retail and restaurant businesses to quickly assess the freshness, quality, and correct serving size of the Pagrus-Pagrus species on trays. Customers will benefit from the assurance of high-quality seafood, while businesses can improve inventory management and reduce food waste.

  4. Educational Purposes: The Fish Measure model can be utilized as an interactive educational tool for students or enthusiasts learning about marine life, particularly the Pagrus-Pagrus species. The model can be used as part of interactive exhibits, mobile applications, or virtual reality experiences, augmenting users' understanding of fish identification and size comparison.

  5. Automated Catch Reporting: Fishing vessels can use the Fish Measure model to automatically record and submit catch data to local authorities, helping to ensure accurate reporting and streamlined compliance with fishing regulations. This will assist in better fisheries management, avoiding overfishing and providing real-time data for ecosystem studies.

Use Free Tray and Pagrus-Pagrus Detection API

Powered by general detection model

Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "Tray, Pagrus-Pagrus"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ fish-measure_dataset,
  title = { Fish Measure Dataset },
  type = { Open Source Dataset },
  author = { Sakr },
  howpublished = { \url{ https://universe.roboflow.com/sakr/fish-measure } },
  url = { https://universe.roboflow.com/sakr/fish-measure },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { feb },
  note = { visited on 2026-07-29 },
}

Similar Projects

See More