import cv2
import numpy
from matplotlib import pyplot as plt

#Define file path for input video
videoInputPath = r'E:\Footage\DJI_0001.MOV'

#Capture video and find frame count, frame rate, and time between frames.
cap = cv2.VideoCapture(videoInputPath)
frameCount = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
frameRate = cap.get(cv2.CAP_PROP_FPS)
timeBetweenFrames = 1000/frameRate
print(str(frameCount) + " frames total.")
print(str(frameRate) + " frames per second.")
print(str(timeBetweenFrames) + " ms per frame.")

#Loop for image processing video frames
#for i in range(0, frameCount):
for i in range(0, 1):

    #Read frames and convert to grayscale
    ret, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    pixelCount = gray.size
    print("Frame " + str(i) + " of " + str(frameCount - 1) + " has " + str(pixelCount) + " total pixels.")

    # Display histogram for image
    plt.hist(gray.ravel(), 256, [0, 256])
    plt.show()

    # Count how many pixels are at each intensity value
    histValues = [0] * 256
    for j in range(1, 255):
        pixelRange = cv2.inRange(gray, j, j)
        valueCount = cv2.countNonZero(pixelRange)

        #Assign the count for each pixel value to the index value that matches the pixel value
        histValues[j] = valueCount

        #Plot bar chart histogram
        plt.bar(j, valueCount)
    nonZeroPixels = numpy.sum(histValues)
    zeroPixels = pixelCount - nonZeroPixels
    histValues[0] = zeroPixels
    listLength = len(histValues)

    #Show bar chart histogram
    plt.show()

    #Plot and show the line chart histogram
    plt.plot(histValues)
    plt.show()

    #Find location of maximum value
    maxValue = float(numpy.max(histValues))
    maxValueIndex = int(numpy.argmax(histValues))

    print("Max value is " + str(maxValue) + " at pixel value " + str(maxValueIndex) + ".")

    print("Frames per second: " + str(frameRate))

#Close video
cap.release()