Universe

GOOD ML Computer Vision Model

bylinggaTask:
Object Detection
License:CC BY 4.032 views3 downloads

How to use the GOOD ML Detection API

Try This Model

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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="good-ml-zdfpr/2")
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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": "bounding 1, bounding 2, bounding 3, bounding 4, bounding 5"
  },
  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 
See all 226 imagesGOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8GOOD ML piecies sample showing bounding 1, bounding 2, bounding 3, bounding 4, bounding 5, bounding 6, bounding 7, bounding 8

About GOOD ML Model

Here are a few use cases for this project:

  1. Quality Control in Manufacturing: Utilize GOOD ML to inspect various products on the assembly line, ensuring that they meet quality standards. By identifying bounding classes of individual components, the model can quickly detect incorrect assembly, misaligned parts, or missing elements in the final product.

  2. Recycling and Waste Management: Use the GOOD ML model to streamline the process of sorting waste and recyclable items at waste treatment facilities. Identifying objects' bounding classes can help machines separate objects more efficiently and reduce the manual labor needed for sorting.

  3. Inventory Management: Implement the GOOD ML model in warehouses or retail stores to monitor products on shelves and track stock levels. Bounding class identification can enable automatic restocking notifications, as well as catch misplaced items in real-time.

  4. Object Recognition for Autonomous Vehicles: Equip self-driving vehicle systems with the GOOD ML model to enhance road safety by identifying and categorizing different objects in its environment. detections of bounding classes can help the vehicle system make more informed decisions, avoiding obstacles, and navigating complex scenarios.

  5. Assisting Visually Impaired Users: Create assistive technology with the help of the GOOD ML model to help visually impaired users identify everyday objects. By quickly detecting various bounding classes, the software can describe objects to users and provide useful context about their surroundings.

Cite This Project

LicenseCC BY 4.0

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

@misc{ good-ml-zdfpr_dataset,
  title = { GOOD ML Dataset },
  type = { Open Source Dataset },
  author = { lingga },
  howpublished = { \url{ https://universe.roboflow.com/lingga/good-ml-zdfpr } },
  url = { https://universe.roboflow.com/lingga/good-ml-zdfpr },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jul },
  note = { visited on 2026-07-29 },
}

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