captcha-system | Code open-source permettant de créer un Captcha dans son | Bot library
kandi X-RAY | captcha-system Summary
kandi X-RAY | captcha-system Summary
Code open-source permettant de créer un Captcha dans son serveur !.
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QUESTION
I am working on a CAPTCHA-system at the moment. For this I am creating random pictures with some basic math-problems on it. The user has to give the correct anser before submitting the form.
Here's the code:
...ANSWER
Answered 2020-Sep-07 at 20:24There are several ways to handle this.
You could create a unique filename per user - that is per address and port using the $_SERVER['REMOTE_ADDR'] and $_SERVER['REMOTE_PORT'] variables to make a filename (possibly along with the time).
Note: port will change if socket is closed so if your client page isn't keeping a socket open over js, you will need to maintain a session id. The session ID would need to be generated server side and stored on the client side until the client is ready to return it along with the verification.
You could make php take out semaphors for each client.
QUESTION
I have found the following code on this website:
...ANSWER
Answered 2019-Mar-28 at 10:34This is doing the wrong thing:
QUESTION
Context: I'm trying learning machine-learning using python3. My intended goal is to create a CNN program that can guess simple 4 letters 72*24 pixels CAPTCHA image as below: CAPTCHA Image Displaying VDF5. This challenge was inspired by https://medium.com/@ageitgey/how-to-break-a-captcha-system-in-15-minutes-with-machine-learning-dbebb035a710, which I thought would be a great challenge for me to learn k-means clustering and CNN.
Edit--- I see I was being too "build me this guy". Now that I found scikit, I'll try to learn it and apply that instead. Sorry for annoying you all.
...ANSWER
Answered 2018-Sep-10 at 17:51It seems as if you are looking to build a machine learning algorithm for educational purposes. If so, import TensorFlow and get to it! However, seeing as your question seems to be "create this for me" you might be better off simply using existing implementations from the scikit learn package. Simply import scikit learn, make an instance of the KNearestNeighborClassifier
train it, and boom you've cracked this problem.
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