underwater_trash_detection Computer Vision Model

byjeeviTask:
Object Detection
License:CC BY 4.0

How to use the underwater_trash_detection Detection API

Try This Model

Drop an image here or click to upload

Or try a test image 

Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="underwater_trash_detection-l7pgg/2")
Give your agent everything it needs

Or, Use Free Mask, Can and Glove 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": "Mask, can, glove, tire, cellphone"
  },
  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 

About underwater_trash_detection Model

The project aims to develop an image processing solution for detecting underwater debris and garbage using the Yolo V8 deep learning algorithm. The images used for this project will be preprocessed to remove noise using the Dark Channel Prior approach described in the research paper "Single Image Haze Removal Using Dark Channel Prior" by Kaiming He, Jian Sun, and Xiaoou Tang.Link to the Research Paper

Cite This Project

LicenseCC BY 4.0

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

@misc{ underwater_trash_detection-l7pgg_dataset,
  title = { underwater_trash_detection Dataset },
  type = { Open Source Dataset },
  author = { jeevi },
  howpublished = { \url{ https://universe.roboflow.com/jeevi/underwater_trash_detection-l7pgg } },
  url = { https://universe.roboflow.com/jeevi/underwater_trash_detection-l7pgg },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

Similar Projects

See More