Text-based CAPTCHA has become one of the most popular methods for preventing bot attacks. With the rapid development of deep learning techniques, many new methods to break text-based CAPTCHAs have been developed in recent years. However, a holistic and uniform investigation and comparison of these attacks’ effects is lacking due to inconsistent choices of model structures, training datasets, and evaluation metrics.
Label : 00AQ59V0x5 Label : 0A3A28oY8HWeb-app file as app.py: app.py
Final notebook : notebook
Note : The final notebook mentions the working of the model as well as the reduction in CTC loss.
A Connectionist Temporal Classification Loss, or CTC Loss, is designed for tasks where we need alignment between sequences, but where that alignment is difficult - e.g. aligning each character to its location in an audio file. It calculates a loss between a continuous (unsegmented) time series and a target sequence. It does this by summing over the probability of possible alignments of input to target, producing a loss value which is differentiable with respect to each input node.
https://huggingface.co/spaces/PushkarA07/Captcha-breaker-project