Image Annotation

Construction Equipment Annotation

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We successfully completed a project annotating construction equipment, labeling approximately 5,000 images using object detection methods. Our approach ensured high accuracy and fast turnaround, fully meeting the client’s requirements.

Industry Construction & Infrastructure
Timeline 5 days
Data 5,000 images
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Industry Construction & Infrastructure
Timeline 5 days
Data 5,000 images

Challenge

A client from the construction industry needed a dataset for automatic detection of construction equipment on worksites. The goal was to annotate all machinery in the images to enable automated monitoring and tracking of equipment movement.

Key Objectives

  • Image Processing: Annotate construction equipment using object detection techniques.
  • Dataset Creation: Develop a labeled dataset with equipment classes, including dump trucks, cement mixers, and cranes.

Solution

  • 01

    Task Definition & Technical Requirements

    The client provided a list of equipment classes to be annotated, along with detailed technical specifications outlining precise labeling instructions. After carefully reviewing the requirements and clarifying details, we began the annotation process.

  • 02

    Efficient Annotation

    Thanks to a well-prepared workflow, we completed the annotations in just five days. Clear technical guidelines and pre-approved object classes allowed us to streamline the process. The bulk of the annotation work was finished in four days, and when the client provided additional images, our team quickly processed them as well.

    In total, we labeled 20,000 bounding boxes for various types of construction equipment across different locations and conditions. Each equipment class was meticulously annotated according to the given specifications.

  • 03

    Validation Process

    To ensure maximum accuracy, all data underwent an additional validation stage. This involved selecting a representative sample of images for quality checks.

    During validation, we proactively communicated with teams, reporting detected anomalies and providing insights on top-performing and underperforming annotators to team leads.

  • 04

    Training & Quality Assurance

    We place strong emphasis on the quality of our validators’ work. Their ongoing skill development is overseen by a dedicated training department.

Results

  • Timely Completion: All images were annotated within five days, including client-requested revisions.

  • High Efficiency: The project was completed with exceptional accuracy and speed, allowing the client to utilize the data for real-time equipment monitoring.

  • Positive Feedback: The client was highly satisfied with the quality and timeliness of the work, noting that all requirements were fully met.

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