suppression du ratio aléatoire

labelme2yolo.py

@@ -15,7 +15,7 @@ import shutil
 import argparse
 from pathlib import Path
 from glob import glob
-#import ipdb;ipdb.set_trace()
+
 
 # Parse arguments
 def arg_directory(path):
@@ -25,67 +25,36 @@ def arg_directory(path):
         raise argparse.ArgumentTypeError(f'`{path}` is not a valid path')
 
 
-parser = argparse.ArgumentParser(
-    description='Convert LabelMe annotations to YOLO compatible'
-)
-parser.add_argument('--input',
-                    type=arg_directory,
-                    help='Directory to LabelMe annotations',
-                    default=os.path.join(
-                        str(Path.home()), 'Pictures', 'Webcam')
-                    )
-parser.add_argument('--output',
-                    type=arg_directory,
-                    help='Directory to which YOLO annotations will be stored',
-                    default='./yolo'
-                    )
-parser.add_argument('--ratio',
-                    type=float,
-                    help='Training ratio',
-                    default=0.9
-                    )
+parser = argparse.ArgumentParser(description='Convert LabelMe annotations to YOLO compatible')
+parser.add_argument('-p','--path_to_data',type=arg_directory,help='Path to LabelMe annotations')
+parser.add_argument('-d','--direction',type=arg_directory,help='Directory to which YOLO annotations will be stored')
 args = parser.parse_args()
 
 # YOLO metadata and files
 yolo_names = []
-yolo_train_dir_path = os.path.join(args.output, 'train')
-yolo_valid_dir_path = os.path.join(args.output, 'valid')
-yolo_backup_dir_path = os.path.join(args.output, 'backup')
-yolo_list_file_train_path = os.path.join(args.output, 'train.txt')
-yolo_list_file_valid_path = os.path.join(args.output, 'valid.txt')
-yolo_data_path = os.path.join(args.output, 'custom.data')
-yolo_names_path = os.path.join(args.output, 'custom.names')
+yolo_names_path = os.path.join(args.direction, 'custom.names')
 
 # Prepare output directory
-shutil.rmtree(yolo_train_dir_path)
-os.mkdir(yolo_train_dir_path)
-shutil.rmtree(yolo_valid_dir_path)
-os.mkdir(yolo_valid_dir_path)
-if not os.path.isdir(yolo_backup_dir_path):
-    os.mkdir(yolo_backup_dir_path)
+
+os.mkdir(os.path.join(args.direction,'labels'))
 
 # Convert image annotations
-yolo_list_file = {
-    'train': open(yolo_list_file_train_path, 'w'),
-    'valid': open(yolo_list_file_valid_path, 'w')
-}
-for index, labelme_annotation_path in enumerate(glob(f'{args.input}/*.json')):
+
+for index, labelme_annotation_path in enumerate(glob(f'{args.path_to_data}/*.json')):
     image_id = os.path.basename(labelme_annotation_path).rstrip('.json')
-    train_or_valid = 'train' if random.random() < args.ratio else 'valid'
 
     labelme_annotation_file = open(labelme_annotation_path, 'r')
     labelme_annotation = json.load(labelme_annotation_file)
 
-    yolo_annotation_path = os.path.join(args.output, train_or_valid, image_id + '.txt')
+    yolo_annotation_path = os.path.join(args.direction,'labels', image_id + '.txt')
     yolo_annotation_file = open(yolo_annotation_path, 'w')
     yolo_image = base64.decodebytes(labelme_annotation['imageData'].encode())
-    yolo_image_path = os.path.join(args.output, train_or_valid, image_id + '.jpg')
+    yolo_image_path = os.path.join(args.direction, 'labels', image_id + '.jpg')
 
     # Write YOLO image (and it to the list)
     yolo_image_file = open(yolo_image_path, 'wb')
     yolo_image_file.write(yolo_image)
     yolo_image_file.close()
-    yolo_list_file[train_or_valid].write(f'{yolo_image_path}{os.linesep}')
 
     # Write YOLO image annotation
     for shape in labelme_annotation['shapes']:
@@ -103,25 +72,12 @@ for index, labelme_annotation_path in enumerate(glob(f'{args.input}/*.json')):
         height = abs(points[1][1] - points[0][1]) * scale_height
         x = (abs(points[1][0] + points[0][0]) / 2) * scale_width
         y = (abs(points[1][1] + points[0][1]) / 2) * scale_height
-#       object_class = yolo_names.index(shape['label'])
+
         object_class = shape['label']
         yolo_annotation_file.write(f'{object_class} {x} {y} {width} {height}\n')
-    yolo_annotation_file.close()
-yolo_list_file['train'].close()
-yolo_list_file['valid'].close()
 
 # Write YOLO names
 yolo_names_file = open(yolo_names_path, 'w')
 yolo_names_file.write(os.linesep.join(yolo_names))
 yolo_names_file.close()
 
-# Write YOLO data configuration
-yolo_data_file = open(yolo_data_path, 'w')
-yolo_data_file.write(f'classes = {len(yolo_names)}{os.linesep}')
-yolo_data_file.write(f'train = {yolo_list_file_train_path}{os.linesep}')
-yolo_data_file.write(f'valid = {yolo_list_file_valid_path}{os.linesep}')
-yolo_data_file.write(f'names = {yolo_names_path}{os.linesep}')
-yolo_data_file.write(f'backup = {yolo_backup_dir_path}{os.linesep}')
-
-
-