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--- opencv_vs_matplotlib [2022/09/23 01:11] – jhagstrand
+++ opencv_vs_matplotlib [2023/01/12 11:39] (current) – removed jhagstrand
@@ Line 1: / Line 1: @@
-====== OpenCV vs matplotlib ======
-data format
-  - both matplotlib and opencv express the image as a numpy array
-  - you can always manipulate the array directly using matrix math
-  - or, both matplotlib and opencv provide methods to do sophisticated operations
-  - there is considerable overlap between the two systems
-  - you can probably do whatever you want with either system
-  - and you can mix and match both systems, so long as you know the differences
-  - in the way they handle the array
-color model
-  - by default, matplotlib uses RGB, opencv uses BGR
-alpha channel
-  - by default, array shape is (y,x,3)
-  - can be changed to (y,x,4), for RGBA or BGRA
-  - example:
-    - y,x,d = myarray.shape
-    - numpy.dstack(myarray, numpy.zeros(y, x))
-    - [[https://stackoverflow.com/questions/39642721/adding-alpha-channel-to-rgb-array-using-numpy]]
-display
-  - by default, matplotlib produces a graph
-  -   - with x,y,z axis, with tickmarks and scale
-  -   - the graph is positioned with margins inside a resizeable window
-  - opencv gives a full-size image in a fixed-size window
-animation
-  - both systems provide systems for animation and user-input handling
-  - matplotlib FuncAnimation allows for an incremental blit
-  - matplotlib allows you to change the data of objects already in the plot
-  - opencv requires you to rewrite the whole screen
-user input
-  - both systems allow you to wait for a key press
-  - both systems provide an event-handler for keyboard and mouse events
-tiling
-  - numpy hstack() and vstack() can be used to tile multiple images into one
-  - in addition, matplotlib uses the Figure->Axes->Plot heirarchy of subplots
-how to overlay transparent plot on top of a photo
-. convert plot to image
-google: convert matplotlib figure to numpy array opencv
-https:  www.autoscripts.net/convert-matplotlib-figure-to-cv2-image  /
-. overlay transparent plot on top of image
-https:  docs.opencv.org/3.4/d5/dc4/tutorial_adding_images.html
-in cv2,
-use cv2.inRange() to make a mask
-use cv2.bitwise_and() to make masked image
-see ../sk8/visualcortex.py
-in matplotlib,  \\
-use imshow() twice, where second, top, image has alpha channel\\
-https://stackoverflow.com/questions/49025832/combine-picture-and-plot-with-matplotlib-with-alpha-channel \\
-ax.imshow(bottom, interpolation=None) \\
-ax.imshow(topimg, interpolation=None) # top image must have alpha channel  \\