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