Comments (1)
Connectionist Temporal Classification (CTC) is targeted for aligning input and output label sequences, particularly where the length is variable. To address your use case, you'll likely need to change the loss function for a different encoding/merging scheme and the decoder to output fixed sequence lengths.
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Related Issues (20)
- Training error HOT 9
- How to deal with single character input HOT 2
- Using Multiple GPU as a train_device HOT 3
- ctc_loss_calculator.cc Not a valid path HOT 3
- are there any pretrain model file HOT 3
- Input shapes: [72,357,1], [4] and with input tensors computed HOT 3
- It's possible to use a pre-trained model? HOT 1
- CuDnn 7.2.1 HOT 1
- get not good result, HOT 2
- FineTune ! HOT 3
- Model learns nothing about certain characters. HOT 1
- TypeError HOT 4
- Training Error when using my data HOT 1
- 0% GPU-Util when testing HOT 1
- Train on vertical patches HOT 1
- Question Regarding End Model HOT 3
- confidence on sess passing HOT 6
- How to convert .ckpt model to SavedModel .pb format for hosting with Tensorflow Model Serving? HOT 6
- How to batch inference? HOT 5
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