#-------------- ------------------ ------------------- --------------------- ---
#Numpy and OpenCV to create a PowerPoint like animation of image.  This is an
#example of BOX-appearance starting from centre of the image.  There are also 
#example of wiping an image from centre to edges and from Top - Left corner to
#the Bottom-Right corner. This code is good demonstration of slicing of arrays
#in NumPy along with use of numpy.insert and numpy.append operations. Creation
#of sub-matrix and cropping of an image while maitaining size same as input
#image can also be achieved with this piece of code.
#-------------- ------------------ ------------------- --------------------- ---
import numpy as np
import sys
import cv2

#-------------- ------------------ ------------------- --------------------- ---
def vidFromImgArray(imgArray, vidName, fps, vidW=0, vidH = 0):
	#Function to create an MP4 file from array of images
	#Image or video width should be even number else they would be truncated 
	#to the nearest lower even numbers
	if vidW == 0 or vidH == 0:
		ht, wd, ch = imgArray[0].shape
		size = (wd, ht)
	else:
		size = (vidW, vidH)
		
	codec = cv2.VideoWriter_fourcc(*'mp4v')
	video = cv2.VideoWriter(vidName, codec, fps, size)
	
	for img in imgArray:
		if vidW > 0 and vidH > 0:
			img=cv2.resize(img, size, interpolation=cv2.INTER_LINEAR)
		video.write(img)
	video.release()
#-------------- ------------------ ------------------- --------------------- ---

def imgAnimBoxEntrance(img):
	#Function to create box-shaped entrance of image from centre to edges
	frames = []
	#Works for coloured images with Alpha channel and grayscale (BW) images
	img = cv2.imread(img)
	h_half = img.shape[0]//2
	w_half = img.shape[1]//2
	even = img.shape[0] % 2
	arat = img.shape[1]/img.shape[0]
	
	#Check if image is colored with or without alpha layer
	if len(img.shape) > 2:
		ht, wd, ch = img.shape
		imgW = np.ones([ht, wd, ch], dtype=np.uint8) * 255
		
		for i in range(1, h_half, 1):
			j = int (i * arat)
			imgW[h_half-i:h_half+i, w_half-j:w_half+j, :] = 0
			cropImg = cv2.bitwise_or(img, imgW, mask=None)
			frames.append(cropImg)
			
	#Process image as Black-and-White pixels
	else:
		ht, wd = img. shape
		imgW = np.ones([ht, wd], dtype=np.uint8) * 255
		for i in range(1, h_half, 1):
			j = int(i * arat)
			imgW[h_half-i:h_half+i, w_half-j:w_half+j] = 0 
			cropImg = cv2.bitwise_or(img, imgW, mask = None)
			frames.append(cropImg)
	return frames
	#-------------- ------------------ ------------------- --------------------- ---

def imgAnimBoxEntranceEdge2Centre(img):
	#Function to create box-shaped entrance of image from edges to centre
	frames = []
	#Works for coloured images with Alpha channel and grayscale (BW) images
	img = cv2.imread(img)
	h_half = img.shape[0]//2
	w_half = img.shape[1]//2
	arat = img.shape[1]/img.shape[0]
	
	#Check if image is colored with or without alpha layer
	if len(img.shape) > 2:
		ht, wd, ch = img.shape
		imgW = np.ones([ht, wd, ch], dtype=np.uint8) * 255
		
		for i in range(1, ht, 1):
			j = int (i * arat)
			imgW[0:i, :, :] = 0
			imgW[:, 0:j, :] = 0
			imgW[ht-i:ht, :, :] = 0
			imgW[:, wd-j:wd, :] = 0
			cropImg = cv2.bitwise_or(img, imgW, mask=None)
			frames.append(cropImg)
			
	#Process image as Black-and-White pixels
	else:
		ht, wd = img. shape
		imgW = np.ones([ht, wd], dtype=np.uint8) * 255
		for i in range(1, h_half, 1):
			j = int(i * arat)
			imgW[0:i, :] = 0
			imgW[:, 0:j] = 0
			imgW[ht-i:ht, :] = 0
			imgW[:, wd-j:wd] = 0 
			cropImg = cv2.bitwise_or(img, imgW, mask = None)
			frames.append(cropImg)
	return frames
#-------------- ------------------ ------------------- --------------------- ---
#Function to (box shape) wipe out an image from centre towards edge 
def imgAnimBoxWipeOut(img):
	frames = []
	#Works for coloured images with Alpha channel and grayscale (BW) images
	img = cv2.imread(img)
	h_half = img.shape[0]//2
	w_half = img.shape[1]//2
	even = img.shape[0] % 2
	arat = img.shape[1]/img.shape[0]
	
	#Check if image is colored with or without alpha layer
	if len(img.shape) > 2:
		ht, wd, ch = img.shape
		imgW = np.ones([ht, wd, ch], dtype=np.uint8) * 255
		
		for i in range(1, h_half, 1):
			j = int (i * arat)
			imgW[h_half-i:h_half+i, w_half-j:w_half+j, :] = 0
			cropImg = cv2.bitwise_or(img, ~imgW, mask=None)
			frames.append(cropImg)
			
	#Process image as Black-and-White pixels
	else:
		ht, wd = img. shape
		imgW = np.ones([ht, wd], dtype=np.uint8) * 255
		for i in range(1, h_half, 1):
			j = int(i * arat)
			imgW[h_half-i:h_half+i, w_half-j:w_half+j] = 0 
			cropImg = cv2.bitwise_or(img, ~imgW, mask = None)
			frames.append(cropImg)
	return frames	

imgFrames0 = imgAnimBoxWipeOut("0.jpg")
imgFrames1 = imgAnimBoxEntranceEdge2Centre("1.jpg") 
imgFrames2 = imgAnimBoxEntrance("2.jpg")
imgFrames  = np.concatenate([imgFrames0, imgFrames1, imgFrames2])

vidFromImgArray(imgFrames, "BoxAnim.mp4", 50, 800, 450)