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finalized dpi consistency

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This commit is contained in:
Brigham Lysenko 2019-08-19 14:06:49 -06:00
commit 697bddaff3
3 changed files with 17 additions and 17 deletions
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1
facelib/LandmarksProcessor.py
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@ -152,6 +152,7 @@ def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
else:
raise ValueError ('wrong face_type: ', face_type)
mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
mat = mat * (output_size - 2 * padding)
mat[:,2] += padding

2
facelib/S3FDExtractor.py
View file

@ -70,7 +70,7 @@ class S3FDExtractor(object):
if len(bboxlist) == 0:
bboxlist = np.zeros((1, 5))
bboxlist = bboxlist[self.refine_nms(bboxlist, 0.3), :]
bboxlist = bboxlist[self.refine_nms(bboxlist, 0.8), :]
bboxlist = [ x[:-1].astype(np.int) for x in bboxlist if x[-1] >= 0.5]
return bboxlist

31
mainscripts/Extractor.py
View file

@ -41,7 +41,6 @@ class ExtractSubprocessor(Subprocessor):
#override
def on_initialize(self, client_dict):
self.type = client_dict['type']
self.image_size = client_dict['image_size']
self.face_type = client_dict['face_type']
self.device_idx = client_dict['device_idx']
self.cpu_only = client_dict['device_type'] == 'CPU'
@ -126,6 +125,8 @@ class ExtractSubprocessor(Subprocessor):
else:
h, w, ch = image.shape
#self.image_size = h
if ch == 1:
image = np.repeat (image, 3, -1)
elif ch == 4:
@ -230,20 +231,22 @@ class ExtractSubprocessor(Subprocessor):
continue
rect = np.array(rect)
rect_area = mathlib.polygon_area(np.array(rect[[0, 2, 2, 0]]), np.array(rect[[1, 1, 3, 3]]))
self.image_size = int(math.sqrt(rect_area))
print(rect_area)
if self.face_type == FaceType.MARK_ONLY:
image_to_face_mat = None
face_image = image
face_image_landmarks = image_landmarks
else:
image_to_face_mat = LandmarksProcessor.get_transform_mat (image_landmarks, self.image_size, self.face_type)
#print(image_landmarks)
face_image = cv2.warpAffine(image, image_to_face_mat, (self.image_size, self.image_size), cv2.INTER_LANCZOS4)
face_image_landmarks = LandmarksProcessor.transform_points (image_landmarks, image_to_face_mat)
landmarks_bbox = LandmarksProcessor.transform_points ( [ (0,0), (0,self.image_size-1), (self.image_size-1, self.image_size-1), (self.image_size-1,0) ], image_to_face_mat, True)
rect_area = mathlib.polygon_area(np.array(rect[[0,2,2,0]]), np.array(rect[[1,1,3,3]]))
landmarks_area = mathlib.polygon_area(landmarks_bbox[:,0], landmarks_bbox[:,1] )
if landmarks_area > 4*rect_area: #get rid of faces which umeyama-landmark-area > 4*detector-rect-area
@ -305,10 +308,9 @@ class ExtractSubprocessor(Subprocessor):
return data.filename
#override
def __init__(self, input_data, type, image_size=None, face_type=None, debug_dir=None, multi_gpu=False, cpu_only=False, manual=False, manual_window_size=0, final_output_path=None):
def __init__(self, input_data, type, face_type=None, debug_dir=None, multi_gpu=False, cpu_only=False, manual=False, manual_window_size=0, final_output_path=None):
self.input_data = input_data
self.type = type
self.image_size = image_size
self.face_type = face_type
self.debug_dir = debug_dir
self.final_output_path = final_output_path
@ -361,7 +363,6 @@ class ExtractSubprocessor(Subprocessor):
#override
def process_info_generator(self):
base_dict = {'type' : self.type,
'image_size': self.image_size,
'face_type': self.face_type,
'debug_dir': self.debug_dir,
'final_output_dir': str(self.final_output_path),
@ -731,7 +732,6 @@ def extract_fanseg(input_dir, device_args={} ):
data = ExtractSubprocessor ([ ExtractSubprocessor.Data(filename) for filename in paths_to_extract ], 'fanseg', multi_gpu=multi_gpu, cpu_only=cpu_only).run()
def extract_umd_csv(input_file_csv,
image_size=256,
face_type='full_face',
device_args={} ):
@ -798,7 +798,7 @@ def extract_umd_csv(input_file_csv,
data = ExtractSubprocessor (data, 'landmarks', multi_gpu=multi_gpu, cpu_only=cpu_only).run()
io.log_info ('Performing 3rd pass...')
data = ExtractSubprocessor (data, 'final', image_size, face_type, None, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, final_output_path=output_path).run()
data = ExtractSubprocessor (data, 'final', face_type, None, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, final_output_path=output_path).run()
faces_detected += sum([d.faces_detected for d in data])
@ -814,7 +814,6 @@ def main(input_dir,
manual_fix=False,
manual_output_debug_fix=False,
manual_window_size=1368,
image_size=256,
face_type='full_face',
device_args={}):
@ -867,16 +866,16 @@ def main(input_dir,
if images_found != 0:
if detector == 'manual':
io.log_info ('Performing manual extract...')
data = ExtractSubprocessor ([ ExtractSubprocessor.Data(filename) for filename in input_path_image_paths ], 'landmarks', image_size, face_type, debug_dir, cpu_only=cpu_only, manual=True, manual_window_size=manual_window_size).run()
data = ExtractSubprocessor ([ ExtractSubprocessor.Data(filename) for filename in input_path_image_paths ], 'landmarks', face_type, debug_dir, cpu_only=cpu_only, manual=True, manual_window_size=manual_window_size).run()
else:
io.log_info ('Performing 1st pass...')
data = ExtractSubprocessor ([ ExtractSubprocessor.Data(filename) for filename in input_path_image_paths ], 'rects-'+detector, image_size, face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False).run()
data = ExtractSubprocessor ([ ExtractSubprocessor.Data(filename) for filename in input_path_image_paths ], 'rects-'+detector, face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False).run()
io.log_info ('Performing 2nd pass...')
data = ExtractSubprocessor (data, 'landmarks', image_size, face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False).run()
data = ExtractSubprocessor (data, 'landmarks', face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False).run()
io.log_info ('Performing 3rd pass...')
data = ExtractSubprocessor (data, 'final', image_size, face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, final_output_path=output_path).run()
data = ExtractSubprocessor (data, 'final', face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, final_output_path=output_path).run()
faces_detected += sum([d.faces_detected for d in data])
if manual_fix:
@ -885,8 +884,8 @@ def main(input_dir,
else:
fix_data = [ ExtractSubprocessor.Data(d.filename) for d in data if d.faces_detected == 0 ]
io.log_info ('Performing manual fix for %d images...' % (len(fix_data)) )
fix_data = ExtractSubprocessor (fix_data, 'landmarks', image_size, face_type, debug_dir, manual=True, manual_window_size=manual_window_size).run()
fix_data = ExtractSubprocessor (fix_data, 'final', image_size, face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, final_output_path=output_path).run()
fix_data = ExtractSubprocessor (fix_data, 'landmarks', face_type, debug_dir, manual=True, manual_window_size=manual_window_size).run()
fix_data = ExtractSubprocessor (fix_data, 'final', face_type, debug_dir, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, final_output_path=output_path).run()
faces_detected += sum([d.faces_detected for d in fix_data])