mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-07-06 13:02:15 -07:00
small fixed and refactorings
This commit is contained in:
iperov
parent
d6a45763a2
commit
f3b343c0e5
9 changed files with 479 additions and 170 deletions
Binary file not shown.
File diff suppressed because one or more lines are too long
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@ -282,7 +282,6 @@ def mirror_landmarks (landmarks, val):
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return result
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def draw_landmarks (image, image_landmarks, color=(0,255,0), transparent_mask=False):
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image = image.copy()
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if len(image_landmarks) != 68:
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raise Exception('get_image_eye_mask works only with 68 landmarks')
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@ -309,17 +308,15 @@ def draw_landmarks (image, image_landmarks, color=(0,255,0), transparent_mask=Fa
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if transparent_mask:
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mask = get_image_hull_mask (image.shape, image_landmarks)
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image = image * (1-mask) + image * mask / 2
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return image
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image[...] = ( image * (1-mask) + image * mask / 2 )[...]
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def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type, transparent_mask=False):
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image = draw_landmarks(image, image_landmarks, transparent_mask=transparent_mask)
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draw_landmarks(image, image_landmarks, transparent_mask=transparent_mask)
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image_utils.draw_rect (image, rect, (255,0,0), 2 )
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image_to_face_mat = get_transform_mat (image_landmarks, face_size, face_type)
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points = transform_points ( [ (0,0), (0,face_size-1), (face_size-1, face_size-1), (face_size-1,0) ], image_to_face_mat, True)
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image_utils.draw_polygon (image, points, (0,0,255), 2)
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return image
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def calc_face_pitch(landmarks):
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if not isinstance(landmarks, np.ndarray):
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@ -79,16 +79,29 @@ class ExtractSubprocessor(Subprocessor):
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image = self.cached_image[1]
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else:
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image = cv2_imread( filename_path_str )
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if image is None:
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self.log_err ( 'Failed to extract %s, reason: cv2_imread() fail.' % ( str(filename_path) ) )
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return None
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image_shape = image.shape
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if len(image_shape) == 2:
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h, w = image.shape
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ch = 1
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else:
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h, w, ch = image.shape
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if ch == 1:
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image = np.repeat ( image [:,:,np.newaxis], 3, -1 )
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elif ch == 4:
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image = image[:,:,0:3]
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wm = w % 2
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hm = h % 2
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if wm + hm != 0: #fix odd image
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image = image[0:h-hm,0:w-wm,:]
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self.cached_image = ( filename_path_str, image )
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if image is None:
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self.log_err ( 'Failed to extract %s, reason: cv2_imread() fail.' % ( str(filename_path) ) )
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else:
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if self.type == 'rects':
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h, w, ch = image.shape
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if min(w,h) < 128:
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@ -141,7 +154,7 @@ class ExtractSubprocessor(Subprocessor):
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continue
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if self.debug:
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debug_image = LandmarksProcessor.draw_rect_landmarks (debug_image, rect, image_landmarks, self.image_size, self.face_type, transparent_mask=True)
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LandmarksProcessor.draw_rect_landmarks (debug_image, rect, image_landmarks, self.image_size, self.face_type, transparent_mask=True)
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output_file = '{}_{}{}'.format(str(self.output_path / filename_path.stem), str(face_idx), '.jpg')
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face_idx += 1
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@ -165,7 +178,7 @@ class ExtractSubprocessor(Subprocessor):
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cv2_imwrite(debug_output_file, debug_image, [int(cv2.IMWRITE_JPEG_QUALITY), 50] )
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return result
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return None
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#overridable
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def get_data_name (self, data):
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@ -208,7 +221,7 @@ class ExtractSubprocessor(Subprocessor):
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self.y = 0
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self.rect_size = 100
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self.rect_locked = False
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self.redraw_needed = True
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self.extract_needed = True
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io.progress_bar (None, len (self.input_data))
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@ -277,13 +290,12 @@ class ExtractSubprocessor(Subprocessor):
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if len (self.input_data) > 0:
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return self.input_data.pop(0)
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else:
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skip_remaining = False
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allow_remark_faces = False
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while len (self.input_data) > 0:
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data = self.input_data[0]
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filename, faces = data
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is_frame_done = False
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go_to_prev_frame = False
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# Can we mark an image that already has a marked face?
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if allow_remark_faces:
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@ -291,10 +303,9 @@ class ExtractSubprocessor(Subprocessor):
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# If there was already a face then lock the rectangle to it until the mouse is clicked
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if len(faces) > 0:
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self.rect, self.landmarks = faces.pop()
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self.rect_locked = True
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self.redraw_needed = True
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faces.clear()
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self.extract_needed = True
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self.rect_locked = True
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self.rect_size = ( self.rect[2] - self.rect[0] ) / 2
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self.x = ( self.rect[0] + self.rect[2] ) / 2
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self.y = ( self.rect[1] + self.rect[3] ) / 2
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@ -333,6 +344,8 @@ class ExtractSubprocessor(Subprocessor):
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self.cache_text_lines_img = (sh, self.text_lines_img)
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while True:
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io.process_messages(0.0001)
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new_x = self.x
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new_y = self.y
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new_rect_size = self.rect_size
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@ -346,7 +359,7 @@ class ExtractSubprocessor(Subprocessor):
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new_rect_size = max (5, new_rect_size + diff*mod)
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elif ev == io.EVENT_LBUTTONDOWN:
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self.rect_locked = not self.rect_locked
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self.redraw_needed = True
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self.extract_needed = True
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elif not self.rect_locked:
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new_x = np.clip (x, 0, w-1) / self.view_scale
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new_y = np.clip (y, 0, h-1) / self.view_scale
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@ -355,28 +368,47 @@ class ExtractSubprocessor(Subprocessor):
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key, = key_events[-1] if len(key_events) > 0 else (0,)
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if key == ord('\r') or key == ord('\n'):
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faces.append ( [(self.rect), self.landmarks] )
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#confirm frame
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is_frame_done = True
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faces.append ( [(self.rect), self.landmarks] )
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break
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elif key == ord(' '):
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is_frame_done = True
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break
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elif key == ord('.'):
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allow_remark_faces = True
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# Only save the face if the rect is still locked
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if self.rect_locked:
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faces.append ( [(self.rect), self.landmarks] )
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#confirm skip frame
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is_frame_done = True
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break
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elif key == ord(',') and len(self.result) > 0:
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# Only save the face if the rect is still locked
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#go prev frame
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if self.rect_locked:
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# Only save the face if the rect is still locked
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faces.append ( [(self.rect), self.landmarks] )
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self.input_data.insert(0, self.result.pop() )
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io.progress_bar_inc(-1)
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allow_remark_faces = True
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self.extract_needed = True
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self.rect_locked = False
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break
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elif key == ord('.'):
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#go next frame
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is_frame_done = True
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allow_remark_faces = True
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if self.rect_locked:
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# Only save the face if the rect is still locked
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faces.append ( [(self.rect), self.landmarks] )
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go_to_prev_frame = True
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break
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elif key == ord('q'):
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skip_remaining = True
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#skip remaining
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if self.rect_locked:
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faces.append ( [(self.rect), self.landmarks] )
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while len(self.input_data) > 0:
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self.result.append( self.input_data.pop(0) )
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io.progress_bar_inc(1)
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break
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elif key == ord('h'):
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self.hide_help = not self.hide_help
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break
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@ -384,7 +416,7 @@ class ExtractSubprocessor(Subprocessor):
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if self.x != new_x or \
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self.y != new_y or \
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self.rect_size != new_rect_size or \
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self.redraw_needed:
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self.extract_needed:
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self.x = new_x
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self.y = new_y
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self.rect_size = new_rect_size
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@ -396,7 +428,6 @@ class ExtractSubprocessor(Subprocessor):
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return [filename, [self.rect]]
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io.process_messages(0.0001)
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else:
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is_frame_done = True
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@ -404,20 +435,8 @@ class ExtractSubprocessor(Subprocessor):
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self.result.append ( data )
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self.input_data.pop(0)
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io.progress_bar_inc(1)
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self.redraw_needed = True
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self.extract_needed = True
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self.rect_locked = False
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elif go_to_prev_frame:
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self.input_data.insert(0, self.result.pop() )
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io.progress_bar_inc(-1)
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allow_remark_faces = True
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self.redraw_needed = True
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self.rect_locked = False
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elif skip_remaining:
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if self.rect_locked:
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faces.append ( [(self.rect), self.landmarks] )
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while len(self.input_data) > 0:
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self.result.append( self.input_data.pop(0) )
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io.progress_bar_inc(1)
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return None
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@ -457,11 +476,11 @@ class ExtractSubprocessor(Subprocessor):
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image = cv2.warpAffine(image, mat,(w,h) )
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view_landmarks = LandmarksProcessor.transform_points (view_landmarks, mat)
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image = LandmarksProcessor.draw_rect_landmarks (image, view_rect, view_landmarks, self.image_size, self.face_type)
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LandmarksProcessor.draw_rect_landmarks (image, view_rect, view_landmarks, self.image_size, self.face_type)
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if self.rect_locked:
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image = LandmarksProcessor.draw_landmarks(image, view_landmarks, (255,255,0) )
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self.redraw_needed = False
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LandmarksProcessor.draw_landmarks(image, view_landmarks, (255,255,0) )
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self.extract_needed = False
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io.show_image (self.wnd_name, image)
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else:
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287
mainscripts/LabelingTool_unfinished.py
Normal file
287
mainscripts/LabelingTool_unfinished.py
Normal file
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@ -0,0 +1,287 @@
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import traceback
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import os
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import sys
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import time
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import numpy as np
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import numpy.linalg as npl
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import cv2
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from pathlib import Path
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from interact import interact as io
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from utils.cv2_utils import *
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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 facelib import LandmarksProcessor
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def main(input_dir, output_dir):
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input_path = Path(input_dir)
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output_path = Path(output_dir)
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if not input_path.exists():
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raise ValueError('Input directory not found. Please ensure it exists.')
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if not output_path.exists():
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output_path.mkdir(parents=True)
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wnd_name = "Labeling tool"
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io.named_window (wnd_name)
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io.capture_mouse(wnd_name)
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io.capture_keys(wnd_name)
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#for filename in io.progress_bar_generator (Path_utils.get_image_paths(input_path), desc="Labeling"):
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for filename in Path_utils.get_image_paths(input_path):
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filepath = Path(filename)
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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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lmrks = dflimg.get_landmarks()
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lmrks_list = lmrks.tolist()
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orig_img = cv2_imread(str(filepath))
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h,w,c = orig_img.shape
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mask_orig = LandmarksProcessor.get_image_hull_mask( orig_img.shape, lmrks).astype(np.uint8)[:,:,0]
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ero_dil_rate = w // 8
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mask_ero = cv2.erode (mask_orig, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(ero_dil_rate,ero_dil_rate)), iterations = 1 )
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mask_dil = cv2.dilate(mask_orig, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(ero_dil_rate,ero_dil_rate)), iterations = 1 )
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#mask_bg = np.zeros(orig_img.shape[:2],np.uint8)
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mask_bg = 1-mask_dil
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mask_bgp = np.ones(orig_img.shape[:2],np.uint8) #default - all background possible
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mask_fg = np.zeros(orig_img.shape[:2],np.uint8)
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mask_fgp = np.zeros(orig_img.shape[:2],np.uint8)
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img = orig_img.copy()
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l_thick=2
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def draw_4_lines (masks_out, pts, thickness=1):
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fgp,fg,bg,bgp = masks_out
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h,w = fg.shape
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fgp_pts = []
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fg_pts = np.array([ pts[i:i+2] for i in range(len(pts)-1)])
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bg_pts = []
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bgp_pts = []
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for i in range(len(fg_pts)):
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a, b = line = fg_pts[i]
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ba = b-a
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v = ba / npl.norm(ba)
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ccpv = np.array([v[1],-v[0]])
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cpv = np.array([-v[1],v[0]])
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step = 1 / max(np.abs(cpv))
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fgp_pts.append ( np.clip (line + ccpv * step * thickness, 0, w-1 ).astype(np.int) )
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bg_pts.append ( np.clip (line + cpv * step * thickness, 0, w-1 ).astype(np.int) )
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bgp_pts.append ( np.clip (line + cpv * step * thickness * 2, 0, w-1 ).astype(np.int) )
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fgp_pts = np.array(fgp_pts)
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bg_pts = np.array(bg_pts)
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bgp_pts = np.array(bgp_pts)
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cv2.polylines(fgp, fgp_pts, False, (1,), thickness=thickness)
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cv2.polylines(fg, fg_pts, False, (1,), thickness=thickness)
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cv2.polylines(bg, bg_pts, False, (1,), thickness=thickness)
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cv2.polylines(bgp, bgp_pts, False, (1,), thickness=thickness)
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def draw_lines ( masks_steps, pts, thickness=1):
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lines = np.array([ pts[i:i+2] for i in range(len(pts)-1)])
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for mask, step in masks_steps:
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h,w = mask.shape
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mask_lines = []
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for i in range(len(lines)):
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a, b = line = lines[i]
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ba = b-a
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ba_len = npl.norm(ba)
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if ba_len != 0:
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v = ba / ba_len
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pv = np.array([-v[1],v[0]])
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pv_inv_max = 1 / max(np.abs(pv))
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mask_lines.append ( np.clip (line + pv * pv_inv_max * thickness * step, 0, w-1 ).astype(np.int) )
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else:
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mask_lines.append ( np.array(line, dtype=np.int) )
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cv2.polylines(mask, mask_lines, False, (1,), thickness=thickness)
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def draw_fill_convex( mask_out, pts, scale=1.0 ):
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hull = cv2.convexHull(np.array(pts))
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if scale !=1.0:
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pts_count = hull.shape[0]
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sum_x = np.sum(hull[:, 0, 0])
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sum_y = np.sum(hull[:, 0, 1])
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hull_center = np.array([sum_x/pts_count, sum_y/pts_count])
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hull = hull_center+(hull-hull_center)*scale
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hull = hull.astype(pts.dtype)
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cv2.fillConvexPoly( mask_out, hull, (1,) )
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def get_gc_mask_bgr(gc_mask):
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h, w = gc_mask.shape
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bgr = np.zeros( (h,w,3), dtype=np.uint8 )
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bgr [ gc_mask == 0 ] = (0,0,0)
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bgr [ gc_mask == 1 ] = (255,255,255)
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bgr [ gc_mask == 2 ] = (0,0,255) #RED
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bgr [ gc_mask == 3 ] = (0,255,0) #GREEN
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return bgr
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def get_gc_mask_result(gc_mask):
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return np.where((gc_mask==1) + (gc_mask==3),1,0).astype(np.int)
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#convex inner of right chin to end of right eyebrow
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#draw_fill_convex ( mask_fgp, lmrks_list[8:17]+lmrks_list[26:27] )
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#convex inner of start right chin to right eyebrow
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#draw_fill_convex ( mask_fgp, lmrks_list[8:9]+lmrks_list[22:27] )
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#convex inner of nose
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draw_fill_convex ( mask_fgp, lmrks[27:36] )
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#convex inner of nose half
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draw_fill_convex ( mask_fg, lmrks[27:36], scale=0.5 )
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#left corner of mouth to left corner of nose
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#draw_lines ( [ (mask_fg,0), ], lmrks_list[49:50]+lmrks_list[32:33], l_thick)
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#convex inner: right corner of nose to centers of eyebrows
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#draw_fill_convex ( mask_fgp, lmrks_list[35:36]+lmrks_list[19:20]+lmrks_list[24:25])
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||||
|
||||
#right corner of mouth to right corner of nose
|
||||
#draw_lines ( [ (mask_fg,0), ], lmrks_list[54:55]+lmrks_list[35:36], l_thick)
|
||||
|
||||
#left eye
|
||||
#draw_fill_convex ( mask_fg, lmrks_list[36:40] )
|
||||
#right eye
|
||||
#draw_fill_convex ( mask_fg, lmrks_list[42:48] )
|
||||
|
||||
#right chin
|
||||
draw_lines ( [ (mask_bg,0), (mask_fg,-1), ], lmrks[8:17], l_thick)
|
||||
|
||||
#left eyebrow center to right eyeprow center
|
||||
draw_lines ( [ (mask_bg,-1), (mask_fg,0), ], lmrks_list[19:20] + lmrks_list[24:25], l_thick)
|
||||
# #draw_lines ( [ (mask_bg,-1), (mask_fg,0), ], lmrks_list[24:25] + lmrks_list[19:17:-1], l_thick)
|
||||
|
||||
#half right eyebrow to end of right chin
|
||||
draw_lines ( [ (mask_bg,-1), (mask_fg,0), ], lmrks_list[24:27] + lmrks_list[16:17], l_thick)
|
||||
|
||||
#import code
|
||||
#code.interact(local=dict(globals(), **locals()))
|
||||
|
||||
#compose mask layers
|
||||
gc_mask = np.zeros(orig_img.shape[:2],np.uint8)
|
||||
gc_mask [ mask_bgp==1 ] = 2
|
||||
gc_mask [ mask_fgp==1 ] = 3
|
||||
gc_mask [ mask_bg==1 ] = 0
|
||||
gc_mask [ mask_fg==1 ] = 1
|
||||
|
||||
gc_bgr_before = get_gc_mask_bgr (gc_mask)
|
||||
|
||||
|
||||
|
||||
#io.show_image (wnd_name, gc_mask )
|
||||
|
||||
##points, hierarcy = cv2.findContours(original_mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
|
||||
##gc_mask = ( (1-erode_mask)*2 + erode_mask )# * dilate_mask
|
||||
#gc_mask = (1-erode_mask)*2 + erode_mask
|
||||
#cv2.addWeighted(
|
||||
#gc_mask = mask_0_27 + (1-mask_0_27)*2
|
||||
#
|
||||
##import code
|
||||
##code.interact(local=dict(globals(), **locals()))
|
||||
#
|
||||
#rect = (1,1,img.shape[1]-2,img.shape[0]-2)
|
||||
#
|
||||
#
|
||||
cv2.grabCut(img,gc_mask,None,np.zeros((1,65),np.float64),np.zeros((1,65),np.float64),5, cv2.GC_INIT_WITH_MASK)
|
||||
|
||||
gc_bgr = get_gc_mask_bgr (gc_mask)
|
||||
gc_mask_result = get_gc_mask_result(gc_mask)
|
||||
gc_mask_result_1 = gc_mask_result[:,:,np.newaxis]
|
||||
|
||||
#import code
|
||||
#code.interact(local=dict(globals(), **locals()))
|
||||
orig_img_gc_layers_masked = (0.5*orig_img + 0.5*gc_bgr).astype(np.uint8)
|
||||
orig_img_gc_before_layers_masked = (0.5*orig_img + 0.5*gc_bgr_before).astype(np.uint8)
|
||||
|
||||
|
||||
|
||||
pink_bg = np.full ( orig_img.shape, (255,0,255), dtype=np.uint8 )
|
||||
|
||||
|
||||
orig_img_result = orig_img * gc_mask_result_1
|
||||
orig_img_result_pinked = orig_img_result + pink_bg * (1-gc_mask_result_1)
|
||||
|
||||
#io.show_image (wnd_name, blended_img)
|
||||
|
||||
##gc_mask, bgdModel, fgdModel =
|
||||
#
|
||||
#mask2 = np.where((gc_mask==1) + (gc_mask==3),255,0).astype('uint8')[:,:,np.newaxis]
|
||||
#mask2 = np.repeat(mask2, (3,), -1)
|
||||
#
|
||||
##mask2 = np.where(gc_mask!=0,255,0).astype('uint8')
|
||||
#blended_img = orig_img #-\
|
||||
# #0.3 * np.full(original_img.shape, (50,50,50)) * (1-mask_0_27)[:,:,np.newaxis]
|
||||
# #0.3 * np.full(original_img.shape, (50,50,50)) * (1-dilate_mask)[:,:,np.newaxis] +\
|
||||
# #0.3 * np.full(original_img.shape, (50,50,50)) * (erode_mask)[:,:,np.newaxis]
|
||||
#blended_img = np.clip(blended_img, 0, 255).astype(np.uint8)
|
||||
##import code
|
||||
##code.interact(local=dict(globals(), **locals()))
|
||||
orig_img_lmrked = orig_img.copy()
|
||||
LandmarksProcessor.draw_landmarks(orig_img_lmrked, lmrks, transparent_mask=True)
|
||||
|
||||
screen = np.concatenate ([orig_img_gc_before_layers_masked,
|
||||
orig_img_gc_layers_masked,
|
||||
orig_img,
|
||||
orig_img_lmrked,
|
||||
orig_img_result_pinked,
|
||||
orig_img_result,
|
||||
], axis=1)
|
||||
|
||||
io.show_image (wnd_name, screen.astype(np.uint8) )
|
||||
|
||||
|
||||
while True:
|
||||
io.process_messages()
|
||||
|
||||
for (x,y,ev,flags) in io.get_mouse_events(wnd_name):
|
||||
pass
|
||||
#print (x,y,ev,flags)
|
||||
|
||||
key_events = [ ev for ev, in io.get_key_events(wnd_name) ]
|
||||
for key in key_events:
|
||||
if key == ord('1'):
|
||||
pass
|
||||
if key == ord('2'):
|
||||
pass
|
||||
if key == ord('3'):
|
||||
pass
|
||||
|
||||
if ord(' ') in key_events:
|
||||
break
|
||||
|
||||
import code
|
||||
code.interact(local=dict(globals(), **locals()))
|
||||
|
||||
|
||||
|
||||
|
||||
#original_mask = np.ones(original_img.shape[:2],np.uint8)*2
|
||||
#cv2.drawContours(original_mask, points, -1, (1,), 1)
|
||||
|
|
@ -63,7 +63,7 @@ def add_landmarks_debug_images(input_path):
|
|||
|
||||
if img is not None:
|
||||
face_landmarks = dflimg.get_landmarks()
|
||||
img = LandmarksProcessor.draw_landmarks(img, face_landmarks, transparent_mask=True)
|
||||
LandmarksProcessor.draw_landmarks(img, face_landmarks, transparent_mask=True)
|
||||
|
||||
output_file = '{}{}'.format( str(Path(str(input_path)) / filepath.stem), '_debug.jpg')
|
||||
cv2_imwrite(output_file, img, [int(cv2.IMWRITE_JPEG_QUALITY), 50] )
|
||||
|
|
|
|||
|
|
@ -48,13 +48,13 @@ class SampleProcessor(object):
|
|||
is_face_sample = sample.landmarks is not None
|
||||
|
||||
if debug and is_face_sample:
|
||||
sample_bgr = LandmarksProcessor.draw_landmarks (sample_bgr, sample.landmarks, (0, 1, 0))
|
||||
LandmarksProcessor.draw_landmarks (sample_bgr, sample.landmarks, (0, 1, 0))
|
||||
|
||||
close_sample = sample.close_target_list[ np.random.randint(0, len(sample.close_target_list)) ] if sample.close_target_list is not None else None
|
||||
close_sample_bgr = close_sample.load_bgr() if close_sample is not None else None
|
||||
|
||||
if debug and close_sample_bgr is not None:
|
||||
close_sample_bgr = LandmarksProcessor.draw_landmarks (close_sample_bgr, close_sample.landmarks, (0, 1, 0))
|
||||
LandmarksProcessor.draw_landmarks (close_sample_bgr, close_sample.landmarks, (0, 1, 0))
|
||||
|
||||
params = image_utils.gen_warp_params(sample_bgr, sample_process_options.random_flip, rotation_range=sample_process_options.rotation_range, scale_range=sample_process_options.scale_range, tx_range=sample_process_options.tx_range, ty_range=sample_process_options.ty_range )
|
||||
|
||||
|
|
|
|||
|
|
@ -108,12 +108,11 @@ class DFLJPG(object):
|
|||
|
||||
return inst
|
||||
except Exception as e:
|
||||
raise Exception("Corrupted JPG file: %s" % (str(e)))
|
||||
|
||||
return None
|
||||
raise Exception ("Corrupted JPG file: %s" % (str(e)))
|
||||
|
||||
@staticmethod
|
||||
def load(filename):
|
||||
try:
|
||||
inst = DFLJPG.load_raw (filename)
|
||||
inst.dfl_dict = None
|
||||
|
||||
|
|
@ -144,6 +143,9 @@ class DFLJPG(object):
|
|||
return None
|
||||
|
||||
return inst
|
||||
except Exception as e:
|
||||
print (e)
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def embed_data(filename, face_type=None,
|
||||
|
|
|
|||
|
|
@ -249,6 +249,7 @@ class DFLPNG(object):
|
|||
|
||||
@staticmethod
|
||||
def load(filename):
|
||||
try:
|
||||
inst = DFLPNG.load_raw (filename)
|
||||
inst.fcwp_dict = inst.getDFLDictData()
|
||||
|
||||
|
|
@ -259,6 +260,9 @@ class DFLPNG(object):
|
|||
return None
|
||||
|
||||
return inst
|
||||
except Exception as e:
|
||||
print(e)
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def embed_data(filename, face_type=None,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue