Extra

ground-truth:

• convert xml to our format:

  1. Insert ground-truth xml files into ground-truth/
  2. Run the python script: python convert_gt_xml.py

• convert YOLO to our format:

  1. Add class list to the file class_list.txt
  2. Insert ground-truth files into ground-truth/
  3. Insert images into images/
  4. Run the python script: python convert_gt_yolo.py

• convert keras-yolo3 to our format:

  1. Add or update the class list to the file class_list.txt
  2. Use the parameter --gt to set the ground-truth source.
  3. Run the python script: python3 convert_keras-yolo3.py --gt <gt_file_path>
     1. Supports only python 3.
     2. This code can handle recursive annotation structure. Just use the -r parameter.
     3. The converted annotation is placed by default in a new from_kerasyolo3 folder. You can change that with the parameter -o.
     4. The format is defined according with github.com/qqwweee/keras-yolo3

detection-results:

• convert darkflow json to our format:

  1. Insert result json files into detection-results/
  2. Run the python script: python convert_dr_darkflow_json.py

• convert YOLO to our format:

  After runnuning darknet on a list of images, e.g.: darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -dont_show -ext_output < data/test.txt > result.txt

  1. Copy the file result.txt to the folder extra/
  2. Run the python script: python convert_dr_yolo.py

• convert keras-yolo3 to our format:

  1. Add or update the class list to the file class_list.txt
  2. Use the parameter --dr to set the detection-results source.
  3. Run the python script: python3 convert_keras-yolo3.py --dr <dr_file_path>
     1. Supports only python 3.
     2. This code can handle recursive annotation structure. Just use the -r parameter.
     3. The converted annotation is placed by default in a new from_kerasyolo3 folder. You can change that with the parameter -o.
     4. The format is defined according with github.com/gustavovaliati/keras-yolo3

Find the files that contain a specific class of objects

1. Run the find_class.py script and specify the class as argument, e.g. python find_class.py chair

Intersect ground-truth and detection-results files

This script ensures same number of files in ground-truth and detection-results folder. When you encounter file not found error, it's usually because you have mismatched numbers of ground-truth and detection-results files. You can use this script to move ground-truth and detection-results files that are not in the intersection into a backup folder (backup_no_matches_found). This will retain only files that have the same name in both folders.

1. Prepare .txt files in your ground-truth and detection-results folders.
2. Run the intersect-gt-and-dr.py script to move non-intersected files into a backup folder (default: backup_no_matches_found).

python intersect-gt-and-dr.py