MicroManager images: Time lapse stitching by NumPy and Scipy

timelapse_stitching.py

# Make time lapse of stitched image.
# Uses Numpy, Scipy, and tifffile

import numpy as np  # numpy
import tifffile  # tifffile
import cv2  # opencv
from scipy.ndimage.interpolation import zoom  # scipy
import json

original_side = 1024
size = 128  # Side of one frame
folder = "/path/to/rootfolder/"
infolder = folder + 'path/to/subfolder'
outpath = "%sprocess/out.tiff" % (folder)

grid_x = 4
grid_y = 4
positions = [['2-Pos_%03d_%03d' % (x, y) for y in range(grid_y)] for x in range(grid_x)]


def read_metadata():
	d = {}
	imgs = []
	for y, row in enumerate(positions):
		for x, pos in enumerate(row):
			if not pos in d:
				d[pos] = {}
				path = infolder + pos + '/metadata.txt'
				with open(path, 'r') as f:
					obj = json.load(f)
					ks = obj.keys()
					for fr in ks:
						if fr != 'Summary':
							time = obj[fr]['ElapsedTime-ms']
							fr_idx = obj[fr]['FrameIndex']
							d[pos][fr_idx] = time
							imgpath = '%s%s/img_000%06d_RICM_000.tif' % (infolder, pos, fr_idx)
							imgs.append((imgpath, x, y, time))
	imgs = sorted(imgs, key=lambda a: a[3])
	return d, imgs


def stitch(ims, res, path, x, y, time):
	im = zoom(tifffile.imread(path), 1.0 * size / original_side)
	ims[y][x] = im
	yy = y * size
	xx = x * size
	res[yy:yy + size, xx:xx + size] = ims[y][x]
	font = cv2.FONT_HERSHEY_SIMPLEX
	res2 = np.copy(res)
	cv2.putText(res2, '%3d sec' % (round(1.0 * time / 1000)), (10, 40), font, 0.8, (255, 255, 255), 2)
	return res2


def main():
	max_process = 1000
	count = 0
	imgs = []
	ims = [[np.zeros((size, size), np.uint16)] * grid_x] * grid_y
	stitched = np.zeros((size * grid_y, size * grid_x), np.uint16)
	times, images = read_metadata()
	for path, x, y, time in images:
		count += 1
		if count > max_process:
			break
		print(count)
		imgs.append(stitch(ims, stitched, path, x, y, time))
	print('Writing at: %s' % (outpath))
	imgs = np.array(imgs)
	tifffile.imsave(outpath, imgs)


if __name__ == "__main__":
	main()