WebJun 14, 2024 · class CTCLayer(layers.Layer): def __init__(self, name=None): super().__init__(name=name) self.loss_fn = keras.backend.ctc_batch_cost def call(self, y_true, y_pred): # Compute the training-time loss value and add it # to the layer using `self.add_loss ()`. batch_len = tf.cast(tf.shape(y_true) [0], dtype="int64") input_length = … WebJul 3, 2024 · In the model compile line, # the loss calc occurs elsewhere, so use a dummy lambda function for the loss model.compile (loss= {'ctc': lambda y_true, y_pred: y_pred}, optimizer=sgd) they are using a dummy lambda function with y_true,y_pred as inputs and y_pred as output. But y_pred was already defined previously as the softmax activation.
基于PaddleOCR的小学生手写汉语拼音识别 - CSDN博客
WebJun 15, 2024 · CTC For loss calculation, we feed both the ground truth text and the matrix to the operation. The ground truth text is encoded as a sparse tensor. The length of the input sequences must be passed to both CTC operations. We now have all the input data to create the loss operation and the decoding operation. Training WebApr 2, 2024 · This is an example CTC decoder written in Python. The code is: intended to be a simple example and is not designed to be: especially efficient. The algorithm is a … shut down email
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Web53 minutes ago · I have been trying to solve this issue for the last few weeks but is unable to figure it out. I am hoping someone out here could help out. I am following this github repository for generating a model for lip reading however everytime I try to train my own version of the model I get this error: Attempt to convert a value (None) with an … WebJul 13, 2024 · loss = ctc_loss (input, target, input_lengths, target_lengths) print(loss) # tensor (0.1839, grad_fn=) That this the main idea of CTC Loss, but there is an obvious flaw:... shutdown engineer