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Image-Segmentation Project

A deep learning and computer vision project to segment and locate the image of humans from various backgrounds

  • used U-net architecture with efficientnet-b0 as encoder for CNN to train the model
  • used albumentations for randomly augment the image with corresponding the mask
  • used a combination of Binary Cross Entropy loss and Dice loss for computing loss
  • used OpenCV for reading and pre-processing images
  • used cuda runtime for faster training