Universe

cifar16 Computer Vision Dataset

byampTask:
Object Detection
License:CC BY 4.0127 views
See all 2.2k imagescifar16 fcjfnfgng sample showing bottled_drinks, canned_drinks, chip, milkcifar16 fcjfnfgng sample showing banana, chewing_gum, liquid_soap, milkcifar16 fcjfnfgng sample showing papercifar16 fcjfnfgng sample showing liquid_soapcifar16 fcjfnfgng sample showing bottled_drinks, canned_drinks, chip, milk, watercifar16 fcjfnfgng sample showing bottled_drinks, canned_drinks, chip, instant_noodles, milk, watercifar16 fcjfnfgng sample showing canned_drinks, chipcifar16 fcjfnfgng sample showing bottled_drinks, canned_drinks, chip, milk, watercifar16 fcjfnfgng sample showing papercifar16 fcjfnfgng sample showing bottled_drinks, canned_drinks, chip, milk, watercifar16 fcjfnfgng sample showing bottled_drinks, canned_drinks, chip, instant_noodles, milk, watercifar16 fcjfnfgng sample showing bottled_drinks, canned_drinks, chip, milk, water

About cifar16 Dataset

Here are a few use cases for this project:

  1. Retail Inventory Management: The cifar16 model can be used by retail businesses to automatically track and manage inventory of products like canned drinks, bottled drinks, chips, milk, etc. It can provide real-time updates on inventory levels, thus aiding in efficient stock management.

  2. Waste Management and Recycling: This model can be used to identify items in waste or recycling loads. It can help in efficient sorting of recyclable items such as cans, bottles, and paper, contributing to enhanced waste management strategies.

  3. Grocery Store Self-checkout Systems: The cifar16 model could be integrated into self-checkout systems at grocery stores. Customers can quickly scan items themselves, speeding up the checkout process and reducing queues.

  4. Health & Nutrition Apps: Fitness or nutrition tracking apps can use this model to identify foods and their likely nutritional value, helping users track their dietary habits.

  5. Smart Home Appliances: Integrated into smart fridges or pantry systems, the model could keep an inventory of available food and household items, suggest when to restock certain items, or even propose recipes based on available ingredients.

Use Free Apple, Banana and Paper 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": "apple, banana, paper, water, pear"
  },
  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{ cifar16_dataset,
  title = { cifar16 Dataset },
  type = { Open Source Dataset },
  author = { amp },
  howpublished = { \url{ https://universe.roboflow.com/amp-ctvtq/cifar16 } },
  url = { https://universe.roboflow.com/amp-ctvtq/cifar16 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { nov },
  note = { visited on 2026-07-29 },
}

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