diff --git a/pdf_table_extraction_and_ocr.org b/pdf_table_extraction_and_ocr.org
index 327e867..52d01e6 100644
--- a/pdf_table_extraction_and_ocr.org
+++ b/pdf_table_extraction_and_ocr.org
@@ -965,11 +965,35 @@ print("\n".join(paths))
 **** table_ocr/ocr_image/__init__.py
 #+BEGIN_SRC python :tangle table_ocr/ocr_image/__init__.py
 import math
+import os
 
 import cv2
 import numpy as np
 import pytesseract
 
+def main(image_file, tess_args):
+    """
+    OCR the image and output the text to a file with an extension that is ready
+    to be used in Tesseract training (.gt.txt).
+
+    Tries to crop the image so that only the relevant text gets passed to Tesseract.
+
+    Returns the name of the text file that contains the text.
+    """
+    directory, filename = os.path.split(image_file)
+    filename_sans_ext, ext = os.path.splitext(filename)
+    image = cv2.imread(image_file, cv2.IMREAD_GRAYSCALE)
+    cropped = crop_to_text(image)
+    ocr_data_dir = os.path.join(directory, "ocr_data")
+    os.makedirs(ocr_data_dir, exist_ok=True)
+    out_imagepath = os.path.join(ocr_data_dir, filename)
+    out_txtpath = os.path.join(ocr_data_dir, "{}.gt.txt".format(filename_sans_ext))
+    cv2.imwrite(out_imagepath, cropped)
+    txt = ocr_image(cropped, " ".join(tess_args))
+    with open(out_txtpath, "w") as txt_file:
+        txt_file.write(txt)
+    return out_txtpath
+
 <<crop-to-text>>
 <<ocr-image>>
 #+END_SRC
@@ -982,13 +1006,8 @@ https://github.com/tesseract-ocr/tesstrain.
 
 #+BEGIN_SRC python :tangle table_ocr/ocr_image/__main__.py :mkdirp yes :results none
 import argparse
-import math
-import os
-import sys
 
-import cv2
-
-from table_ocr.ocr_image import crop_to_text, ocr_image
+from table_ocr.ocr_image import main
 
 description="""Takes a single argument that is the image to OCR.
 Remaining arguments are passed directly to Tesseract.
@@ -999,24 +1018,8 @@ Filenames are of the format for training with tesstrain."""
 parser = argparse.ArgumentParser(description=description)
 parser.add_argument("image", help="filepath of image to perform OCR")
 
-def main(image_file, tess_args):
-    directory, filename = os.path.split(image_file)
-    filename_sans_ext, ext = os.path.splitext(filename)
-    image = cv2.imread(image_file, cv2.IMREAD_GRAYSCALE)
-    cropped = crop_to_text(image)
-    ocr_data_dir = os.path.join(directory, "ocr_data")
-    os.makedirs(ocr_data_dir, exist_ok=True)
-    out_imagepath = os.path.join(ocr_data_dir, filename)
-    out_txtpath = os.path.join(ocr_data_dir, "{}.gt.txt".format(filename_sans_ext))
-    cv2.imwrite(out_imagepath, cropped)
-    txt = ocr_image(cropped, " ".join(tess_args))
-    print(txt)
-    with open(out_txtpath, "w") as txt_file:
-        txt_file.write(txt)
-
-if __name__ == "__main__":
-    args, tess_args = parser.parse_known_args()
-    main(args.image, tess_args)
+args, tess_args = parser.parse_known_args()
+print(main(args.image, tess_args))
 #+END_SRC
 *** table_ocr/ocr_to_csv/
 **** table_ocr/ocr_to_csv/__init__.py
diff --git a/table_ocr/ocr_image/__init__.py b/table_ocr/ocr_image/__init__.py
index 526202c..e952522 100644
--- a/table_ocr/ocr_image/__init__.py
+++ b/table_ocr/ocr_image/__init__.py
@@ -1,9 +1,33 @@
 import math
+import os
 
 import cv2
 import numpy as np
 import pytesseract
 
+def main(image_file, tess_args):
+    """
+    OCR the image and output the text to a file with an extension that is ready
+    to be used in Tesseract training (.gt.txt).
+
+    Tries to crop the image so that only the relevant text gets passed to Tesseract.
+
+    Returns the name of the text file that contains the text.
+    """
+    directory, filename = os.path.split(image_file)
+    filename_sans_ext, ext = os.path.splitext(filename)
+    image = cv2.imread(image_file, cv2.IMREAD_GRAYSCALE)
+    cropped = crop_to_text(image)
+    ocr_data_dir = os.path.join(directory, "ocr_data")
+    os.makedirs(ocr_data_dir, exist_ok=True)
+    out_imagepath = os.path.join(ocr_data_dir, filename)
+    out_txtpath = os.path.join(ocr_data_dir, "{}.gt.txt".format(filename_sans_ext))
+    cv2.imwrite(out_imagepath, cropped)
+    txt = ocr_image(cropped, " ".join(tess_args))
+    with open(out_txtpath, "w") as txt_file:
+        txt_file.write(txt)
+    return out_txtpath
+
 def crop_to_text(image):
     MAX_COLOR_VAL = 255
     BLOCK_SIZE = 15
diff --git a/table_ocr/ocr_image/__main__.py b/table_ocr/ocr_image/__main__.py
index f849b53..67dd4c2 100644
--- a/table_ocr/ocr_image/__main__.py
+++ b/table_ocr/ocr_image/__main__.py
@@ -1,11 +1,6 @@
 import argparse
-import math
-import os
-import sys
 
-import cv2
-
-from table_ocr.ocr_image import crop_to_text, ocr_image
+from table_ocr.ocr_image import main
 
 description="""Takes a single argument that is the image to OCR.
 Remaining arguments are passed directly to Tesseract.
@@ -16,21 +11,5 @@ Filenames are of the format for training with tesstrain."""
 parser = argparse.ArgumentParser(description=description)
 parser.add_argument("image", help="filepath of image to perform OCR")
 
-def main(image_file, tess_args):
-    directory, filename = os.path.split(image_file)
-    filename_sans_ext, ext = os.path.splitext(filename)
-    image = cv2.imread(image_file, cv2.IMREAD_GRAYSCALE)
-    cropped = crop_to_text(image)
-    ocr_data_dir = os.path.join(directory, "ocr_data")
-    os.makedirs(ocr_data_dir, exist_ok=True)
-    out_imagepath = os.path.join(ocr_data_dir, filename)
-    out_txtpath = os.path.join(ocr_data_dir, "{}.gt.txt".format(filename_sans_ext))
-    cv2.imwrite(out_imagepath, cropped)
-    txt = ocr_image(cropped, " ".join(tess_args))
-    print(txt)
-    with open(out_txtpath, "w") as txt_file:
-        txt_file.write(txt)
-
-if __name__ == "__main__":
-    args, tess_args = parser.parse_known_args()
-    main(args.image, tess_args)
+args, tess_args = parser.parse_known_args()
+print(main(args.image, tess_args))