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enhancing landmarks extractor by using s3fd second pass inside second pass,

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it will be x2 slower, but time will be saved due to more images will be marked properly
works on 2GB+
This commit is contained in:
iperov
2019-03-18 10:25:24 +04:00
parent 1d56585f33
commit b8efb4cbba
3 changed files with 51 additions and 17 deletions
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33
mainscripts/Extractor.py
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@@ -52,7 +52,7 @@ class ExtractSubprocessor(Subprocessor):
nnlib.import_all (device_config)
self.e = facelib.S3FDExtractor()
else:
raise ValueError ("Wrond detector type.")
raise ValueError ("Wrong detector type.")
if self.e is not None:
self.e.__enter__()
@@ -61,6 +61,11 @@ class ExtractSubprocessor(Subprocessor):
nnlib.import_all (device_config)
self.e = facelib.LandmarksExtractor(nnlib.keras)
self.e.__enter__()
if device_config.gpu_vram_gb[0] >= 2:
self.second_pass_e = facelib.S3FDExtractor()
self.second_pass_e.__enter__()
else:
self.second_pass_e = None
elif self.type == 'final':
pass
@@ -76,7 +81,7 @@ class ExtractSubprocessor(Subprocessor):
filename_path_str = str(filename_path)
if self.cached_image[0] == filename_path_str:
image = self.cached_image[1]
image = self.cached_image[1] #cached image for manual extractor
else:
image = cv2_imread( filename_path_str )
@@ -102,8 +107,14 @@ class ExtractSubprocessor(Subprocessor):
image = image[0:h-hm,0:w-wm,:]
self.cached_image = ( filename_path_str, image )
src_dflimg = None
h, w, ch = image.shape
if h == w:
#extracting from already extracted jpg image?
if filename_path.suffix == '.jpg':
src_dflimg = DFLJPG.load ( str(filename_path) )
if self.type == 'rects':
h, w, ch = image.shape
if min(w,h) < 128:
self.log_err ( 'Image is too small %s : [%d, %d]' % ( str(filename_path), w, h ) )
rects = []
@@ -116,18 +127,13 @@ class ExtractSubprocessor(Subprocessor):
rects = data[1]
if rects is None:
landmarks = None
else:
landmarks = self.e.extract_from_bgr (image, rects)
else:
landmarks = self.e.extract_from_bgr (image, rects, self.second_pass_e if src_dflimg is None else None)
return [str(filename_path), landmarks]
elif self.type == 'final':
src_dflimg = None
(h,w,c) = image.shape
if h == w:
#extracting from already extracted jpg image?
if filename_path.suffix == '.jpg':
src_dflimg = DFLJPG.load ( str(filename_path) )
result = []
faces = data[1]
@@ -139,7 +145,10 @@ class ExtractSubprocessor(Subprocessor):
face_idx = 0
for face in faces:
rect = np.array(face[0])
image_landmarks = np.array(face[1])
image_landmarks = face[1]
if image_landmarks is None:
continue
image_landmarks = np.array(image_landmarks)
if self.face_type == FaceType.MARK_ONLY:
face_image = image