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Used UNET approach to remove background and classify body parts from image.

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The U-Net model is trained on a segmented or non segmented dataset. it consist of images of different womens with their Fancy outwears. The dataset i found is too big. but due to complex architecture of U-Net. i Trained it on 50 images and test on 20. the size of images are (600,400,3) but trained by resizing it to (400,256,3) due to High memory usage problem in U-Net architecture.

Dataset: You can view dataset uploaded on My google drive.

( https://drive.google.com/drive/folders/18yU_YryMzuNRX_W1_oNDfyKb318ANX5H?usp=sharing ).

image_13 image_13

Model:- Due to large and complex model. it's size is 105MB. which is not uploadable to GitHub. So for model view You can download it from my drive link.

( https://drive.google.com/file/d/1-NjgsUHlNW4YxzWjQ9Ht2ilXZCsGPIBg/view?usp=sharing )

Model Architecture:

Screenshot (73) Screenshot (74)

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Used UNET approach to remove background and classify body parts from image.

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