formatting

fromgilbert · fromgilbert · commit 542c05bd0f13 · 2017-11-29T15:45:56.000-07:00
diff --git a/examples/motion-heatmap/README.md b/examples/motion-heatmap/README.md
@@ -27,16 +27,16 @@ pip install opencv-contrib-python
 Code is included in this folder of the repository in the .py file.
 
 ## How it works
-The main APIs used in OpenCV are:
-MOG background subtractor (cv2.bgsegm.createBackgroundSubtractorMOG()) - https://docs.opencv.org/3.0-beta/modules/video/doc/motion_analysis_and_object_tracking.html?highlight=createbackgroundsubtractormog#createbackgroundsubtractormog  
+The main APIs used in OpenCV are:  
+* MOG background subtractor (cv2.bgsegm.createBackgroundSubtractorMOG()) - https://docs.opencv.org/3.0-beta/modules/video/doc/motion_analysis_and_object_tracking.html?highlight=createbackgroundsubtractormog#createbackgroundsubtractormog  
 Note: the docs are out of date, and the propoer way to initialize is  
 ```
 cv2.bgsegm.createBackgroundSubtractorMOG()
 ```
-cv2.threshold() - https://docs.opencv.org/3.3.1/d7/d4d/tutorial_py_thresholding.html   
-cv2.add() - https://docs.opencv.org/3.2.0/d0/d86/tutorial_py_image_arithmetics.html  
-cv2.applyColorMap() - https://docs.opencv.org/3.0-beta/modules/imgproc/doc/colormaps.html   
-cv2.addWeighted() - https://docs.opencv.org/3.2.0/d0/d86/tutorial_py_image_arithmetics.html  
+* cv2.threshold() - https://docs.opencv.org/3.3.1/d7/d4d/tutorial_py_thresholding.html   
+* cv2.add() - https://docs.opencv.org/3.2.0/d0/d86/tutorial_py_image_arithmetics.html  
+* cv2.applyColorMap() - https://docs.opencv.org/3.0-beta/modules/imgproc/doc/colormaps.html   
+* cv2.addWeighted() - https://docs.opencv.org/3.2.0/d0/d86/tutorial_py_image_arithmetics.html  
 
 The application takes each frame and first applies background subtraction using the cv2.bgsegm.createBackgroundSubtractorMOG() object to create a mask.  A threshold is then applied to the mask to remove small amounts of movement, and also to set the accumulation value for each iteration.  The result of the threshold is added to an accumulation image (one that starts out at all zero and gets added to each iteration without removing anything), which is what records the motion.  At the very end, a color map is applied to the accumulated image so it's easier to see the motion.  This colored imaged is then combined with a copy of the first frame using cv2.addWeighted to accomplish the overlay.
 
