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[Computer Vision] Semantic Segmentation Demo with Tensorflow Keras

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Deep Learning Image Segmentation Demo

This project is a short demonstration showcasing my experience with deep learning using TensorFlow Keras. The goal is to perform image segmentation using a Fully Convolutional Network (FCN) implemented in FCN.py. The segmentation results can be visualized using start.py.

Project Structure

  • FCN.py: Fully Convolutional Network model for image segmentation.
  • start.py: Script to perform image segmentation and visualize results.
  • hw2_data/:
    • images/: Testing images.
    • segmentation/: Ground-truth segmentation masks.
    • tf_segmentation/: Predicted segmentation masks using TensorFlow Keras.
  • hw2_scripts/keras-deeplab-v3-plus/:
    • imgs/: result images.

How to Run

Run the image segmentation script:

python start.py

Visual Results

Seg-Results Seg-Results2 Seg-Results3

Note to Recruiters

This project serves as a showcase of my skills in deep learning, particularly in image segmentation using TensorFlow Keras. Feel free to explore the code in FCN.py and start.py in hw2_scripts/ to understand the implementation details.

If you have any questions or would like to discuss the project further, please feel free to reach out.

Thank you for your time!

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[Computer Vision] Semantic Segmentation Demo with Tensorflow Keras

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