Universe

Balls Counting Computer Vision Dataset

bynew-workspace-qgvlwTask:
Object Detection
License:MIT58 views3 downloads
See all 102 imagesBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sampleBalls Counting Balls sample

About Balls Counting Dataset

Here are a few use cases for this project:

  1. Sports Analysis: The Balls Counting model can be used to analyze sports events, counting the number of balls in a frame or scene, which could be useful for sports like tennis, golf, table tennis, or baseball to study the behavior of the balls during practice or matches.

  2. Inventory Management: This model can be applied in warehouses or sports stores to automate the process of counting the stock of different types of balls, making the inventory system more efficient and reducing human error.

  3. Quality Control: In factories producing balls, the computer vision model can ensure that the required quantity of balls is accurately manufactured and packaged, as well as detecting defective items during the production process.

  4. Ball-Pit Tracking: In entertainment venues where ball pits are featured, the model can be used to monitor and count the number of balls in a specific area, ensuring that balls are regularly maintained and replenished in case of loss or damage.

  5. Environmental Cleanup: The Balls Counting model can be employed in beach or park cleanups to detect and quantify disposed balls, assisting in more efficient waste management and pollution reduction.

Use Free B and Balls 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": "B, Balls"
  },
  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

LicenseMIT

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

@misc{ balls-counting_dataset,
  title = { Balls Counting Dataset },
  type = { Open Source Dataset },
  author = { new-workspace-qgvlw },
  howpublished = { \url{ https://universe.roboflow.com/new-workspace-qgvlw/balls-counting } },
  url = { https://universe.roboflow.com/new-workspace-qgvlw/balls-counting },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { jan },
  note = { visited on 2026-07-29 },
}

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