Advanced lane-finding for ADAS application
We will make a line finding algorithm which could be used for ADAS (Advanced Driving Assistance System) applications.
Line detection in this tutorial will cover :
Line detection of ego vehicle’s current lane
Line detection of ego vehicle’s next lane (next-left side and next-right lane)
Confidence level of each detected line
Line-type of each detected line
Curve-fitting by 3-rd polynomial
Build a Traffic Sign Recognition with Keras/Tensorflow
Intrigued by the question 'What is deep learning ?'. Let's get a gentle deep dive to discover deep-learning by simplified notions with this tutorial . The goals of this project are the following:
-[x] Load the data set
-[x] Explore, summarize and visualize the data set
-[x] Design, train and test with different model architectures (LeNet, GoogLeNet, ResNet34)
-[x] Use the model to make predictions on new images
-[x] Analyze the softmax probabilities of the new images
Use OpenCV for Face Detection then pilote a Pi Camera with 2 servos in order to keep the tracked-face always in the center of camera-frame.
This is a very fun project in collaboration with Clément Coste to get start with Raspberry and 3D-printing.
#face_tracking #Raspberry #pan_tilt_camera
Line detection with Canny Filter and Hough Transform
In this tutorial, we apply technics based on Canny Filter and Hough Transform to detect lines.
Our processing consist of :
- [x] Colour selection
- [x] Gaussian filter with small kernel size to detect even blurred lines in far left/right side
- [x] Canny edge detection
- [x] Zone of interest filtering
- [x] Probabilistic Hough Transform