Universe

Packages Computer Vision Dataset

byHAWTask:
Object Detection
License:MIT135 views4 downloads
See all 673 imagesPackages Packages sample showing packagePackages Packages samplePackages Packages samplePackages Packages sample showing packagePackages Packages sample showing packagePackages Packages samplePackages Packages samplePackages Packages samplePackages Packages sample showing packagePackages Packages sample showing packagePackages Packages samplePackages Packages sample showing package

About Packages Dataset

Here are a few use cases for this project:

  1. Ecommerce and Retail Logistics: The "Packages" model can be used in warehouses or logistics centers for automating the process of sorting and categorizing various types of packages. It can streamline operations for businesses dealing with large-scale shipping and receiving of items.

  2. Smart Home Security Systems: The model can be integrated into home security systems to identify delivered packages. When a courier leaves a package at the door, the system can alert the homeowner about the delivery, potentially preventing theft or misplacement.

  3. Robotics: In settings like large warehouses or storage facilities, robots could use the "Packages" model to identify packages, optimizing their picking and placing process, which can make their routes more efficient.

  4. Postal and Delivery Services: The model can aid in identifying poorly labeled or damaged packages within postal services, aiding in their delivery and reducing the rate of lost parcels.

  5. Conveyor Belt Systems: In manufacturing industries or order fulfillment centers, the model could be used to identify items on conveyor belts for quality control, proper separation, or routing to different areas based on the package type.

Use Free Package 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": "package"
  },
  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{ packages-iw8aw_dataset,
  title = { Packages Dataset },
  type = { Open Source Dataset },
  author = { HAW },
  howpublished = { \url{ https://universe.roboflow.com/haw-odap3/packages-iw8aw } },
  url = { https://universe.roboflow.com/haw-odap3/packages-iw8aw },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jul },
  note = { visited on 2026-07-29 },
}

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