added

4.2.other) data_src util faceset metadata save.bat
	saves metadata of data_src\aligned\ faces into data_src\aligned\meta.dat

4.2.other) data_src util faceset metadata restore.bat
	restore metadata from 'meta.dat' to images
	if image size different from original, then it will be automatically resized

You can greatly enhance face details of src faceset by using Topaz Gigapixel software.
example https://i.imgur.com/Gwee99L.jpg
Example of workflow:
1) run 'data_src util faceset metadata save.bat'
2) launch Topaz Gigapixel
3) open 'data_src\aligned\' and select all images
4) set output folder to 'data_src\aligned_topaz' (create folder in save dialog)
5) set settings as on screenshot https://i.imgur.com/kAVWMQG.jpg
	you can choose 2x, 4x, or 6x upscale rate
6) start process images and wait full process
7) rename folders:
	data_src\aligned        ->  data_src\aligned_original
	data_src\aligned_topaz  ->  data_src\aligned
8) copy 'data_src\aligned_original\meta.dat' to 'data_src\aligned\'
9) run 'data_src util faceset metadata restore.bat'
	images will be downscaled back to original size (256x256) preserving details
	metadata will be restored
10) now your new enhanced faceset is ready to use !

mainscripts/Util.py

@@ -1,12 +1,84 @@
 import cv2
+import pickle
 from pathlib import Path
-from utils import Path_utils
-from utils.DFLPNG import DFLPNG
-from utils.DFLJPG import DFLJPG
-from utils.cv2_utils import *
+
 from facelib import LandmarksProcessor
 from interact import interact as io
+from utils import Path_utils
+from utils.cv2_utils import *
+from utils.DFLJPG import DFLJPG
+from utils.DFLPNG import DFLPNG
 
+
+def save_faceset_metadata_folder(input_path):
+    input_path = Path(input_path)
+
+    metadata_filepath = input_path / 'meta.dat'
+    
+    io.log_info (f"Saving metadata to {str(metadata_filepath)}\r\n")
+
+    d = {}
+    for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Processing"):
+        filepath = Path(filepath)
+        if filepath.suffix == '.png':
+            dflimg = DFLPNG.load( str(filepath) )
+        elif filepath.suffix == '.jpg':
+            dflimg = DFLJPG.load ( str(filepath) )
+        else:
+            continue
+        
+        dfl_dict = dflimg.getDFLDictData()        
+        d[filepath.name] = ( dflimg.get_shape(), dfl_dict )
+    
+    try:
+        with open(metadata_filepath, "wb") as f:
+            f.write ( pickle.dumps(d) )
+    except:
+        raise Exception( 'cannot save %s' % (filename) )
+    
+    io.log_info("Now you can edit images.")
+    io.log_info("!!! Keep same filenames in the folder.")  
+    io.log_info("You can change size of images, restoring process will downscale back to original size.")  
+    io.log_info("After that, use restore metadata.")
+    
+def restore_faceset_metadata_folder(input_path):
+    input_path = Path(input_path)
+
+    metadata_filepath = input_path / 'meta.dat'
+    io.log_info (f"Restoring metadata from {str(metadata_filepath)}.\r\n")
+    
+    if not metadata_filepath.exists():
+        io.log_err(f"Unable to find {str(metadata_filepath)}.")
+
+    try:
+        with open(metadata_filepath, "rb") as f:
+            d = pickle.loads(f.read())
+    except:
+        raise FileNotFoundError(filename)
+
+    for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Processing"):
+        filepath = Path(filepath)
+        
+        shape, dfl_dict = d.get(filepath.name, None)
+        
+        img = cv2_imread (str(filepath))
+        if img.shape != shape:
+            img = cv2.resize (img, (shape[1], shape[0]), cv2.INTER_LANCZOS4 )
+        
+            if filepath.suffix == '.png':
+                cv2_imwrite (str(filepath), img)         
+            elif filepath.suffix == '.jpg':            
+                cv2_imwrite (str(filepath), img, [int(cv2.IMWRITE_JPEG_QUALITY), 100] )
+
+        if filepath.suffix == '.png':
+            DFLPNG.embed_dfldict( str(filepath), dfl_dict )            
+        elif filepath.suffix == '.jpg':            
+            DFLJPG.embed_dfldict( str(filepath), dfl_dict )
+        else:
+            continue
+       
+    metadata_filepath.unlink()
+     
 def remove_ie_polys_file (filepath):
     filepath = Path(filepath)
 
@@ -76,7 +148,7 @@ def convert_png_to_jpg_file (filepath):
 
     img = cv2_imread (str(filepath))
     new_filepath = str(filepath.parent / (filepath.stem + '.jpg'))
-    cv2_imwrite ( new_filepath, img, [int(cv2.IMWRITE_JPEG_QUALITY), 85])
+    cv2_imwrite ( new_filepath, img, [int(cv2.IMWRITE_JPEG_QUALITY), 100])
 
     DFLJPG.embed_data( new_filepath,
                        face_type=dfl_dict.get('face_type', None),