added feature for choosing different face recognition models

detect-face.py

@@ -8,7 +8,7 @@
 import os
 
 backends = ['opencv', 'ssd', 'dlib', 'mtcnn', 'retinaface', 'mediapipe']
-models = ['VGG-Face', 'Facenet', 'Facenet512', 'OpenFace', 'DeepFace', 'DeepID', 'ArcFace', 'Dlib']
+models = ['VGG-Face', 'Facenet512', 'ArcFace', 'Dlib']
 
 
 
@@ -25,14 +25,16 @@ def main():
  source_image = arguments.source_image[0]
  database_path = arguments.database_path[0]
  k_value = arguments.k_value[0]
+ model = arguments.model[0]
  output_file = arguments.output_file[0]
 
  identities = []
 
  results_dataframe = DeepFace.find(img_path = source_image,
  db_path = database_path,
  enforce_detection = False,
- detector_backend = backends[3])
+ detector_backend = backends[3],
+ model_name=model)
 
  # Get the first 'K' results from the facial recognition system.
  for i, row in results_dataframe.iloc[:k_value].iterrows():
@@ -99,6 +101,9 @@ def parse_command_line_arguments() -> argparse.ArgumentParser:
  parser.add_argument('-k', '--k_value', type=int, nargs=1, required=True,
  help='Determines the value used for Top-K Accuracy.')
 
+ parser.add_argument('-m', '--model', choices=['VGG-Face', 'Facenet512', 'ArcFace', 'Ensemble'], nargs=1, required=True,
+ help='Face recognition model to use.')
+
  parser.add_argument('-o', '--output_file', nargs=1, required=True,
  help='Output file to write accuracy results to (Ex. "output.txt")')
 

requirements.txt

@@ -1,3 +1,4 @@
 tensorflow
 deepface
 tqdm
+lightgbm

run.py

@@ -16,9 +16,9 @@ def main():
  source_directory = arguments.source_directory[0]
  database_path = arguments.database_path[0]
  k_value = arguments.k_value[0]
+ model = arguments.model[0]
  output_file = arguments.output_file[0]
 
- #results = [os.path.join(dp, f) for dp, dn, fn in os.walk(source_directory) for f in fn]
  results = get_an_image_from_each_class(source_directory)
  source_images_count = len(results)
  correct_predictions = 0
@@ -43,7 +43,7 @@ def main():
  out_file.write('\n' + str(count) + '.\n')
  out_file.close()
 
- correct_predictions += subprocess.call([sys.executable, 'detect-face.py', '-s', item, '-d', database_path, '-k', str(k_value), '-o', output_file])
+ correct_predictions += subprocess.call([sys.executable, 'detect-face.py', '-s', item, '-d', database_path, '-k', str(k_value), '-m', model, '-o', output_file])
 
  count += 1
  progress_bar.update(1)
@@ -77,6 +77,9 @@ def parse_command_line_arguments() -> argparse.ArgumentParser:
  parser.add_argument('-k', '--k_value', type=int, nargs=1, required=True,
  help='Determines the value used for Top-K Accuracy.')
 
+ parser.add_argument('-m', '--model', choices=['VGG-Face', 'Facenet512', 'ArcFace', 'Ensemble'], nargs=1, required=True,
+ help='Face recognition model to use.')
+
  parser.add_argument('-o', '--output_file', nargs=1, required=True,
  help='Output file to write accuracy results to (Ex. "output.txt")')