LOAD EVERYTHING!!!!!!!

Author: methylDragon

01 OpenCV Basics and Image Processing.md

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+# OpenCV Python Optimisation Cheatsheet
+
+Author: methylDragon  
+Contains a syntax reference and code snippets for OpenCV for Python!  
+Note that this document is more or less based on the tutorials on https://docs.opencv.org    
+With some personal notes from me!    
+
+------
+
+## Pre-Requisites
+
+### Required
+
+- Python knowledge, this isn't a tutorial!
+- OpenCV installed
+
+
+
+## 1. Introduction
+
+Not much of an introduction here. OpenCV is just really great!
+
+Since this is a work in progress, it's not going to be very well organised.
+
+```python
+# These will have been assumed to have been run
+
+import cv2 as cv2, cv
+import numpy as np
+```
+
+If you need additional help or need a refresher on the parameters, feel free to use:
+
+```python
+help(cv.FUNCTION_YOU_NEED_HELP_WITH)
+```
+
+
+
+## 2. Optimisation
+
+### Enabling Optimisation
+
+```python
+cv.useOptimized() # Returns True if optimisation is enabled
+cv.setUseOptimized(True) # Set it to True
+```
+
+
+
+### Measuring Performance
+
+Timing your code is important!
+
+**Tick comparison**
+
+```python
+cv.getTickCount() # Current clock cycles
+cv.getTickFrequency() # Number of clock cycles per second
+
+# Example use
+e1 = cv.getTickCount()
+# your code execution
+e2 = cv.getTickCount()
+time = (e2 - e1)/ cv.getTickFrequency()
+```
+
+**Using Timeit**
+
+**Example**
+
+```python
+import timeit
+
+def performSearch(array):
+    array.sort()
+
+arrayTest = ["X"]*1000
+
+if __name__ == "__main__":
+    print(timeit.timeit("performSearch(arrayTest)",
+                        "from __main__ import performSearch, arrayTest",
+                        repeat=3,
+                        number=10))
+```
+
+
+
+### Cython
+
+- Cython code compiles to C, making it way faster than just pure Python code!
+- Install Cython with `pip install cython` or `conda install cython`
+
+**Note: Using Cython to optimise your OpenCV script will only work generally for the for loops, since the OpenCV Python API is actually a Python wrapper for already fairly optimised C++ code.**
+
+Ok!
+
+So.... You're going to need to check the Cython reference I made, or know how to use Cython. But generally...
+
+You need a
+
+**setup.py**
+
+```cython
+from distutils.core import setup
+from Cython.Build import cythonize
+
+setup(
+    ext_modules = cythonize('script_file.pyx'
+)
+```
+
+**script_file.pyx**
+
+```cython
+# Source: https://www.pyimagesearch.com/2017/08/28/fast-optimized-for-pixel-loops-with-opencv-and-python/
+
+import cython
+ 
+@cython.boundscheck(False)
+cpdef unsigned char[:, :] threshold_fast(int T, unsigned char [:, :] image):
+    # set the variable extension types
+    cdef int x, y, w, h
+    
+    # grab the image dimensions
+    h = image.shape[0]
+    w = image.shape[1]
+    
+    # loop over the image
+    for y in range(0, h):
+        for x in range(0, w):
+            # threshold the pixel
+            image[y, x] = 255 if image[y, x] >= T else 0
+    
+    # return the thresholded image
+    return image
+```
+
+And then compile it with
+
+```shell
+$ python3 setup.py build_ext --inplace
+```
+
+Then import it!
+
+```python
+from script_file import threshold_fast
+
+# Now you can use it!
+```
+
+
+
+```
+                            .     .
+                         .  |\-^-/|  .    
+                        /| } O.=.O { |\
+```
+
+
+
+------
+
+ [![Yeah! Buy the DRAGON a COFFEE!](assets/COFFEE%20BUTTON%20%E3%83%BE(%C2%B0%E2%88%87%C2%B0%5E).png)](https://www.buymeacoffee.com/methylDragon)
+

02 OpenCV Feature Detection and Description.md

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 # opencv-python-reference
 An (almost) fully comprehensive reference for OpenCV!
+
+**Comes with Code Snippets, Resources, Pictures (Some are animated), Explanations, Parameter Descriptions, and more!**
+
+---
+
+![Image result for opencv logo](assets/OpenCV_Logo_with_text.png)
+
+
+
+Sometimes it's just nice to have everything you need, all the bits and pieces of code all easily retrievable from a single source. It's like making lego bricks for your code!
+
+I found that this kind of pre-loading of all the retrieval work makes my workflow a lot more streamlined, and I save a lot of time for the time invested into preparing these references. It also makes it so that I'm forced to read through all the documentation and understand it.
+
+So, here's a reference that covers almost every function and functionality in OpenCV!
+
+**-CH3EERS**
+
+
+
+## Support my efforts!
+
+ [![Yeah! Buy the DRAGON a COFFEE!](assets/COFFEE%20BUTTON%20%E3%83%BE(%C2%B0%E2%88%87%C2%B0%5E).png)](https://www.buymeacoffee.com/methylDragon)
+
+[Or leave a tip! ヾ(°∇°*)](https://www.paypal.me/methylDragon)
+
+---
+
+## Reference Map
+
+1. **Basics and Image Processing**
+   - OpenCV Basic Commands
+     - Windows, Operations, Drawing, Interaction
+   - Basic Image Operations
+   - Basic Image Processing
+     - Transformations, Convolutions, Morphological Transformations,  Gradients, Pyramids
+   - Advanced Image Processing
+     - Canny, Histogram Equalisation, Hough Lines and Circles, Blob Detection, Denoising, Inpainting, Fourier, HDR, Template Matching, Watershed
+   - Contours
+   - Histograms
+   - Saliency API
+2. **Feature Detection and Description**
+   - Harris Corner
+   - Shi-Tomasi
+   - Key Points
+   - Keypoint Detectors
+     - FAST
+     - SIFT
+     - SURF
+     - BRIEF
+     - ORB
+     - Final Notes
+   - Feature Matching
+     - Brute Force
+     - FLANN
+     - Homography
+3. **Video and Image Analysis, and Object Tracking**
+   - Optical Flow
+     - Lucas-Kanade
+     - Dense
+   - Background Subtraction
+   - Camera Calibration
+     - Camera Properties
+     - Calibration
+     - Undistortion
+   - Pose Estimation
+   - Depth Map
+   - Meanshift
+   - Camshift
+   - Centroid Tracking
+   - Single and Multi-Object Tracking
+   - Single and Multi-Object Tracking with dlib (and Multiprocessing!)
+   - Footfall Tracking
+4. **Machine Learning and AI Detectors**
+   - k-Nearest Neighbours (With OCR example)
+   - K-Means Clustering (With Colour Quantisation example)
+   - Support Vector Machines (With OCR example)
+   - Non-maximum Suppression
+   - Haar Cascades
+   - Facial Landmarks with dlib
+   - Caffe Face Detection
+   - Loading Neural Nets with OpenCV
+   - YOLO
+   - Mask R-CNN
+   - Applications
+     - Face Recognition
+     - Facial Clustering
+5. **Optimisation**
+   - Enabling optimisation
+   - Measuring performance
+   - Cython
+
+
+
+## Credits
+
+All credits and sources are listed inside the tutorials and references themselves.
+
+
+
+```
+                            .     .
+                         .  |\-^-/|  .    
+                        /| } O.=.O { |\
+```

03 OpenCV Analysis and Object Tracking.md

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+HERE! https://pjreddie.com/darknet/yolo/

04 OpenCV Machine Learning and AI Detectors.md

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+person
+bicycle
+car
+motorbike
+aeroplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+backpack
+umbrella
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+sofa
+pottedplant
+bed
+diningtable
+toilet
+tvmonitor
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush