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A post showing how to convert your dataset to .tfrecords file and later on use it as a part of a computational graph. Introduction In this post we will cover how to convert a dataset into .tfrecord file. Binary files are sometimes easier to use, because you don’t have to specify different directories for images and groundtruth annotations. While storing your data in binary file, you have your data
A post showing how to perform Image Segmentation using Fully Convolutional Networks that were trained on PASCAL VOC using our framework. Introduction In this post we want to present Our Image Segmentation library that is based on Tensorflow and TF-Slim library, share some insights and thoughts and demonstrate one application of Image Segmentation. To be more precise, we trained FCN-32s, FCN-16s an
Image Segmentation with Tensorflow using CNNs and Conditional Random Fields A post showing how to perform Image Segmentation with a recently released TF-Slim library and pretrained models. It covers the training and post-processing using Conditional Random Fields. Introduction In the previous post, we implemented the upsampling and made sure it is correct by comparing it to the implementation of t
Image Classification and Segmentation with Tensorflow and TF-Slim A post showing how to perform Image Classification and Image Segmentation with a recently released TF-Slim library and pretrained models. Inroduction In this post I want to show an example of application of Tensorflow and a recently released library slim for Image Classification, Image Annotation and Segmentation. In the post I focu
Google Summer of Code: patent-free Face Detection for Scikit-image in Python. Introduction An introduction post about my project where I describe the chosen Face Detection algorithm, explain why it was chosen and briefly go over all the stages of it. Algorithm choice Usually, when it goes to the Face Recognition task, the most important criteria are: Good False Positive and False Negatives ratio (
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