STEAM+Project+computer+vision+color+space

STEAM project -- Compute vision meets art: Explore and DIY Image Filter

Stage 3: Start the STEAM project: , A. Color representation: Hexadecimal B. Colors in images: Binary, gray and color-map C. Color space: RGB --- HSV D. Image arithmetic and Logic Operation E. Advanced image operations in OPENCV (Mar 08 2017)
 * Color representation: Hexidecimal: http://www.discoveryplayground.com/computer-programming-for-kids/rgb-colors/
 * Obtain the pixel color from an image interactively --- reference link: [[file:Matplotlib_in_tk_template.py|Trial code template]]
 * Use hex in GUI design --- reference link: http://www.cnblogs.com/kaituorensheng/p/3287652.html --- section 3.1 --- l = Label(root, text="show", bg="green", font=("Arial", 12), width=5, height=2) # Try to change bg="green" to bg = "#00FF00"
 * Try to edit the font color of a wiki page to see how the color are represented.
 * Try different digits combinations: Trial code: [[file:colorRepDemo.py|colorRepDemo.py]]
 * False color image – color map: http://matplotlib.org/examples/color/colormaps_reference.html and http://stackoverflow.com/questions/12201577/how-can-i-convert-an-rgb-image-into-grayscale-in-python (Refer to the code--- gray = 0.2989 * r + 0.5870 * g + 0.1140 * b)
 * shading_example.py: http://matplotlib.org/examples/pylab_examples/shading_example.html?highlight=gray
 * Simple Thresholding: []
 * Simulation:[[file:Color Maker.jar| color maker]]
 * HSV to RGB converter: http://www.rapidtables.com/convert/color/hsv-to-rgb.htm
 * HSV representation and conversion: []
 * understand Colorspace: [] (the functions in Image module could be replaced by similar ones in opencv)
 * Conversions between color systems: https://docs.python.org/2/library/colorsys.html
 * Color Filtering OpenCV Python Tutorial: []
 * Image calculations:Ox04 : http://docs.opencv.org/trunk/df/d9d/tutorial_py_colorspaces.html
 * Basic operations on images:http://docs.opencv.org/trunk/d3/df2/tutorial_py_basic_ops.html
 * Image arithmetic and Logic Opera: http://docs.opencv.org/trunk/d0/d86/tutorial_py_image_arithmetics.html
 * Bool function in python: http://blog.csdn.net/you_are_my_dream/article/details/52925750
 * Changing color space: http://docs.opencv.org/trunk/df/d9d/tutorial_py_colorspaces.html
 * Image Gradient: http://docs.opencv.org/trunk/d5/d0f/tutorial_py_gradients.html
 * Image threshold: http://docs.opencv.org/trunk/d7/d4d/tutorial_py_thresholding.html
 * Image histograms: http://docs.opencv.org/trunk/de/db2/tutorial_py_table_of_contents_histograms.html
 * Smooth images: http://docs.opencv.org/trunk/d4/d13/tutorial_py_filtering.html
 * Image calculations: first 3 sections: http://docs.opencv.org/trunk/df/d9d/tutorial_py_colorspaces.html
 * Canny Edge Detection: http://docs.opencv.org/trunk/da/d22/tutorial_py_canny.html
 * Image Pyramid: http://docs.opencv.org/trunk/dc/dff/tutorial_py_pyramids.html

Stage 2: Design your GUI Study Python Tkinter: [] Intro demo [] Intro Demo [] Tkinter wiki [] Example code: how complex the GUI could be with Tkinter [] A good example for using Tkinter Note: Python 2 Tkinter, python 3 tkinter (Mar 06 2017)

Stage 1: Build environment and install tools (Mar 03 2017) Python + OpenCV + numpy + matplotlib --- Image [] **Color Space RGB -- BGR**
 * [Mac user] Do not use cv2.imshow, please use matplotlib function plt.imshow(img) and plt.show **
 * cv imread paring with with matplotlib imshow: []
 * Image operations, image as a high-dimensional matrix:[]
 * Matplotlib colormap: []
 * Matplotlib image display with different colormap: []
 * Basic opencv operations: []

[HOMEWORK] Deadline: 20170305 6:00pm as follows you can download here :
 * Modeling Salt noise :** []

Submission: Project progress list