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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 !
255 lines
8.2 KiB
Python
255 lines
8.2 KiB
Python
import cv2
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import pickle
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from pathlib import Path
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from facelib import LandmarksProcessor
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from interact import interact as io
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from utils import Path_utils
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from utils.cv2_utils import *
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from utils.DFLJPG import DFLJPG
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from utils.DFLPNG import DFLPNG
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def save_faceset_metadata_folder(input_path):
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input_path = Path(input_path)
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metadata_filepath = input_path / 'meta.dat'
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io.log_info (f"Saving metadata to {str(metadata_filepath)}\r\n")
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d = {}
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for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Processing"):
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filepath = Path(filepath)
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath) )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath) )
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else:
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continue
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dfl_dict = dflimg.getDFLDictData()
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d[filepath.name] = ( dflimg.get_shape(), dfl_dict )
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try:
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with open(metadata_filepath, "wb") as f:
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f.write ( pickle.dumps(d) )
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except:
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raise Exception( 'cannot save %s' % (filename) )
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io.log_info("Now you can edit images.")
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io.log_info("!!! Keep same filenames in the folder.")
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io.log_info("You can change size of images, restoring process will downscale back to original size.")
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io.log_info("After that, use restore metadata.")
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def restore_faceset_metadata_folder(input_path):
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input_path = Path(input_path)
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metadata_filepath = input_path / 'meta.dat'
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io.log_info (f"Restoring metadata from {str(metadata_filepath)}.\r\n")
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if not metadata_filepath.exists():
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io.log_err(f"Unable to find {str(metadata_filepath)}.")
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try:
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with open(metadata_filepath, "rb") as f:
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d = pickle.loads(f.read())
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except:
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raise FileNotFoundError(filename)
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for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Processing"):
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filepath = Path(filepath)
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shape, dfl_dict = d.get(filepath.name, None)
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img = cv2_imread (str(filepath))
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if img.shape != shape:
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img = cv2.resize (img, (shape[1], shape[0]), cv2.INTER_LANCZOS4 )
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if filepath.suffix == '.png':
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cv2_imwrite (str(filepath), img)
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elif filepath.suffix == '.jpg':
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cv2_imwrite (str(filepath), img, [int(cv2.IMWRITE_JPEG_QUALITY), 100] )
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if filepath.suffix == '.png':
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DFLPNG.embed_dfldict( str(filepath), dfl_dict )
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elif filepath.suffix == '.jpg':
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DFLJPG.embed_dfldict( str(filepath), dfl_dict )
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else:
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continue
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metadata_filepath.unlink()
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def remove_ie_polys_file (filepath):
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filepath = Path(filepath)
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath) )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath) )
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else:
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return
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if dflimg is None:
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io.log_err ("%s is not a dfl image file" % (filepath.name) )
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return
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dflimg.remove_ie_polys()
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dflimg.embed_and_set( str(filepath) )
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def remove_ie_polys_folder(input_path):
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input_path = Path(input_path)
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io.log_info ("Removing ie_polys...\r\n")
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for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Removing"):
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filepath = Path(filepath)
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remove_ie_polys_file(filepath)
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def remove_fanseg_file (filepath):
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filepath = Path(filepath)
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath) )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath) )
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else:
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return
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if dflimg is None:
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io.log_err ("%s is not a dfl image file" % (filepath.name) )
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return
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dflimg.remove_fanseg_mask()
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dflimg.embed_and_set( str(filepath) )
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def remove_fanseg_folder(input_path):
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input_path = Path(input_path)
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io.log_info ("Removing fanseg mask...\r\n")
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for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Removing"):
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filepath = Path(filepath)
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remove_fanseg_file(filepath)
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def convert_png_to_jpg_file (filepath):
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filepath = Path(filepath)
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if filepath.suffix != '.png':
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return
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dflpng = DFLPNG.load (str(filepath) )
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if dflpng is None:
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io.log_err ("%s is not a dfl image file" % (filepath.name) )
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return
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dfl_dict = dflpng.getDFLDictData()
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img = cv2_imread (str(filepath))
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new_filepath = str(filepath.parent / (filepath.stem + '.jpg'))
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cv2_imwrite ( new_filepath, img, [int(cv2.IMWRITE_JPEG_QUALITY), 100])
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DFLJPG.embed_data( new_filepath,
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face_type=dfl_dict.get('face_type', None),
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landmarks=dfl_dict.get('landmarks', None),
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ie_polys=dfl_dict.get('ie_polys', None),
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source_filename=dfl_dict.get('source_filename', None),
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source_rect=dfl_dict.get('source_rect', None),
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source_landmarks=dfl_dict.get('source_landmarks', None) )
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filepath.unlink()
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def convert_png_to_jpg_folder (input_path):
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input_path = Path(input_path)
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io.log_info ("Converting PNG to JPG...\r\n")
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for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Converting"):
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filepath = Path(filepath)
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convert_png_to_jpg_file(filepath)
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def add_landmarks_debug_images(input_path):
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io.log_info ("Adding landmarks debug images...")
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for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Processing"):
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filepath = Path(filepath)
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img = cv2_imread(str(filepath))
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath) )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath) )
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else:
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dflimg = None
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if dflimg is None:
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io.log_err ("%s is not a dfl image file" % (filepath.name) )
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continue
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if img is not None:
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face_landmarks = dflimg.get_landmarks()
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LandmarksProcessor.draw_landmarks(img, face_landmarks, transparent_mask=True, ie_polys=dflimg.get_ie_polys() )
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output_file = '{}{}'.format( str(Path(str(input_path)) / filepath.stem), '_debug.jpg')
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cv2_imwrite(output_file, img, [int(cv2.IMWRITE_JPEG_QUALITY), 50] )
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def recover_original_aligned_filename(input_path):
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io.log_info ("Recovering original aligned filename...")
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files = []
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for filepath in io.progress_bar_generator( Path_utils.get_image_paths(input_path), "Processing"):
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filepath = Path(filepath)
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath) )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath) )
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else:
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dflimg = None
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if dflimg is None:
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io.log_err ("%s is not a dfl image file" % (filepath.name) )
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continue
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files += [ [filepath, None, dflimg.get_source_filename(), False] ]
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files_len = len(files)
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for i in io.progress_bar_generator( range(files_len), "Sorting" ):
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fp, _, sf, converted = files[i]
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if converted:
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continue
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sf_stem = Path(sf).stem
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files[i][1] = fp.parent / ( sf_stem + '_0' + fp.suffix )
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files[i][3] = True
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c = 1
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for j in range(i+1, files_len):
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fp_j, _, sf_j, converted_j = files[j]
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if converted_j:
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continue
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if sf_j == sf:
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files[j][1] = fp_j.parent / ( sf_stem + ('_%d' % (c)) + fp_j.suffix )
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files[j][3] = True
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c += 1
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for file in io.progress_bar_generator( files, "Renaming", leave=False ):
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fs, _, _, _ = file
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dst = fs.parent / ( fs.stem + '_tmp' + fs.suffix )
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try:
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fs.rename (dst)
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except:
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io.log_err ('fail to rename %s' % (fs.name) )
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for file in io.progress_bar_generator( files, "Renaming" ):
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fs, fd, _, _ = file
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fs = fs.parent / ( fs.stem + '_tmp' + fs.suffix )
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try:
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fs.rename (fd)
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except:
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io.log_err ('fail to rename %s' % (fs.name) )
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