​I Built My Own Self-Driving Car. Part #1

In this part of article I am going to build a very basic car detection classifier using Python and OpenCV. There is a variety of different object detection and classification techniques and I am going to pay particular attention to the use of Haar Cascades. However, the Haar Cascade classification itself would be covered very briefly in this particular article.

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https://blog.maddevs.io/i-built-my-own-self-driving-car-part-1-4478551ee205

🔗 I Built My Own Self-Driving Car. Part #1 – Mad Devs

​I Built My Own Self-Driving Car. Part #3
In the last article, I have introduced you to a very simple lane detection with OpenCV. Taking into account the simplicity, it was doing well. However, it was not up to my expectations. Looks like the current solution that I am going to show you today does not get better unless you want switch to the Recurrent Convolutional Neural Networks (and this is exactly what I am up to). We are going to talk about a way to get better results based on the Hough Transform method output.

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https://blog.maddevs.io/i-built-my-own-self-driving-car-part-3-1ca1d85e9d59

🔗 I Built My Own Self-Driving Car. Part #3 – Mad Devs

​I Built My Own Self-Driving Car. Part #2

In my last article, I have played around with OpenCV and Haar Cascade Classifier in order to detect vehicles. It did not perform very well though. There were many false predictions and the FPS could not get above 15. Today I will introduce you to the third version of the YOLO algorithm developed for the Darknet and ported to Tensorflow and Keras so we can use a nice and shiny Python environment. We are not going to train our own model today and use pre-trained weights.

#programming #IT #artificialintellegence #developer #HaarCascade #Python #OpenCV #MadDevs

https://blog.maddevs.io/i-built-my-own-self-driving-car-part-2-e3894ce4eb42

🔗 I Built My Own Self-Driving Car. Part #2 – Mad Devs

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