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https://github.com/iperov/DeepFaceLab.git
synced 2025-08-20 05:23:22 -07:00
DFL now works with JPG files by default. Old PNG files also supported. Added util convertor PNG to JPG.
This commit is contained in:
iperov
parent
f0a5f97995
commit
6d95dd4a99
9 changed files with 400 additions and 92 deletions
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@ -6,6 +6,7 @@ from utils import Path_utils
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import cv2
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from tqdm import tqdm
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from utils.DFLPNG import DFLPNG
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from utils.DFLJPG import DFLJPG
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from utils import image_utils
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import shutil
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import numpy as np
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@ -163,7 +164,14 @@ class ConvertSubprocessor(SubprocessorBase):
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cv2.waitKey(0)
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faces_processed = 1
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elif self.converter.get_mode() == ConverterBase.MODE_IMAGE_WITH_LANDMARKS:
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image_landmarks = DFLPNG.load( str(filename_path), throw_on_no_embedded_data=True ).get_landmarks()
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if filename_path.suffix == '.png':
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dflimg = DFLPNG.load( str(filename_path), throw_on_no_embedded_data=True )
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elif filename_path.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filename_path), throw_on_no_embedded_data=True )
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else:
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raise Exception ("%s is not a dfl image file" % (filename_path.name) )
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image_landmarks = dflimg.get_landmarks()
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image = self.converter.convert_image(image, image_landmarks, self.debug)
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if self.debug:
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@ -259,16 +267,21 @@ def main (input_dir, output_dir, model_dir, model_name, aligned_dir=None, **in_o
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alignments = {}
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aligned_path_image_paths = Path_utils.get_image_paths(aligned_path)
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for filename in tqdm(aligned_path_image_paths, desc="Collecting alignments", ascii=True ):
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dflpng = DFLPNG.load( str(filename), print_on_no_embedded_data=True )
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if dflpng is None:
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continue
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for filepath in tqdm(aligned_path_image_paths, desc="Collecting alignments", ascii=True ):
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filepath = Path(filepath)
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source_filename_stem = Path( dflpng.get_source_filename() ).stem
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath), print_on_no_embedded_data=True )
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else:
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print ("%s is not a dfl image file" % (filepath.name) )
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source_filename_stem = Path( dflimg.get_source_filename() ).stem
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if source_filename_stem not in alignments.keys():
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alignments[ source_filename_stem ] = []
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alignments[ source_filename_stem ].append (dflpng.get_source_landmarks())
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alignments[ source_filename_stem ].append (dflimg.get_source_landmarks())
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#interpolate landmarks
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@ -7,7 +7,7 @@ from pathlib import Path
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import numpy as np
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import cv2
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from utils import Path_utils
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from utils.DFLPNG import DFLPNG
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from utils.DFLJPG import DFLJPG
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from utils import image_utils
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from facelib import FaceType
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import facelib
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@ -311,7 +311,7 @@ class ExtractSubprocessor(SubprocessorBase):
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debug_image = image.copy()
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for (face_idx, face) in enumerate(faces):
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output_file = '{}_{}{}'.format(str(self.output_path / filename_path.stem), str(face_idx), '.png')
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output_file = '{}_{}{}'.format(str(self.output_path / filename_path.stem), str(face_idx), '.jpg')
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rect = face[0]
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image_landmarks = np.array(face[1])
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@ -329,7 +329,7 @@ class ExtractSubprocessor(SubprocessorBase):
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cv2.imwrite(output_file, face_image)
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DFLPNG.embed_data(output_file, face_type = FaceType.toString(self.face_type),
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DFLJPG.embed_data(output_file, face_type = FaceType.toString(self.face_type),
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landmarks = face_image_landmarks.tolist(),
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yaw_value = facelib.LandmarksProcessor.calc_face_yaw (face_image_landmarks),
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pitch_value = facelib.LandmarksProcessor.calc_face_pitch (face_image_landmarks),
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@ -10,6 +10,7 @@ from pathlib import Path
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from utils import Path_utils
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from utils import image_utils
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from utils.DFLPNG import DFLPNG
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from utils.DFLJPG import DFLJPG
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from facelib import LandmarksProcessor
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from utils.SubprocessorBase import SubprocessorBase
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import multiprocessing
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@ -86,17 +87,24 @@ class BlurEstimatorSubprocessor(SubprocessorBase):
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#override
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def onClientProcessData(self, data):
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filename_path = Path( data[0] )
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dflpng = DFLPNG.load( str(filename_path), print_on_no_embedded_data=True )
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if dflpng is not None:
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image = cv2.imread( str(filename_path) )
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image = ( image * \
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LandmarksProcessor.get_image_hull_mask (image.shape, dflpng.get_landmarks()) \
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).astype(np.uint8)
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return [ str(filename_path), estimate_sharpness( image ) ]
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filepath = Path( data[0] )
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath), print_on_no_embedded_data=True )
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else:
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return [ str(filename_path), 0 ]
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print ("%s is not a dfl image file" % (filepath.name) )
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dflimg = None
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if dflimg is not None:
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image = cv2.imread( str(filepath) )
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image = ( image * \
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LandmarksProcessor.get_image_hull_mask (image.shape, dflimg.get_landmarks()) \
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).astype(np.uint8)
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return [ str(filepath), estimate_sharpness( image ) ]
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else:
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return [ str(filepath), 0 ]
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#override
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def onClientGetDataName (self, data):
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@ -151,15 +159,15 @@ def sort_by_face(input_path):
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for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True):
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filepath = Path(filepath)
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if filepath.suffix != '.png':
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print ("%s is not a png file required for sort_by_face" % (filepath.name) )
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath), print_on_no_embedded_data=True )
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else:
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print ("%s is not a dfl image file" % (filepath.name) )
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continue
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dflpng = DFLPNG.load (str(filepath), print_on_no_embedded_data=True)
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if dflpng is None:
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continue
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img_list.append( [str(filepath), dflpng.get_landmarks()] )
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img_list.append( [str(filepath), dflimg.get_landmarks()] )
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img_list_len = len(img_list)
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@ -187,15 +195,15 @@ def sort_by_face_dissim(input_path):
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for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True):
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filepath = Path(filepath)
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if filepath.suffix != '.png':
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print ("%s is not a png file required for sort_by_face_dissim" % (filepath.name) )
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continue
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath), print_on_no_embedded_data=True )
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else:
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print ("%s is not a dfl image file" % (filepath.name) )
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continue
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dflpng = DFLPNG.load (str(filepath), print_on_no_embedded_data=True)
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if dflpng is None:
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continue
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img_list.append( [str(filepath), dflpng.get_landmarks(), 0 ] )
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img_list.append( [str(filepath), dflimg.get_landmarks(), 0 ] )
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img_list_len = len(img_list)
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for i in tqdm( range(0, img_list_len-1), desc="Sorting", ascii=True):
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@ -220,15 +228,15 @@ def sort_by_face_yaw(input_path):
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for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True):
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filepath = Path(filepath)
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if filepath.suffix != '.png':
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print ("%s is not a png file required for sort_by_face_dissim" % (filepath.name) )
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath), print_on_no_embedded_data=True )
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else:
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print ("%s is not a dfl image file" % (filepath.name) )
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continue
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dflpng = DFLPNG.load (str(filepath), print_on_no_embedded_data=True)
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if dflpng is None:
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continue
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img_list.append( [str(filepath), np.array( dflpng.get_yaw_value() ) ] )
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img_list.append( [str(filepath), np.array( dflimg.get_yaw_value() ) ] )
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print ("Sorting...")
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img_list = sorted(img_list, key=operator.itemgetter(1), reverse=True)
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@ -436,15 +444,22 @@ def sort_by_hist_dissim(input_path):
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print ("Sorting by histogram dissimilarity...")
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img_list = []
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for filename_path in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True):
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image = cv2.imread(filename_path)
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for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True):
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filepath = Path(filepath)
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dflpng = DFLPNG.load( str(filename_path) )
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if dflpng is not None:
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face_mask = LandmarksProcessor.get_image_hull_mask (image.shape, dflpng.get_landmarks())
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image = (image*face_mask).astype(np.uint8)
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load ( str(filepath), print_on_no_embedded_data=True )
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else:
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print ("%s is not a dfl image file" % (filepath.name) )
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continue
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image = cv2.imread(str(filepath))
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face_mask = LandmarksProcessor.get_image_hull_mask (image.shape, dflimg.get_landmarks())
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image = (image*face_mask).astype(np.uint8)
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img_list.append ([filename_path, cv2.calcHist([cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)], [0], None, [256], [0, 256]), 0 ])
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img_list.append ([str(filepath), cv2.calcHist([cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)], [0], None, [256], [0, 256]), 0 ])
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img_list = HistDissimSubprocessor(img_list).process()
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@ -512,26 +527,27 @@ class FinalLoaderSubprocessor(SubprocessorBase):
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filepath = Path(data[0])
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try:
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if filepath.suffix != '.png':
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raise Exception ("%s is not a png file required for sort_final" % (filepath.name) )
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dflpng = DFLPNG.load (str(filepath), print_on_no_embedded_data=True)
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if dflpng is None:
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raise Exception ("")
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load( str(filepath), print_on_no_embedded_data=True )
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else:
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print ("%s is not a dfl image file" % (filepath.name) )
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raise Exception("")
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bgr = cv2.imread(str(filepath))
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if bgr is None:
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raise Exception ("Unable to load %s" % (filepath.name) )
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gray = cv2.cvtColor(bgr, cv2.COLOR_BGR2GRAY)
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gray_masked = ( gray * LandmarksProcessor.get_image_hull_mask (bgr.shape, dflpng.get_landmarks() )[:,:,0] ).astype(np.uint8)
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gray_masked = ( gray * LandmarksProcessor.get_image_hull_mask (bgr.shape, dflimg.get_landmarks() )[:,:,0] ).astype(np.uint8)
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sharpness = estimate_sharpness(gray_masked)
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hist = cv2.calcHist([gray], [0], None, [256], [0, 256])
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except Exception as e:
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print (e)
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return [ 1, [str(filepath)] ]
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return [ 0, [str(filepath), sharpness, hist, dflpng.get_yaw_value() ] ]
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return [ 0, [str(filepath), sharpness, hist, dflimg.get_yaw_value() ] ]
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#override
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@ -689,15 +705,15 @@ def sort_by_origname(input_path):
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for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True):
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filepath = Path(filepath)
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if filepath.suffix != '.png':
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print ("%s is not a png file required for sort_by_origname" % (filepath.name) )
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continue
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dflpng = DFLPNG.load (str(filepath), print_on_no_embedded_data=True)
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if dflpng is None:
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if filepath.suffix == '.png':
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dflimg = DFLPNG.load( str(filepath), print_on_no_embedded_data=True )
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elif filepath.suffix == '.jpg':
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dflimg = DFLJPG.load( str(filepath), print_on_no_embedded_data=True )
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else:
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print ("%s is not a dfl image file" % (filepath.name) )
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continue
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img_list.append( [str(filepath), dflpng.get_source_filename()] )
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img_list.append( [str(filepath), dflimg.get_source_filename()] )
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print ("Sorting...")
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img_list = sorted(img_list, key=operator.itemgetter(1))
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46
mainscripts/Util.py
Normal file
46
mainscripts/Util.py
Normal file
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@ -0,0 +1,46 @@
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import os
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import sys
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import operator
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import numpy as np
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import cv2
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from tqdm import tqdm
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from shutil import copyfile
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from pathlib import Path
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from utils import Path_utils
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from utils import image_utils
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from utils.DFLPNG import DFLPNG
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from utils.DFLJPG import DFLJPG
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from facelib import LandmarksProcessor
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from utils.SubprocessorBase import SubprocessorBase
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import multiprocessing
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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), print_on_no_embedded_data=True)
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if dflpng is None:
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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), 85])
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DFLJPG.embed_data( new_filepath, **dfl_dict )
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filepath.unlink()
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def convert_png_to_jpg_folder (input_path):
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if not all(ord(c) < 128 for c in input_path):
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print ("Path to directory must contain only non unicode characters.")
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return
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input_path = Path(input_path)
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print ("Converting PNG to JPG...\r\n")
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for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Converting", ascii=True):
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filepath = Path(filepath)
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convert_png_to_jpg_file(filepath)
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