added in a calibration tiff splitter for Windows

.gitignore

@@ -1,2 +1,3 @@
 logfile.txt
 -logfile.txt
+test.ipynb

gonet-v2-win-calibration-tff.py

@@ -0,0 +1,86 @@
+#!/usr/bin/env python
+import numpy as np
+from tifffile import tifffile
+from PIL import Image
+import sys
+# import re
+import os
+
+"""
+    Based on th Original file located at
+    https://colab.research.google.com/drive/1tCvs7-J3Z6l_WhY5DjnFxnGBEARXPv5p
+
+    This has been updated to run under Windows following the GONet Downloader Utility
+    It will carry over the %USERPROFILE% and %folder% vars from the batch file
+
+"""
+
+folder = os.environ.get('folder')
+userprofile = os.environ.get('USERPROFILE')
+print(f"Destination Folder is:: {folder}")
+
+out_dir = (f'{userprofile}\\{folder}\\tiffs\\')
+# jpeg_out_dir = (f'{userprofile}\\{folder}\\jpegs\\')
+in_dir = (f'{userprofile}\\{folder}\\')
+
+
+## Isolate the files to only those larger than 4MB
+file_list = [fn for fn in os.listdir(in_dir) if not None]
+file_list = [fn for fn in file_list if os.stat(in_dir+"/"+fn).st_size > 4000000] ## only images that aren't small
+file_list = sorted([fn for fn in file_list if (fn[-4:]==".jpg")]) ## only raw jpg images
+print(len(file_list))
+
+if not os.path.exists(out_dir):
+    os.makedirs(out_dir)
+
+files_converted = 0
+for fn in file_list:
+    imageInFileName=in_dir+"/"+fn
+    imageOutFileName=out_dir + fn.rsplit('.',1)[0]+'.tiff'
+    # imageOutJpg = jpeg_out_dir + fn.rsplit('.',1)[0]+'.jpeg'
+
+    file = open(imageInFileName, "rb")
+    rawFileOffset = 18711040
+    rawHeaderSize = 32768
+    rawDataOffset = rawFileOffset - rawHeaderSize
+    RELATIVETOEND = 2
+
+    file.seek(-rawDataOffset,RELATIVETOEND)
+    pixelsPerLine=4056
+    pixelsPerColumn=3040
+    usedLineBytes=int(pixelsPerLine*12/8)
+
+    s=np.zeros((pixelsPerLine,pixelsPerColumn),dtype='uint16')
+    # do this at least 3040 times though the precise number of lines is a bit unclear
+    for i in range(pixelsPerColumn):
+
+        # read in 6112 bytes, but only 6084 will be used
+        bdLine = file.read(6112)
+        gg=np.array(list(bdLine[0:usedLineBytes]),dtype='uint16')
+        s[0::2,i] = (gg[0::3]<<4) + (gg[2::3]&15)
+        s[1::2,i] = (gg[1::3]<<4) + (gg[2::3]>>4)
+
+    # form superpixel array
+    sp=np.zeros((int(pixelsPerLine/2),int(pixelsPerColumn/2),3),dtype='uint16')
+    sp[:,:,0]=s[1::2,1::2]                      # red
+    sp[:,:,1]=(s[0::2,1::2]+s[1::2,0::2])/2     # green
+    sp[:,:,2]=s[0::2,0::2]                      # blue
+    sp = np.multiply(sp,16) ## adjusting the image to be saturated correctly(it was imported from 12bit into a 16bit) so it is a factor of 16 dimmer than should be, i.e this conversion
+
+    sp=sp.transpose()
+
+    # now we need to write it to a tiff file
+    array = ((sp+0.5).astype('uint16'))
+    tifffile.imwrite(imageOutFileName, array, photometric='rgb')
+
+    # # Now make the JPG --- not needed in Calibration so removed
+    # jpeg = Image.open(imageInFileName).convert("RGB")
+    # # exif = jpeg.info['exif']
+    # # print('EXIF saved on JPEG')
+    # jpeg.save((imageOutJpg), 'JPEG')
+
+
+    ## to be able to keep track of progress
+    files_converted += 1
+    if files_converted % 10 == 0:
+        print(f'Files Converted:: {files_converted}')