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Background

A leading environmental research organization approached us to develop an advanced object detection model to analyze aerial RGB images of vegetation and pathways. The primary goal was to identify three specific objects of interest:

Paths/Roads (blue)

Continuous linear shapes.

Small Gaps in Vegetation (red)

Circular gaps (< 50 cm).

Elongated Gaps in Vegetation (green)

Rectangular gaps (~50 x 100 cm).

Project Objectives

  • Improve the accuracy of object detection for aerial image analysis.
  • Ensure the robustness of the solution for varying image quality.
  • Deploy the best-performing model for long-term monitoring and research purposes.

Work Phases

#1. Dataset Preparation

  • Tasks:
  • Verify Image Quality: Analyzed the quality and consistency of RGB images provided.
  • Manual Annotation: Manually annotated around 250 images to establish a high-quality training subset.
  • Model-Assisted Annotation: Trained a preliminary model on the manually annotated subset. The model automated annotation for the remaining dataset (~3,000 images).
  • Review & Correction: Reviewed all model-generated annotations and corrected errors.

#2. Tool Selection and Benchmarking

  • Tasks:
  • Tool Evaluation: Assessed multiple object detection frameworks: YOLOv5, TensorFlow Object Detection API, and Detectron2.
  • Initial Benchmarking: Tested each framework on 100 annotated images, evaluating their speed, precision, recall, and ease of integration.

#3. Data Preprocessing, Model Training, and Validation

  • Tasks:
  • Preprocess Images: Used OpenCV to normalize, preprocess images, and optimized them for model training.
  • Train & Fine-Tune Models: Configured and trained the Detectron2 model using an NVIDIA A100 GPU.
  • Validation: Evaluated on a test dataset (500 images), tracking metrics such as accuracy, precision, recall, and F1 score.

#4. Full Dataset Testing and Result Analysis

  • Tasks:
  • Full Dataset Testing: Tested the fine-tuned Detectron2 model on the entire dataset (~3,000 images). The model achieved consistent results across diverse image conditions.
  • Result Analysis & Report: Analyzed model accuracy, reliability, and performance. Compiled a final report summarizing the findings and recommendations.
  • Deployment: Deployed the final model with accuracy for all object types. Set up a monitoring system to track prediction reliability and flag anomalies.

Outcomes & Key Achievements

Improved Accuracy

Achieved high precision and recall for all object types, meeting the client’s requirements.

Optimized Workflow

Achieved high precision and recall for all object types, meeting the client’s requirements.

Scalable Deployment

Deployed the model for real-time image detection with a user-friendly monitoring dashboard.

Tools & Technologies Used

Annotation Tools

  • CVAT

Image Processing

  • OpenCV (for preprocessing and segmentation)

Object Detection Frameworks

  • YOLOv5
  • TensorFlow Object Detection API
  • Detectron2

Model Training & Testing

  • PyTorch
  • TensorFlow

Cloud Compute

  • AWS EC2

Visualization & Monitoring

  • Matplotlib
  • TensorBoard

Team Composition

  • Project Manager: 1
  • Data Engineers: 1
  • Data Scientists: 2
  • Computer Vision Engineer: 1
  • Annotation Specialist: 2
  • DevOps Engineer: 1
  • QA: 1

Clientele

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Testimonials

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Tony Lehtimaki

DIRECTOR - AMEOS

Spain

Very professional, accurate and efficient team despite all the changes I had them do. I look forward to working with them again.

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CEO - BEESPOKE

France

They are great at what they do. Very easy to communicate with and they came through faster than I hoped. They delivered everything I wanted and more! I will certainly use them again!

Vivek Singh

MARKETING & SALES HEAD - VARMORA

Gujarat

I really liked their attention to detail and their sheer will to do the job at hand as good as possible beyond professional boundaries.

Nimesh Patel

DIRECTOR - COVERTEK CERAMICA

Gujarat

Excellent work, and on time with all goals. Communication was very easy, and knowledge of work was excellent. Will be working with them on upcoming projects. I highly recommend.

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Their team of experts jotted down every need of mine and turned them into a high performing web application within no time. Just superb!

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Contact number

+91 8487981277

+1 770 796 0077

Email Address

[email protected]

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