utilities.py

'''
	func initializer takes input from the GUI and saves them in variables for furthur use anywhere in the program
	func preview displays a preview of initial 50 frames to help cropping of rotating cell by the user
'''

import cv2
import os
import json
import imgpros
import cv2


'''defines variables for storing the inputs obtained from the user from the GUI'''
image = []
refPt = []
cropping = False
folder_path = ''
filename = ''
num_frames =0
meta=0
delay=0
outfilename = ''
out_folder = ''
time = 0
cell_name=''


def intializer(argv):
	'''
		Initializes the inputs taken from encrypt.py and stores them for furthur use
		Input: argv (input taken in command line from the user)
	'''

	global folder_path,filename,num_frames,meta,delay,outfilename,out_folder,time,cell_name			#defines global variables for furthur use
	folder_path = argv[1]		#folder path is taken from the user from command line
	print (folder_path)
	folder=folder_path.split("/")	#splits absolute folder path to separate folder path and file name
	a=0
	folder_path=""					#initializes folder path

	while a<(len(folder)-1):		#stores folder path from split name
		folder_path += folder[a]
		folder_path += "/"
		a=a+1
	filename= folder[a]				#stores file name
	tuta = folder_path.split('/')	#stores split folder path
	cell_name = tuta[len(tuta) - 2]	#defining variable cell_name
	out_folder = folder_path + cell_name +  "_out/"
	global num_frames				#defining global variable num_frames to define number of frames for image analysis
	num_frames = argv[2]			#number of frames is input from user
	num_frames = int(num_frames)	#coverting variable to int

	if not os.path.isdir(out_folder):
		print ('creating new directory')
		os.makedirs(out_folder)		#creates new folder with name out_folder to save output data
	outfilename = "raw_data.csv"	#defining output file name for storing csv data

	meta = int(argv[3])
	if meta == 1:					#takes metadata from folder and changes file name to specified format
		fd1 = 'FrameKey-'
		fd2 = '-0-0'
		print (fd1 + str(num_frames - 1) + fd2)
		with open(folder_path + '/metadata.txt') as f:
			data = json.load(f)
		time = (data[fd1 + str(num_frames - 1) + fd2]['ElapsedTime-ms'] - data[fd1 + '0' + fd2]['ElapsedTime-ms']) / num_frames
	else:							#takes file name as per obtained filename convention
		fps = argv[4]				#fps is input from user
		fps = int(fps)
		# int(raw_input('Enter FPS: '))
		time = 1.0 / float(fps)		#time inteval b/w 2 frames equals to inverse of the user-specified fps
	print ('time between frames ' + str(time))

	delay = argv[5]					#time difference to be taken between adjacent frames to be displayed to user in GUI
	delay = int(delay)				#takes values from 1-100 with 100 bring slowest and 1 being fastest



def preview():
	'''
	Displays a preview of initial 50 frames to help cropping of rotating cell by the user
	'''
	global meta,filename,folder_path,delay		#defining global variables
	addr = folder_path + '/img_000000'			
	ad = '_Default_000.tif'
	frame = addr + '000' + ad
	if meta == 0:								#preview preferences if no metadata is present
		frame = cv2.imread(folder_path + filename)	#reads image from folder and stores it as a frame
	else:										#preview preferences if metadata is present
		frame = cv2.imread(addr+ '000'+ad)		#preview preferences if metadata is present
	print ('\nPreviewing.....\n')
	count = 0
	while (count<50):							#loop for limiting number of frames to be previewed to 50
		if meta == 0:							#case when metadata is not present
			print (count)
			print (filename)
			print (folder_path + filename.replace("00000",str("%05d" % count)))
			frame = cv2.imread(folder_path + filename.replace("00000",str("%05d" % count)))		#processes 1 frame
		else:									#case when metadata is present
			frame = cv2.imread(addr+ str("%03d" % count)+ad)
		image = imgpros.threshold(frame)		#thresholds the image before displaying it. Explained in imgpros file
		cv2.imshow('image',image)
		cv2.waitKey(delay)						#imparts delay in displaying frames in GUI
		count+=1								#increases count

'''
def click_and_crop(event, x, y, flags, param):
	# grab references to the global variables
	global refPt, cropping,image
	# if the left mouse button was clicked, record the starting
	# (x, y) coordinates and indicate that cropping is being
	# performed
	if event == cv2.EVENT_LBUTTONDOWN:
		refPt = [(x, y)]
		cropping = True

	# check to see if the left mouse button was released
	elif event == cv2.EVENT_LBUTTONUP:
		# record the ending (x, y) coordinates and indicate that
		# the cropping operation is finished
		refPt.append((x, y))
		cropping = False

		# draw a rectangle around the region of interest
		cv2.rectangle(image, refPt[0], refPt[1], (0, 255, 0), 2)
		cv2.imshow("image", image)

def crop(meta,filename,folder_path):
	global image		
	addr = folder_path + '/img_000000'
	ad = '_Default_000.tif'
	print ('crop cell for analysis.....')
	print ('Press c to proceed after cropping')
	print ('Press r to redo')
	if meta == 1:
		frame = addr + '000' + ad
	else:
		frame = folder_path + filename
	# load the image, clone it, and setup the mouse callback function
	image = cv2.imread(frame)
	image = threshold.threshold(image)
	clone = image.copy()
	cv2.namedWindow("image")
	cv2.setMouseCallback("image", click_and_crop)

	# keep looping until the 'q' key is pressed
	while True:
		# display the image and wait for a keypress
		cv2.imshow("image", image)
		key = cv2.waitKey(1) & 0xFF

		# if the 'r' key is pressed, reset the cropping region
		if key == ord("r"):
			image = clone.copy()

		# if the 'c' key is pressed, break from the loop
		elif key == ord("c"):
			break

	# if there are two reference points, then crop the region of interest
	# from teh image and display it

	# close all open windows
	cv2.destroyAllWindows()

	a = image[refPt[0][1]:refPt[1][1], refPt[0][0]:refPt[1][0]]
	trace = numpy.zeros((a.shape[0],a.shape[1]), numpy.uint8)
	return refPt,trace
'''