Python + OpenCV: generate Histograms of images

Python + OpenCv example run on Raspberry Pi 2 to generate Histograms of images, pyHist.py

from PIL import Image
import numpy as np
from matplotlib import pyplot as plt
import cv2

img = Image.open('photo.jpg')
#img = Image.open('b.png')
imgArr = np.asarray(img)

plt.subplot(221), plt.imshow(img)

color = ('r','g','b')
for i,col in enumerate(color):
    histr = cv2.calcHist([imgArr],[i],None,[256],[0,256])
    plt.subplot(222), plt.plot(histr,color = col)
    plt.xlim([0,256])

plt.xlim([0,256])

plt.show()

Reference: http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_histograms/py_histogram_begins/py_histogram_begins.html

Python + OpenCV: convert RGB to HSV and reverse

Python + OpenCV example run on Raspberry Pi 2 to convert RGB to HSV and reverse from HSV to RGB, pyCV_cvtImage.py.

import sys
import cv2

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)

#img1 and img2 must be in same size
img1 = cv2.imread('Raspberry_Pi_Logo.png', 1)
hsv1 = cv2.cvtColor(img1, cv2.COLOR_RGB2HSV)
h,s,v = cv2.split(hsv1)
hsv2 = cv2.merge((h,s,v))
img2 = cv2.cvtColor(hsv2, cv2.COLOR_HSV2RGB)

cv2.imshow('img1',img1)
cv2.imshow('hsv1',hsv1)
cv2.imshow('h', h)
cv2.imshow('s', s)
cv2.imshow('v', v)
cv2.imshow('hsv2',hsv2)
cv2.imshow('img2',img2)

cv2.waitKey(0)
cv2.destroyAllWindow()

Python + OpenCV: create negative image

Example to generate negative image:

import sys
import cv2

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)

#img1 and img2 must be in same size
img1 = cv2.imread('Raspberry_Pi_Logo.png', 1)
img2 = (255-img1)

cv2.imshow('img1',img1)
cv2.imshow('img2',img2)

cv2.waitKey(0)
cv2.destroyAllWindow()

---

Edit the example "Capture Raspberry Pi Camera image, display on OpenCV, Matplotlib PyPlot and Tkinter GUI" to generate negative image from the picamera captured image.

import picamera
import picamera.array
import time
import cv2
from matplotlib import pyplot as plt
import Tkinter 
import Image, ImageTk
import sys

def capturePiCam():
    with picamera.PiCamera() as camera:
        cap=picamera.array.PiRGBArray(camera)
        camera.resolution = (640, 480)
        camera.start_preview()
        time.sleep(3)
        camera.capture(cap,format="bgr")
        global img
        img =cap.array
        img = (255-img)

#- display on OpenCV window -
def displayAtOpenCV():
    cv2.namedWindow('imageWindow', cv2.WINDOW_AUTOSIZE)
    cv2.imshow('imageWindow',img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

#- display with matplotlib -
def displayAtPyplot():
    plt.figure().canvas.set_window_title("Hello Raspberry Pi")
    plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
    plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
    plt.show()
    
#- display on Tkinter -
def displayAtThinter():
    root = Tkinter.Tk() 
    b,g,r = cv2.split(img) 
    img2 = cv2.merge((r,g,b))
    img2FromArray = Image.fromarray(img2)
    imgtk = ImageTk.PhotoImage(image=img2FromArray) 
    Tkinter.Label(root, image=imgtk).pack() 
    root.mainloop()

def displayUsage():
    print("usage: ")
    print("python pyCV_picam.py 1 - display wiyh OpenCV window")
    print("python pyCV_picam.py 2 - display with matplotlib")
    print("python pyCV_picam.py 3 - display with Tkinter")

if len(sys.argv) != 2:
    displayUsage()
    sys.exit()
    
opt = sys.argv[1]

if opt=="1":
    print("display wiyh OpenCV window")
    capturePiCam()
    displayAtOpenCV()
elif opt=="2":
    print("display with matplotlib")
    capturePiCam()
    displayAtPyplot()
elif opt=="3":
    print("display with Tkinter")
    capturePiCam()
    displayAtThinter()
else:
    displayUsage()

Python + OpenCV: split and merge - to exchange color channel

Example to use OpenCV split() and merge() to separate color channel, and re-construct image with red and blue color channel exchanged.

import sys
import cv2

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)

#img1 and img2 must be in same size
img1 = cv2.imread('Raspberry_Pi_Logo.png', 1)
b,g,r = cv2.split(img1)
img2 = cv2.merge((r,g,b))

cv2.imshow('img1',img1)
cv2.imshow('img2',img2)
cv2.imshow('r', r)
cv2.imshow('g', g)
cv2.imshow('b', b)
cv2.waitKey(0)
cv2.destroyAllWindow()

Python + OpenCV: Arithmetic Operations on Images - add(), addWeighted() and subtract()

import sys
import cv2
import numpy
import urllib

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)
print("numpy version: " + numpy.__version__)
print("urllib version: " + urllib.__version__)

#img1 and img2 must be in same size
img1 = cv2.imread('Raspberry_Pi_Logo.png', 1)
img2 = cv2.imread('opencv-logo-white.png', 1)
imgAdd = cv2.add(img1, img2)
imgAddWeighted = cv2.addWeighted(img1, 0.7, img2, 0.3, 0)
imgSub = cv2.subtract(img1, img2)

cv2.imshow('img1',img1)
cv2.imshow('img2',img2)
cv2.imshow('imgAdd',imgAdd)
cv2.imshow('imgAddWeighted',imgAddWeighted)
cv2.imshow('imgSub',imgSub)
cv2.waitKey(0)
cv2.destroyAllWindow()

Reference: http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_core/py_image_arithmetics/py_image_arithmetics.html

Python/OpenCV, get image properties - number of row, column, color channel

import sys
import cv2
import numpy
import urllib

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)
print("numpy version: " + numpy.__version__)
print("urllib version: " + urllib.__version__)

url = 'http://goo.gl/41cgQr'
data = urllib.urlopen(url)
img = numpy.asarray(bytearray(data.read()), dtype='uint8')
img = cv2.imdecode(img, cv2.IMREAD_COLOR)

print("")
print "image info"
print "#row #column #channel"
print img.shape
print "#row * #column * #channel"
print img.size

cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyWindow('image')

Capture Raspberry Pi Camera image, display on OpenCV, Matplotlib PyPlot and Tkinter GUI

This example capture photo from Raspberry Pi Camera Module, and display with OpenCV, Matplotlib PyPlot and Tkinter GUI.


usage:
python pyCV_picam.py 1 - display wiyh OpenCV window
python pyCV_picam.py 2 - display with matplotlib
python pyCV_picam.py 3 - display with Tkinter

import picamera
import picamera.array
import time
import cv2
from matplotlib import pyplot as plt
import Tkinter 
import Image, ImageTk
import sys

def capturePiCam():
    with picamera.PiCamera() as camera:
        cap=picamera.array.PiRGBArray(camera)
        camera.resolution = (640, 480)
        camera.start_preview()
        time.sleep(3)
        camera.capture(cap,format="bgr")
        global img
        img =cap.array

#- display on OpenCV window -
def displayAtOpenCV():
    cv2.namedWindow('imageWindow', cv2.WINDOW_AUTOSIZE)
    cv2.imshow('imageWindow',img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

#- display with matplotlib -
def displayAtPyplot():
    plt.figure().canvas.set_window_title("Hello Raspberry Pi")
    plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
    plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
    plt.show()
    
#- display on Tkinter -
def displayAtThinter():
    root = Tkinter.Tk() 
    b,g,r = cv2.split(img) 
    img2 = cv2.merge((r,g,b))
    img2FromArray = Image.fromarray(img2)
    imgtk = ImageTk.PhotoImage(image=img2FromArray) 
    Tkinter.Label(root, image=imgtk).pack() 
    root.mainloop()

def displayUsage():
    print("usage: ")
    print("python pyCV_picam.py 1 - display wiyh OpenCV window")
    print("python pyCV_picam.py 2 - display with matplotlib")
    print("python pyCV_picam.py 3 - display with Tkinter")

if len(sys.argv) != 2:
    displayUsage()
    sys.exit()
    
opt = sys.argv[1]

if opt=="1":
    print("display wiyh OpenCV window")
    capturePiCam()
    displayAtOpenCV()
elif opt=="2":
    print("display with matplotlib")
    capturePiCam()
    displayAtPyplot()
elif opt=="3":
    print("display with Tkinter")
    capturePiCam()
    displayAtThinter()
else:
    displayUsage()
    

---

To use ImageTk in your python, refer to "Install PIL (with jpg supported) and ImageTk on Raspberry Pi/Raspbian".

Python capture picamera image, display on OpenCV and matplotlib

Python example to capture image from Raspberry Pi Camera Module with picamera, display on OpenCV and matplotlib.

This demo run on Windows log-in Raspberry Pi 2/Raspbian remotely, so the preview will not shown.

pyCV_picam.py

import picamera
import picamera.array
import time
import cv2
from matplotlib import pyplot as plt

with picamera.PiCamera() as camera:
    cap=picamera.array.PiRGBArray(camera)
    camera.resolution = (640, 480)
    camera.start_preview()
    time.sleep(3)
    camera.capture(cap,format="bgr")
    img=cap.array
    
#- display on OpenCV window -
cv2.namedWindow('imageWindow', cv2.WINDOW_AUTOSIZE)
cv2.imshow('imageWindow',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

#- display with matplotlib
#plt.figure().canvas.set_window_title("Hello Raspberry Pi")
#plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
#plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
#plt.show()

---

more:
~ Display on Tkinter GUI also.

Raspberry Pi + Python/OpenCV, draw something on OpenCV image

Example to draw something on OpenCV image.

pyCV_draw.py

import platform
import os
import sys
import cv2
import numpy
import urllib
import matplotlib
from matplotlib import pyplot as plt

print platform.system(), platform.release(), platform.dist()
print os.uname()
print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)
print("numpy version: " + numpy.__version__)
print("urllib version: " + urllib.__version__)
print("matplotlib version: " + matplotlib.__version__)

#- load image from local file
#img = cv2.imread('test.png', cv2.IMREAD_UNCHANGED)

#- load image from internet
url = 'http://goo.gl/41cgQr'
data = urllib.urlopen(url)
img = numpy.asarray(bytearray(data.read()), dtype='uint8')
img = cv2.imdecode(img, cv2.IMREAD_COLOR)

#draw something
#ref: 
#http://docs.opencv.org/master/dc/da5/tutorial_py_drawing_functions.html
cv2.line(img,(0,0),(511,511),(255,0,0),5)
cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
cv2.circle(img,(447,63), 63, (0,0,255), -1)
cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
pts = numpy.array([[10,5],[20,30],[70,20],[50,10]], numpy.int32)
pts = pts.reshape((-1,1,2))
cv2.polylines(img,[pts],True,(0,255,255))
font = cv2.FONT_HERSHEY_SIMPLEX
# AttributeError: 'module' object has no attribute 'LINE_AA'
# to solve it, change 'LINE_AA' to 'CV_AA'
#cv2.putText(img,'OpenCV',(10,500), font, 4,(255,255,255),2,cv2.LINE_AA)
cv2.putText(img,'OpenCV',(10,500), font, 4,(255,255,255),2,cv2.CV_AA)

#- display on OpenCV window -
#cv2.namedWindow('imageWindow', cv2.WINDOW_AUTOSIZE)
#cv2.imshow('imageWindow', img)
#cv2.waitKey(0)
#cv2.destroyWindow('imageWindow')

#sys.exit()

#- display with matplotlib
#set window title of matplotlib plt
plt.figure().canvas.set_window_title("Hello Raspberry Pi") 
#-- incorrect color
#plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')
#-- correct color with cv2.cvtColor()
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
plt.title("Hello Raspberry Pi")
plt.suptitle("http://helloraspberrypi.blogspot.com/")

plt.show()

Raspberry Pi + Python/OpenCV, display image on matplotlib pyplot

With OpenCV image displayed using matplotlib pyplot, we can resize the window, also save the image on storage. This Python example run on Raspberry Pi 2, show how to load JPG image from internet, display on pyplot, save to local storage in PNG format, then open and display the saved local image.

import platform
import os
import sys
import cv2
import numpy
import urllib
import matplotlib
from matplotlib import pyplot as plt

print platform.system(), platform.release(), platform.dist()
print os.uname()
print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)
print("numpy version: " + numpy.__version__)
print("urllib version: " + urllib.__version__)
print("matplotlib version: " + matplotlib.__version__)

#- load image from local file
#img = cv2.imread('test.png', cv2.IMREAD_UNCHANGED)

#- load image from internet
url = 'http://goo.gl/41cgQr'
data = urllib.urlopen(url)
img = numpy.asarray(bytearray(data.read()), dtype='uint8')
img = cv2.imdecode(img, cv2.IMREAD_COLOR)

#- display on OpenCV window -
#cv2.namedWindow('imageWindow', cv2.WINDOW_AUTOSIZE)
#cv2.imshow('imageWindow', img)
#cv2.waitKey(0)
#cv2.destroyWindow('imageWindow')

#- display with matplotlib
#set window title of matplotlib plt
plt.figure().canvas.set_window_title("Hello Raspberry Pi") 
#-- incorrect color
#plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')
#-- correct color with cv2.cvtColor()
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
plt.title("Hello Raspberry Pi")
plt.suptitle("http://helloraspberrypi.blogspot.com/")

plt.show()

~ To use matplotlib with Python 2 on Raspberry Pi, refer "Install numpy, matplotlib and drawnow for Python 2".

Raspberry Pi + Python/OpenCV, show image in window

To creates window in Python/OpenCV, call:

cv2.namedWindow('imageWindow', cv2.WINDOW_AUTOSIZE)

Here is a Python example using OpenCV to load image from internet, display in window.

import sys
import cv2
import numpy
import urllib

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)
print("numpy version: " + numpy.__version__)
print("urllib version: " + urllib.__version__)

url = 'http://goo.gl/41cgQr'
data = urllib.urlopen(url)
img = numpy.asarray(bytearray(data.read()), dtype='uint8')
img = cv2.imdecode(img, cv2.IMREAD_COLOR)
cv2.namedWindow('imageWindow', cv2.WINDOW_AUTOSIZE)
cv2.imshow('imageWindow', img)
cv2.waitKey(0)
cv2.destroyWindow('imageWindow')

Raspberry Pi + Python/OpenCV, load image from internet

Python example on Raspberry Pi to load image from internet, using OpenCV:

import sys
import cv2
import numpy
import urllib

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)
print("numpy version: " + numpy.__version__)
print("urllib version: " + urllib.__version__)

url = 'http://goo.gl/41cgQr'
data = urllib.urlopen(url)
img = numpy.asarray(bytearray(data.read()), dtype='uint8')
img = cv2.imdecode(img, cv2.IMREAD_COLOR)
cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyWindow('image')

Raspberry Pi + Python/OpenCV, load and display image

Example of Python run on Raspberry Pi 2 to load and display image using OpenCV 2:

import sys
import cv2

print("Python version: \n" + sys.version)
print("cv2 version: " + cv2.__version__)

img = cv2.imread('smallRPi.JPG', cv2.IMREAD_UNCHANGED)
cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyWindow('image')

Install OpenCV 2 on Raspberry Pi/Python 2

To install OpenCV 2 on Raspberry Pi, Python 2, enter the command in LXTerminal:
$ sudo apt-get install python-opencv