How to implement ctc loss using tensorflow keras (feat. CRNN example)

Code: using tensorflow 1.14 The tk.keras.backend.ctc_batch_cost uses tensorflow.python.ops.ctc_ops.ctc_loss functions which has preprocess_collapse_repeated parameter. In some threads, it comments that this parameters should be set to True when the tf.keras.backend.ctc_batch_cost function does not seem to work, such as inconverging loss. However, my experience is that although setting this parameter to True Read more…

DenseNet paper review

paper url: https://arxiv.org/pdf/1608.06993.pdf Core Idea The core of DenseNet is using Dense blocks which is an essential of the idea behind it all. The core idea is that within a block, it contains multiple layers. All previous attempts before this paper only used the layers in sequential manner. An output Read more…

tensorRT stuff

tensorRT support matrix: https://docs.nvidia.com/deeplearning/dgx/integrate-tf-trt/index.html#matrix to apply the tensorRT optimizations, it needs to call create_inference_graph function. Check here for more details on this function. the graph that is fed to create_inference_graph should be freezed. To know more on what exactly means by “freezing”, check here. for using bare tensorRT python module, Read more…