Universe

test Computer Vision Dataset

byfairyTask:
Object Detection
License:CC BY 4.0154 views9 downloads
See all 361 imagestest draw sample showing flower, person, suntest draw sample showing ballon, cat, child, cloud, house, person, sun, tree, windowtest draw sample showing child, cloud, person, umbrellatest draw sampletest draw sample showing persontest draw sample showing cloud, flower, person, sun, treetest draw sample showing animal, bird, cat, flower, house, person, sun, treetest draw sample showing flower, treetest draw sample showing house, sun, treetest draw sample showing house, treetest draw sample showing ballon, child, cloud, person, rain, rainbow, suntest draw sample showing animal, house, person

About test Dataset

Here are a few use cases for this project:

  1. Educational App: Use the model in an educational app meant for children to help them learn and identify different drawings. When a child draws something, the app identifies and labels the drawing in real-time.

  2. Content Filtering: Implement the model in social networks or content sharing platforms to identify and auto-tag user-uploaded sketches, helping to improve content categorization and searchability.

  3. Augmented Reality Game: In an AR-based game, players could draw an object in the real world, which the game would identify and then animate or interact with in the gaming environment.

  4. Graphic Design Software: Design software could utilize the model to offer suggestions to designers based on their current project. Drawing a tree, for example, might prompt the software to suggest similar tree designs for inspiration.

  5. Image Sorting: Use the model in photo storage or organization software to categorize and sort drawings or sketches based on their contents, making it easier for users to manage their collections.

Use Free Car, Dog and Cat 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": "car, dog, cat, apple, ball"
  },
  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{ test-wonib_dataset,
  title = { test Dataset },
  type = { Open Source Dataset },
  author = { fairy },
  howpublished = { \url{ https://universe.roboflow.com/fairy/test-wonib } },
  url = { https://universe.roboflow.com/fairy/test-wonib },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2024 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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