remove delimiter char option

extra/README.md

@@ -19,6 +19,16 @@
     1) Insert result json files into **predicted/**
     2) Run the python script: `python convert_pred_darkflow_json.py`
 
+## Remove specific char delimiter from files
+
+E.g. from:
+`<class_name>;<left>;<top>;<right>;<bottom>`
+to:
+`<class_name> <left> <top> <right> <bottom>`
+
+In the case you have the `--ground-truth` or `--predicted` files in the right format but with a specific char being used as a delimiter (e.g. `";"`), you can remove it by running:
+`python remove_delimiter_char.py --char ";" --ground-truth`
+
 ## Find the files that contain a specific class of objects
 
 1) Run the python script and specify the **class** as argument, e.g.

extra/remove_delimiter_char.py

@@ -0,0 +1,61 @@
+import glob
+import os
+import sys
+import argparse
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument('-c', '--char', required=True, type=str, help='specific character to be removed (e.g. ";").')
+# mutually exclusive arguments (can't select both)
+group = parser.add_mutually_exclusive_group(required=True)
+group.add_argument('-g', '--ground-truth', help="if to remove that char from the ground-truth files.", action="store_true")
+group.add_argument('-p', '--predicted', help="if to remove that char from the predicted objects files.", action="store_true")
+args = parser.parse_args()
+
+def file_lines_to_list(path):
+  # open txt file lines to a list
+  with open(path) as f:
+    content = f.readlines()
+  # remove whitespace characters like `\n` at the end of each line
+  content = [x.strip() for x in content]
+  return content
+
+if len(args.char) != 1:
+  print("Error: Please select a single char to be removed.")
+  sys.exit(0)
+
+if args.predicted:
+  os.chdir("../predicted/")
+else:
+  os.chdir("../ground-truth/")
+
+## create the backup dir if it doesn't exist already
+backup_path = "backup"
+if not os.path.exists(backup_path):
+  os.makedirs(backup_path)
+
+# get a list with the predicted files
+files_list = glob.glob('*.txt')
+files_list.sort()
+
+for txt_file in files_list:
+  lines = file_lines_to_list(txt_file)
+  is_char_present = any(args.char in line for line in lines)
+  if is_char_present:
+    # move old file to backup
+    os.rename(txt_file, backup_path + "/" + txt_file)
+    # create new file
+    with open(txt_file, "a") as new_f:
+      for line in lines:
+        #print(line)
+        if args.predicted:
+          class_name, confidence, left, top, right, bottom = line.split(args.char)
+          # remove any white space if existent in the class name
+          class_name = class_name.replace(" ", "")
+          new_f.write(class_name + " " + confidence + " " + left + " " + top + " " + right + " " + bottom + '\n')
+        else:
+          # ground-truth has no "confidence"
+          class_name, left, top, right, bottom = line.split(args.char)
+          # remove any white space if existent in the class name
+          class_name = class_name.replace(" ", "")
+          new_f.write(class_name  + " " + left + " " + top + " " + right + " " + bottom + '\n')