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Shift masking features to face_masking.py
This commit is contained in:
KRSHH
parent
d8fc1ffa04
commit
ab3b73631b
580
modules/processors/frame/face_masking.py
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580
modules/processors/frame/face_masking.py
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@ -0,0 +1,580 @@
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import cv2
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import numpy as np
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from modules.typing import Face, Frame
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import modules.globals
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def apply_color_transfer(source, target):
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"""
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Apply color transfer from target to source image
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"""
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source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
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target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
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source_mean, source_std = cv2.meanStdDev(source)
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target_mean, target_std = cv2.meanStdDev(target)
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# Reshape mean and std to be broadcastable
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source_mean = source_mean.reshape(1, 1, 3)
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source_std = source_std.reshape(1, 1, 3)
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target_mean = target_mean.reshape(1, 1, 3)
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target_std = target_std.reshape(1, 1, 3)
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# Perform the color transfer
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source = (source - source_mean) * (target_std / source_std) + target_mean
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return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)
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def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
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mask = np.zeros(frame.shape[:2], dtype=np.uint8)
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landmarks = face.landmark_2d_106
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if landmarks is not None:
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# Convert landmarks to int32
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landmarks = landmarks.astype(np.int32)
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# Extract facial features
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right_side_face = landmarks[0:16]
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left_side_face = landmarks[17:32]
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right_eye = landmarks[33:42]
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right_eye_brow = landmarks[43:51]
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left_eye = landmarks[87:96]
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left_eye_brow = landmarks[97:105]
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# Calculate forehead extension
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right_eyebrow_top = np.min(right_eye_brow[:, 1])
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left_eyebrow_top = np.min(left_eye_brow[:, 1])
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eyebrow_top = min(right_eyebrow_top, left_eyebrow_top)
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face_top = np.min([right_side_face[0, 1], left_side_face[-1, 1]])
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forehead_height = face_top - eyebrow_top
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extended_forehead_height = int(forehead_height * 5.0) # Extend by 50%
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# Create forehead points
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forehead_left = right_side_face[0].copy()
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forehead_right = left_side_face[-1].copy()
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forehead_left[1] -= extended_forehead_height
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forehead_right[1] -= extended_forehead_height
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# Combine all points to create the face outline
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face_outline = np.vstack(
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[
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[forehead_left],
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right_side_face,
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left_side_face[::-1], # Reverse left side to create a continuous outline
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[forehead_right],
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]
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)
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# Calculate padding
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padding = int(
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np.linalg.norm(right_side_face[0] - left_side_face[-1]) * 0.05
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) # 5% of face width
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# Create a slightly larger convex hull for padding
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hull = cv2.convexHull(face_outline)
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hull_padded = []
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for point in hull:
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x, y = point[0]
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center = np.mean(face_outline, axis=0)
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direction = np.array([x, y]) - center
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direction = direction / np.linalg.norm(direction)
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padded_point = np.array([x, y]) + direction * padding
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hull_padded.append(padded_point)
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hull_padded = np.array(hull_padded, dtype=np.int32)
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# Fill the padded convex hull
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cv2.fillConvexPoly(mask, hull_padded, 255)
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# Smooth the mask edges
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mask = cv2.GaussianBlur(mask, (5, 5), 3)
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return mask
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def create_lower_mouth_mask(
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face: Face, frame: Frame
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) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
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mask = np.zeros(frame.shape[:2], dtype=np.uint8)
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mouth_cutout = None
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landmarks = face.landmark_2d_106
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if landmarks is not None:
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# 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
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lower_lip_order = [
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65,
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66,
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62,
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70,
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69,
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18,
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19,
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20,
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21,
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22,
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23,
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24,
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0,
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8,
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7,
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6,
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5,
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4,
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3,
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2,
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65,
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]
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lower_lip_landmarks = landmarks[lower_lip_order].astype(
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np.float32
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) # Use float for precise calculations
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# Calculate the center of the landmarks
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center = np.mean(lower_lip_landmarks, axis=0)
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# Expand the landmarks outward
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expansion_factor = (
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1 + modules.globals.mask_down_size
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) # Adjust this for more or less expansion
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expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
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# Extend the top lip part
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toplip_indices = [
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20,
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0,
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1,
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2,
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3,
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4,
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5,
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] # Indices for landmarks 2, 65, 66, 62, 70, 69, 18
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toplip_extension = (
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modules.globals.mask_size * 0.5
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) # Adjust this factor to control the extension
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for idx in toplip_indices:
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direction = expanded_landmarks[idx] - center
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direction = direction / np.linalg.norm(direction)
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expanded_landmarks[idx] += direction * toplip_extension
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# Extend the bottom part (chin area)
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chin_indices = [
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11,
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12,
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13,
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14,
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15,
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16,
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] # Indices for landmarks 21, 22, 23, 24, 0, 8
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chin_extension = 2 * 0.2 # Adjust this factor to control the extension
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for idx in chin_indices:
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expanded_landmarks[idx][1] += (
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expanded_landmarks[idx][1] - center[1]
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) * chin_extension
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# Convert back to integer coordinates
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expanded_landmarks = expanded_landmarks.astype(np.int32)
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# Calculate bounding box for the expanded lower mouth
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min_x, min_y = np.min(expanded_landmarks, axis=0)
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max_x, max_y = np.max(expanded_landmarks, axis=0)
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# Add some padding to the bounding box
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padding = int((max_x - min_x) * 0.1) # 10% padding
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min_x = max(0, min_x - padding)
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min_y = max(0, min_y - padding)
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max_x = min(frame.shape[1], max_x + padding)
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max_y = min(frame.shape[0], max_y + padding)
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# Ensure the bounding box dimensions are valid
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if max_x <= min_x or max_y <= min_y:
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if (max_x - min_x) <= 1:
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max_x = min_x + 1
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if (max_y - min_y) <= 1:
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max_y = min_y + 1
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# Create the mask
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mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
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cv2.fillPoly(mask_roi, [expanded_landmarks - [min_x, min_y]], 255)
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# Apply Gaussian blur to soften the mask edges
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mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
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# Place the mask ROI in the full-sized mask
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mask[min_y:max_y, min_x:max_x] = mask_roi
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# Extract the masked area from the frame
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mouth_cutout = frame[min_y:max_y, min_x:max_x].copy()
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# Return the expanded lower lip polygon in original frame coordinates
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lower_lip_polygon = expanded_landmarks
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return mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon
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def create_eyes_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
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mask = np.zeros(frame.shape[:2], dtype=np.uint8)
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eyes_cutout = None
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landmarks = face.landmark_2d_106
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if landmarks is not None:
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# Left eye landmarks (87-96) and right eye landmarks (33-42)
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left_eye = landmarks[87:96]
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right_eye = landmarks[33:42]
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# Calculate centers and dimensions for each eye
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left_eye_center = np.mean(left_eye, axis=0).astype(np.int32)
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right_eye_center = np.mean(right_eye, axis=0).astype(np.int32)
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# Calculate eye dimensions
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def get_eye_dimensions(eye_points):
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x_coords = eye_points[:, 0]
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y_coords = eye_points[:, 1]
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width = int((np.max(x_coords) - np.min(x_coords)) * (1 + modules.globals.mask_down_size))
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height = int((np.max(y_coords) - np.min(y_coords)) * (1 + modules.globals.mask_down_size))
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return width, height
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left_width, left_height = get_eye_dimensions(left_eye)
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right_width, right_height = get_eye_dimensions(right_eye)
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# Add extra padding
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padding = int(max(left_width, right_width) * 0.2)
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# Calculate bounding box for both eyes
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min_x = min(left_eye_center[0] - left_width//2, right_eye_center[0] - right_width//2) - padding
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max_x = max(left_eye_center[0] + left_width//2, right_eye_center[0] + right_width//2) + padding
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min_y = min(left_eye_center[1] - left_height//2, right_eye_center[1] - right_height//2) - padding
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max_y = max(left_eye_center[1] + left_height//2, right_eye_center[1] + right_height//2) + padding
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# Ensure coordinates are within frame bounds
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min_x = max(0, min_x)
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min_y = max(0, min_y)
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max_x = min(frame.shape[1], max_x)
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max_y = min(frame.shape[0], max_y)
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# Create mask for the eyes region
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mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
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# Draw ellipses for both eyes
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left_center = (left_eye_center[0] - min_x, left_eye_center[1] - min_y)
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right_center = (right_eye_center[0] - min_x, right_eye_center[1] - min_y)
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# Calculate axes lengths (half of width and height)
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left_axes = (left_width//2, left_height//2)
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right_axes = (right_width//2, right_height//2)
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# Draw filled ellipses
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cv2.ellipse(mask_roi, left_center, left_axes, 0, 0, 360, 255, -1)
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cv2.ellipse(mask_roi, right_center, right_axes, 0, 0, 360, 255, -1)
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# Apply Gaussian blur to soften mask edges
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mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
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# Place the mask ROI in the full-sized mask
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mask[min_y:max_y, min_x:max_x] = mask_roi
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# Extract the masked area from the frame
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eyes_cutout = frame[min_y:max_y, min_x:max_x].copy()
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# Create polygon points for visualization
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def create_ellipse_points(center, axes):
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t = np.linspace(0, 2*np.pi, 32)
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x = center[0] + axes[0] * np.cos(t)
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y = center[1] + axes[1] * np.sin(t)
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return np.column_stack((x, y)).astype(np.int32)
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# Generate points for both ellipses
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left_points = create_ellipse_points((left_eye_center[0], left_eye_center[1]), (left_width//2, left_height//2))
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right_points = create_ellipse_points((right_eye_center[0], right_eye_center[1]), (right_width//2, right_height//2))
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# Combine points for both eyes
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eyes_polygon = np.vstack([left_points, right_points])
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return mask, eyes_cutout, (min_x, min_y, max_x, max_y), eyes_polygon
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def create_eyebrows_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
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mask = np.zeros(frame.shape[:2], dtype=np.uint8)
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eyebrows_cutout = None
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landmarks = face.landmark_2d_106
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if landmarks is not None:
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# Left eyebrow landmarks (97-105) and right eyebrow landmarks (43-51)
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left_eyebrow = landmarks[97:105].astype(np.float32)
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right_eyebrow = landmarks[43:51].astype(np.float32)
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# Calculate centers and dimensions for each eyebrow
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left_center = np.mean(left_eyebrow, axis=0)
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right_center = np.mean(right_eyebrow, axis=0)
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# Calculate bounding box with padding
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all_points = np.vstack([left_eyebrow, right_eyebrow])
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min_x = np.min(all_points[:, 0]) - 25
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max_x = np.max(all_points[:, 0]) + 25
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min_y = np.min(all_points[:, 1]) - 20
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max_y = np.max(all_points[:, 1]) + 15
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# Ensure coordinates are within frame bounds
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min_x = max(0, int(min_x))
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min_y = max(0, int(min_y))
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max_x = min(frame.shape[1], int(max_x))
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max_y = min(frame.shape[0], int(max_y))
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# Create mask for the eyebrows region
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mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
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try:
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# Convert points to local coordinates
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left_local = left_eyebrow - [min_x, min_y]
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right_local = right_eyebrow - [min_x, min_y]
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def create_curved_eyebrow(points):
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if len(points) >= 5:
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# Sort points by x-coordinate
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sorted_idx = np.argsort(points[:, 0])
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sorted_points = points[sorted_idx]
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# Calculate dimensions
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x_min, y_min = np.min(sorted_points, axis=0)
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x_max, y_max = np.max(sorted_points, axis=0)
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width = x_max - x_min
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height = y_max - y_min
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# Create more points for smoother curve
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num_points = 50
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x = np.linspace(x_min, x_max, num_points)
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# Fit cubic curve through points for more natural arch
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coeffs = np.polyfit(sorted_points[:, 0], sorted_points[:, 1], 3)
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y = np.polyval(coeffs, x)
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# Create points for top and bottom curves with varying offsets
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top_offset = np.linspace(height * 0.4, height * 0.3, num_points) # Varying offset for more natural shape
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bottom_offset = np.linspace(height * 0.2, height * 0.15, num_points)
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# Add some randomness to the offsets for more natural look
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top_offset += np.random.normal(0, height * 0.02, num_points)
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bottom_offset += np.random.normal(0, height * 0.01, num_points)
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# Smooth the offsets
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top_offset = cv2.GaussianBlur(top_offset.reshape(-1, 1), (1, 3), 1).reshape(-1)
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bottom_offset = cv2.GaussianBlur(bottom_offset.reshape(-1, 1), (1, 3), 1).reshape(-1)
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top_curve = y - top_offset
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bottom_curve = y + bottom_offset
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# Create curved endpoints
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end_points = 5
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start_curve = np.column_stack((
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np.linspace(x[0] - width * 0.05, x[0], end_points),
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np.linspace(bottom_curve[0], top_curve[0], end_points)
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))
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end_curve = np.column_stack((
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np.linspace(x[-1], x[-1] + width * 0.05, end_points),
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np.linspace(bottom_curve[-1], top_curve[-1], end_points)
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))
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# Combine all points to form a smooth contour
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contour_points = np.vstack([
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start_curve,
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np.column_stack((x, top_curve)),
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end_curve,
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np.column_stack((x[::-1], bottom_curve[::-1]))
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])
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# Add padding and smooth the shape
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center = np.mean(contour_points, axis=0)
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vectors = contour_points - center
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padded_points = center + vectors * 1.2 # 20% padding
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# Convert to integer coordinates and draw
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cv2.fillPoly(mask_roi, [padded_points.astype(np.int32)], 255)
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return padded_points
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return points
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# Generate and draw eyebrow shapes
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left_shape = create_curved_eyebrow(left_local)
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right_shape = create_curved_eyebrow(right_local)
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# Apply multi-stage blurring for natural feathering
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# First, strong Gaussian blur for initial softening
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mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
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# Second, medium blur for transition areas
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mask_roi = cv2.GaussianBlur(mask_roi, (11, 11), 3)
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# Finally, light blur for fine details
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mask_roi = cv2.GaussianBlur(mask_roi, (5, 5), 1)
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# Normalize mask values
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mask_roi = cv2.normalize(mask_roi, None, 0, 255, cv2.NORM_MINMAX)
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# Place the mask ROI in the full-sized mask
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mask[min_y:max_y, min_x:max_x] = mask_roi
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# Extract the masked area from the frame
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eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
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# Combine points for visualization
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eyebrows_polygon = np.vstack([
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left_shape + [min_x, min_y],
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right_shape + [min_x, min_y]
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]).astype(np.int32)
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except Exception as e:
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# Fallback to simple polygons if curve fitting fails
|
||||
left_local = left_eyebrow - [min_x, min_y]
|
||||
right_local = right_eyebrow - [min_x, min_y]
|
||||
cv2.fillPoly(mask_roi, [left_local.astype(np.int32)], 255)
|
||||
cv2.fillPoly(mask_roi, [right_local.astype(np.int32)], 255)
|
||||
mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
|
||||
mask[min_y:max_y, min_x:max_x] = mask_roi
|
||||
eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
|
||||
eyebrows_polygon = np.vstack([left_eyebrow, right_eyebrow]).astype(np.int32)
|
||||
|
||||
return mask, eyebrows_cutout, (min_x, min_y, max_x, max_y), eyebrows_polygon
|
||||
|
||||
def apply_mask_area(
|
||||
frame: np.ndarray,
|
||||
cutout: np.ndarray,
|
||||
box: tuple,
|
||||
face_mask: np.ndarray,
|
||||
polygon: np.ndarray,
|
||||
) -> np.ndarray:
|
||||
min_x, min_y, max_x, max_y = box
|
||||
box_width = max_x - min_x
|
||||
box_height = max_y - min_y
|
||||
|
||||
if (
|
||||
cutout is None
|
||||
or box_width is None
|
||||
or box_height is None
|
||||
or face_mask is None
|
||||
or polygon is None
|
||||
):
|
||||
return frame
|
||||
|
||||
try:
|
||||
resized_cutout = cv2.resize(cutout, (box_width, box_height))
|
||||
roi = frame[min_y:max_y, min_x:max_x]
|
||||
|
||||
if roi.shape != resized_cutout.shape:
|
||||
resized_cutout = cv2.resize(
|
||||
resized_cutout, (roi.shape[1], roi.shape[0])
|
||||
)
|
||||
|
||||
color_corrected_area = apply_color_transfer(resized_cutout, roi)
|
||||
|
||||
# Create mask for the area
|
||||
polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
|
||||
|
||||
# Split points for left and right parts if needed
|
||||
if len(polygon) > 50: # Arbitrary threshold to detect if we have multiple parts
|
||||
mid_point = len(polygon) // 2
|
||||
left_points = polygon[:mid_point] - [min_x, min_y]
|
||||
right_points = polygon[mid_point:] - [min_x, min_y]
|
||||
cv2.fillPoly(polygon_mask, [left_points], 255)
|
||||
cv2.fillPoly(polygon_mask, [right_points], 255)
|
||||
else:
|
||||
adjusted_polygon = polygon - [min_x, min_y]
|
||||
cv2.fillPoly(polygon_mask, [adjusted_polygon], 255)
|
||||
|
||||
# Apply strong initial feathering
|
||||
polygon_mask = cv2.GaussianBlur(polygon_mask, (21, 21), 7)
|
||||
|
||||
# Apply additional feathering
|
||||
feather_amount = min(
|
||||
30,
|
||||
box_width // modules.globals.mask_feather_ratio,
|
||||
box_height // modules.globals.mask_feather_ratio,
|
||||
)
|
||||
feathered_mask = cv2.GaussianBlur(
|
||||
polygon_mask.astype(float), (0, 0), feather_amount
|
||||
)
|
||||
feathered_mask = feathered_mask / feathered_mask.max()
|
||||
|
||||
# Apply additional smoothing to the mask edges
|
||||
feathered_mask = cv2.GaussianBlur(feathered_mask, (5, 5), 1)
|
||||
|
||||
face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
|
||||
combined_mask = feathered_mask * (face_mask_roi / 255.0)
|
||||
|
||||
combined_mask = combined_mask[:, :, np.newaxis]
|
||||
blended = (
|
||||
color_corrected_area * combined_mask + roi * (1 - combined_mask)
|
||||
).astype(np.uint8)
|
||||
|
||||
# Apply face mask to blended result
|
||||
face_mask_3channel = (
|
||||
np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
|
||||
)
|
||||
final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
|
||||
|
||||
frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
return frame
|
||||
|
||||
def draw_mask_visualization(
|
||||
frame: Frame,
|
||||
mask_data: tuple,
|
||||
label: str,
|
||||
draw_method: str = "polygon"
|
||||
) -> Frame:
|
||||
mask, cutout, (min_x, min_y, max_x, max_y), polygon = mask_data
|
||||
|
||||
vis_frame = frame.copy()
|
||||
|
||||
# Ensure coordinates are within frame bounds
|
||||
height, width = vis_frame.shape[:2]
|
||||
min_x, min_y = max(0, min_x), max(0, min_y)
|
||||
max_x, max_y = min(width, max_x), min(height, max_y)
|
||||
|
||||
if draw_method == "ellipse" and len(polygon) > 50: # For eyes
|
||||
# Split points for left and right parts
|
||||
mid_point = len(polygon) // 2
|
||||
left_points = polygon[:mid_point]
|
||||
right_points = polygon[mid_point:]
|
||||
|
||||
try:
|
||||
# Fit ellipses to points - need at least 5 points
|
||||
if len(left_points) >= 5 and len(right_points) >= 5:
|
||||
# Convert points to the correct format for ellipse fitting
|
||||
left_points = left_points.astype(np.float32)
|
||||
right_points = right_points.astype(np.float32)
|
||||
|
||||
# Fit ellipses
|
||||
left_ellipse = cv2.fitEllipse(left_points)
|
||||
right_ellipse = cv2.fitEllipse(right_points)
|
||||
|
||||
# Draw the ellipses
|
||||
cv2.ellipse(vis_frame, left_ellipse, (0, 255, 0), 2)
|
||||
cv2.ellipse(vis_frame, right_ellipse, (0, 255, 0), 2)
|
||||
except Exception as e:
|
||||
# If ellipse fitting fails, draw simple rectangles as fallback
|
||||
left_rect = cv2.boundingRect(left_points)
|
||||
right_rect = cv2.boundingRect(right_points)
|
||||
cv2.rectangle(vis_frame,
|
||||
(left_rect[0], left_rect[1]),
|
||||
(left_rect[0] + left_rect[2], left_rect[1] + left_rect[3]),
|
||||
(0, 255, 0), 2)
|
||||
cv2.rectangle(vis_frame,
|
||||
(right_rect[0], right_rect[1]),
|
||||
(right_rect[0] + right_rect[2], right_rect[1] + right_rect[3]),
|
||||
(0, 255, 0), 2)
|
||||
else: # For mouth and eyebrows
|
||||
# Draw the polygon
|
||||
if len(polygon) > 50: # If we have multiple parts
|
||||
mid_point = len(polygon) // 2
|
||||
left_points = polygon[:mid_point]
|
||||
right_points = polygon[mid_point:]
|
||||
cv2.polylines(vis_frame, [left_points], True, (0, 255, 0), 2, cv2.LINE_AA)
|
||||
cv2.polylines(vis_frame, [right_points], True, (0, 255, 0), 2, cv2.LINE_AA)
|
||||
else:
|
||||
cv2.polylines(vis_frame, [polygon], True, (0, 255, 0), 2, cv2.LINE_AA)
|
||||
|
||||
# Add label
|
||||
cv2.putText(
|
||||
vis_frame,
|
||||
label,
|
||||
(min_x, min_y - 10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX,
|
||||
0.5,
|
||||
(255, 255, 255),
|
||||
1,
|
||||
)
|
||||
|
||||
return vis_frame
|
||||
@ -14,6 +14,14 @@ from modules.utilities import (
|
||||
is_video,
|
||||
)
|
||||
from modules.cluster_analysis import find_closest_centroid
|
||||
from modules.processors.frame.face_masking import (
|
||||
create_face_mask,
|
||||
create_lower_mouth_mask,
|
||||
create_eyes_mask,
|
||||
create_eyebrows_mask,
|
||||
apply_mask_area,
|
||||
draw_mask_visualization
|
||||
)
|
||||
import os
|
||||
|
||||
FACE_SWAPPER = None
|
||||
@ -78,54 +86,58 @@ def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
|
||||
face_mask = create_face_mask(target_face, temp_frame)
|
||||
|
||||
if modules.globals.mouth_mask:
|
||||
# Create the mouth mask
|
||||
mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon = (
|
||||
create_lower_mouth_mask(target_face, temp_frame)
|
||||
)
|
||||
|
||||
# Apply the mouth area
|
||||
swapped_frame = apply_mouth_area(
|
||||
swapped_frame, mouth_cutout, mouth_box, face_mask, lower_lip_polygon
|
||||
# Create and apply mouth mask
|
||||
mouth_mask_data = create_lower_mouth_mask(target_face, temp_frame)
|
||||
swapped_frame = apply_mask_area(
|
||||
swapped_frame,
|
||||
mouth_mask_data[1], # mouth_cutout
|
||||
mouth_mask_data[2], # mouth_box
|
||||
face_mask,
|
||||
mouth_mask_data[3] # mouth_polygon
|
||||
)
|
||||
|
||||
if modules.globals.show_mouth_mask_box:
|
||||
mouth_mask_data = (mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon)
|
||||
swapped_frame = draw_mouth_mask_visualization(
|
||||
swapped_frame, target_face, mouth_mask_data
|
||||
swapped_frame = draw_mask_visualization(
|
||||
swapped_frame,
|
||||
mouth_mask_data,
|
||||
"Lower Mouth Mask"
|
||||
)
|
||||
|
||||
if modules.globals.eyes_mask:
|
||||
# Create the eyes mask
|
||||
eyes_mask, eyes_cutout, eyes_box, eyes_polygon = (
|
||||
create_eyes_mask(target_face, temp_frame)
|
||||
)
|
||||
|
||||
# Apply the eyes area
|
||||
swapped_frame = apply_eyes_area(
|
||||
swapped_frame, eyes_cutout, eyes_box, face_mask, eyes_polygon
|
||||
# Create and apply eyes mask
|
||||
eyes_mask_data = create_eyes_mask(target_face, temp_frame)
|
||||
swapped_frame = apply_mask_area(
|
||||
swapped_frame,
|
||||
eyes_mask_data[1], # eyes_cutout
|
||||
eyes_mask_data[2], # eyes_box
|
||||
face_mask,
|
||||
eyes_mask_data[3] # eyes_polygon
|
||||
)
|
||||
|
||||
if modules.globals.show_eyes_mask_box:
|
||||
eyes_mask_data = (eyes_mask, eyes_cutout, eyes_box, eyes_polygon)
|
||||
swapped_frame = draw_eyes_mask_visualization(
|
||||
swapped_frame, target_face, eyes_mask_data
|
||||
swapped_frame = draw_mask_visualization(
|
||||
swapped_frame,
|
||||
eyes_mask_data,
|
||||
"Eyes Mask",
|
||||
draw_method="ellipse"
|
||||
)
|
||||
|
||||
if modules.globals.eyebrows_mask:
|
||||
# Create the eyebrows mask
|
||||
eyebrows_mask, eyebrows_cutout, eyebrows_box, eyebrows_polygon = (
|
||||
create_eyebrows_mask(target_face, temp_frame)
|
||||
)
|
||||
|
||||
# Apply the eyebrows area
|
||||
swapped_frame = apply_eyebrows_area(
|
||||
swapped_frame, eyebrows_cutout, eyebrows_box, face_mask, eyebrows_polygon
|
||||
# Create and apply eyebrows mask
|
||||
eyebrows_mask_data = create_eyebrows_mask(target_face, temp_frame)
|
||||
swapped_frame = apply_mask_area(
|
||||
swapped_frame,
|
||||
eyebrows_mask_data[1], # eyebrows_cutout
|
||||
eyebrows_mask_data[2], # eyebrows_box
|
||||
face_mask,
|
||||
eyebrows_mask_data[3] # eyebrows_polygon
|
||||
)
|
||||
|
||||
if modules.globals.show_eyebrows_mask_box:
|
||||
eyebrows_mask_data = (eyebrows_mask, eyebrows_cutout, eyebrows_box, eyebrows_polygon)
|
||||
swapped_frame = draw_eyebrows_mask_visualization(
|
||||
swapped_frame, target_face, eyebrows_mask_data
|
||||
swapped_frame = draw_mask_visualization(
|
||||
swapped_frame,
|
||||
eyebrows_mask_data,
|
||||
"Eyebrows Mask"
|
||||
)
|
||||
|
||||
return swapped_frame
|
||||
@ -289,851 +301,3 @@ def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
|
||||
modules.processors.frame.core.process_video(
|
||||
source_path, temp_frame_paths, process_frames
|
||||
)
|
||||
|
||||
|
||||
def create_lower_mouth_mask(
|
||||
face: Face, frame: Frame
|
||||
) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
|
||||
mask = np.zeros(frame.shape[:2], dtype=np.uint8)
|
||||
mouth_cutout = None
|
||||
landmarks = face.landmark_2d_106
|
||||
if landmarks is not None:
|
||||
# 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
|
||||
lower_lip_order = [
|
||||
65,
|
||||
66,
|
||||
62,
|
||||
70,
|
||||
69,
|
||||
18,
|
||||
19,
|
||||
20,
|
||||
21,
|
||||
22,
|
||||
23,
|
||||
24,
|
||||
0,
|
||||
8,
|
||||
7,
|
||||
6,
|
||||
5,
|
||||
4,
|
||||
3,
|
||||
2,
|
||||
65,
|
||||
]
|
||||
lower_lip_landmarks = landmarks[lower_lip_order].astype(
|
||||
np.float32
|
||||
) # Use float for precise calculations
|
||||
|
||||
# Calculate the center of the landmarks
|
||||
center = np.mean(lower_lip_landmarks, axis=0)
|
||||
|
||||
# Expand the landmarks outward
|
||||
expansion_factor = (
|
||||
1 + modules.globals.mask_down_size
|
||||
) # Adjust this for more or less expansion
|
||||
expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
|
||||
|
||||
# Extend the top lip part
|
||||
toplip_indices = [
|
||||
20,
|
||||
0,
|
||||
1,
|
||||
2,
|
||||
3,
|
||||
4,
|
||||
5,
|
||||
] # Indices for landmarks 2, 65, 66, 62, 70, 69, 18
|
||||
toplip_extension = (
|
||||
modules.globals.mask_size * 0.5
|
||||
) # Adjust this factor to control the extension
|
||||
for idx in toplip_indices:
|
||||
direction = expanded_landmarks[idx] - center
|
||||
direction = direction / np.linalg.norm(direction)
|
||||
expanded_landmarks[idx] += direction * toplip_extension
|
||||
|
||||
# Extend the bottom part (chin area)
|
||||
chin_indices = [
|
||||
11,
|
||||
12,
|
||||
13,
|
||||
14,
|
||||
15,
|
||||
16,
|
||||
] # Indices for landmarks 21, 22, 23, 24, 0, 8
|
||||
chin_extension = 2 * 0.2 # Adjust this factor to control the extension
|
||||
for idx in chin_indices:
|
||||
expanded_landmarks[idx][1] += (
|
||||
expanded_landmarks[idx][1] - center[1]
|
||||
) * chin_extension
|
||||
|
||||
# Convert back to integer coordinates
|
||||
expanded_landmarks = expanded_landmarks.astype(np.int32)
|
||||
|
||||
# Calculate bounding box for the expanded lower mouth
|
||||
min_x, min_y = np.min(expanded_landmarks, axis=0)
|
||||
max_x, max_y = np.max(expanded_landmarks, axis=0)
|
||||
|
||||
# Add some padding to the bounding box
|
||||
padding = int((max_x - min_x) * 0.1) # 10% padding
|
||||
min_x = max(0, min_x - padding)
|
||||
min_y = max(0, min_y - padding)
|
||||
max_x = min(frame.shape[1], max_x + padding)
|
||||
max_y = min(frame.shape[0], max_y + padding)
|
||||
|
||||
# Ensure the bounding box dimensions are valid
|
||||
if max_x <= min_x or max_y <= min_y:
|
||||
if (max_x - min_x) <= 1:
|
||||
max_x = min_x + 1
|
||||
if (max_y - min_y) <= 1:
|
||||
max_y = min_y + 1
|
||||
|
||||
# Create the mask
|
||||
mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
|
||||
cv2.fillPoly(mask_roi, [expanded_landmarks - [min_x, min_y]], 255)
|
||||
|
||||
# Apply Gaussian blur to soften the mask edges
|
||||
mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
|
||||
|
||||
# Place the mask ROI in the full-sized mask
|
||||
mask[min_y:max_y, min_x:max_x] = mask_roi
|
||||
|
||||
# Extract the masked area from the frame
|
||||
mouth_cutout = frame[min_y:max_y, min_x:max_x].copy()
|
||||
|
||||
# Return the expanded lower lip polygon in original frame coordinates
|
||||
lower_lip_polygon = expanded_landmarks
|
||||
|
||||
return mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon
|
||||
|
||||
|
||||
def draw_mouth_mask_visualization(
|
||||
frame: Frame, face: Face, mouth_mask_data: tuple
|
||||
) -> Frame:
|
||||
landmarks = face.landmark_2d_106
|
||||
if landmarks is not None and mouth_mask_data is not None:
|
||||
mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon = (
|
||||
mouth_mask_data
|
||||
)
|
||||
|
||||
vis_frame = frame.copy()
|
||||
|
||||
# Ensure coordinates are within frame bounds
|
||||
height, width = vis_frame.shape[:2]
|
||||
min_x, min_y = max(0, min_x), max(0, min_y)
|
||||
max_x, max_y = min(width, max_x), min(height, max_y)
|
||||
|
||||
# Adjust mask to match the region size
|
||||
mask_region = mask[0 : max_y - min_y, 0 : max_x - min_x]
|
||||
|
||||
# Remove the color mask overlay
|
||||
# color_mask = cv2.applyColorMap((mask_region * 255).astype(np.uint8), cv2.COLORMAP_JET)
|
||||
|
||||
# Ensure shapes match before blending
|
||||
vis_region = vis_frame[min_y:max_y, min_x:max_x]
|
||||
# Remove blending with color_mask
|
||||
# if vis_region.shape[:2] == color_mask.shape[:2]:
|
||||
# blended = cv2.addWeighted(vis_region, 0.7, color_mask, 0.3, 0)
|
||||
# vis_frame[min_y:max_y, min_x:max_x] = blended
|
||||
|
||||
# Draw the lower lip polygon
|
||||
cv2.polylines(vis_frame, [lower_lip_polygon], True, (0, 255, 0), 2)
|
||||
|
||||
# Remove the red box
|
||||
# cv2.rectangle(vis_frame, (min_x, min_y), (max_x, max_y), (0, 0, 255), 2)
|
||||
|
||||
# Visualize the feathered mask
|
||||
feather_amount = max(
|
||||
1,
|
||||
min(
|
||||
30,
|
||||
(max_x - min_x) // modules.globals.mask_feather_ratio,
|
||||
(max_y - min_y) // modules.globals.mask_feather_ratio,
|
||||
),
|
||||
)
|
||||
# Ensure kernel size is odd
|
||||
kernel_size = 2 * feather_amount + 1
|
||||
feathered_mask = cv2.GaussianBlur(
|
||||
mask_region.astype(float), (kernel_size, kernel_size), 0
|
||||
)
|
||||
feathered_mask = (feathered_mask / feathered_mask.max() * 255).astype(np.uint8)
|
||||
# Remove the feathered mask color overlay
|
||||
# color_feathered_mask = cv2.applyColorMap(feathered_mask, cv2.COLORMAP_VIRIDIS)
|
||||
|
||||
# Ensure shapes match before blending feathered mask
|
||||
# if vis_region.shape == color_feathered_mask.shape:
|
||||
# blended_feathered = cv2.addWeighted(vis_region, 0.7, color_feathered_mask, 0.3, 0)
|
||||
# vis_frame[min_y:max_y, min_x:max_x] = blended_feathered
|
||||
|
||||
# Add labels
|
||||
cv2.putText(
|
||||
vis_frame,
|
||||
"Lower Mouth Mask",
|
||||
(min_x, min_y - 10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX,
|
||||
0.5,
|
||||
(255, 255, 255),
|
||||
1,
|
||||
)
|
||||
cv2.putText(
|
||||
vis_frame,
|
||||
"Feathered Mask",
|
||||
(min_x, max_y + 20),
|
||||
cv2.FONT_HERSHEY_SIMPLEX,
|
||||
0.5,
|
||||
(255, 255, 255),
|
||||
1,
|
||||
)
|
||||
|
||||
return vis_frame
|
||||
return frame
|
||||
|
||||
|
||||
def apply_mouth_area(
|
||||
frame: np.ndarray,
|
||||
mouth_cutout: np.ndarray,
|
||||
mouth_box: tuple,
|
||||
face_mask: np.ndarray,
|
||||
mouth_polygon: np.ndarray,
|
||||
) -> np.ndarray:
|
||||
min_x, min_y, max_x, max_y = mouth_box
|
||||
box_width = max_x - min_x
|
||||
box_height = max_y - min_y
|
||||
|
||||
if (
|
||||
mouth_cutout is None
|
||||
or box_width is None
|
||||
or box_height is None
|
||||
or face_mask is None
|
||||
or mouth_polygon is None
|
||||
):
|
||||
return frame
|
||||
|
||||
try:
|
||||
resized_mouth_cutout = cv2.resize(mouth_cutout, (box_width, box_height))
|
||||
roi = frame[min_y:max_y, min_x:max_x]
|
||||
|
||||
if roi.shape != resized_mouth_cutout.shape:
|
||||
resized_mouth_cutout = cv2.resize(
|
||||
resized_mouth_cutout, (roi.shape[1], roi.shape[0])
|
||||
)
|
||||
|
||||
color_corrected_mouth = apply_color_transfer(resized_mouth_cutout, roi)
|
||||
|
||||
# Use the provided mouth polygon to create the mask
|
||||
polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
|
||||
adjusted_polygon = mouth_polygon - [min_x, min_y]
|
||||
cv2.fillPoly(polygon_mask, [adjusted_polygon], 255)
|
||||
|
||||
# Apply feathering to the polygon mask
|
||||
feather_amount = min(
|
||||
30,
|
||||
box_width // modules.globals.mask_feather_ratio,
|
||||
box_height // modules.globals.mask_feather_ratio,
|
||||
)
|
||||
feathered_mask = cv2.GaussianBlur(
|
||||
polygon_mask.astype(float), (0, 0), feather_amount
|
||||
)
|
||||
feathered_mask = feathered_mask / feathered_mask.max()
|
||||
|
||||
face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
|
||||
combined_mask = feathered_mask * (face_mask_roi / 255.0)
|
||||
|
||||
combined_mask = combined_mask[:, :, np.newaxis]
|
||||
blended = (
|
||||
color_corrected_mouth * combined_mask + roi * (1 - combined_mask)
|
||||
).astype(np.uint8)
|
||||
|
||||
# Apply face mask to blended result
|
||||
face_mask_3channel = (
|
||||
np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
|
||||
)
|
||||
final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
|
||||
|
||||
frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
return frame
|
||||
|
||||
|
||||
def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
|
||||
mask = np.zeros(frame.shape[:2], dtype=np.uint8)
|
||||
landmarks = face.landmark_2d_106
|
||||
if landmarks is not None:
|
||||
# Convert landmarks to int32
|
||||
landmarks = landmarks.astype(np.int32)
|
||||
|
||||
# Extract facial features
|
||||
right_side_face = landmarks[0:16]
|
||||
left_side_face = landmarks[17:32]
|
||||
right_eye = landmarks[33:42]
|
||||
right_eye_brow = landmarks[43:51]
|
||||
left_eye = landmarks[87:96]
|
||||
left_eye_brow = landmarks[97:105]
|
||||
|
||||
# Calculate forehead extension
|
||||
right_eyebrow_top = np.min(right_eye_brow[:, 1])
|
||||
left_eyebrow_top = np.min(left_eye_brow[:, 1])
|
||||
eyebrow_top = min(right_eyebrow_top, left_eyebrow_top)
|
||||
|
||||
face_top = np.min([right_side_face[0, 1], left_side_face[-1, 1]])
|
||||
forehead_height = face_top - eyebrow_top
|
||||
extended_forehead_height = int(forehead_height * 5.0) # Extend by 50%
|
||||
|
||||
# Create forehead points
|
||||
forehead_left = right_side_face[0].copy()
|
||||
forehead_right = left_side_face[-1].copy()
|
||||
forehead_left[1] -= extended_forehead_height
|
||||
forehead_right[1] -= extended_forehead_height
|
||||
|
||||
# Combine all points to create the face outline
|
||||
face_outline = np.vstack(
|
||||
[
|
||||
[forehead_left],
|
||||
right_side_face,
|
||||
left_side_face[
|
||||
::-1
|
||||
], # Reverse left side to create a continuous outline
|
||||
[forehead_right],
|
||||
]
|
||||
)
|
||||
|
||||
# Calculate padding
|
||||
padding = int(
|
||||
np.linalg.norm(right_side_face[0] - left_side_face[-1]) * 0.05
|
||||
) # 5% of face width
|
||||
|
||||
# Create a slightly larger convex hull for padding
|
||||
hull = cv2.convexHull(face_outline)
|
||||
hull_padded = []
|
||||
for point in hull:
|
||||
x, y = point[0]
|
||||
center = np.mean(face_outline, axis=0)
|
||||
direction = np.array([x, y]) - center
|
||||
direction = direction / np.linalg.norm(direction)
|
||||
padded_point = np.array([x, y]) + direction * padding
|
||||
hull_padded.append(padded_point)
|
||||
|
||||
hull_padded = np.array(hull_padded, dtype=np.int32)
|
||||
|
||||
# Fill the padded convex hull
|
||||
cv2.fillConvexPoly(mask, hull_padded, 255)
|
||||
|
||||
# Smooth the mask edges
|
||||
mask = cv2.GaussianBlur(mask, (5, 5), 3)
|
||||
|
||||
return mask
|
||||
|
||||
|
||||
def apply_color_transfer(source, target):
|
||||
"""
|
||||
Apply color transfer from target to source image
|
||||
"""
|
||||
source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
|
||||
target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
|
||||
|
||||
source_mean, source_std = cv2.meanStdDev(source)
|
||||
target_mean, target_std = cv2.meanStdDev(target)
|
||||
|
||||
# Reshape mean and std to be broadcastable
|
||||
source_mean = source_mean.reshape(1, 1, 3)
|
||||
source_std = source_std.reshape(1, 1, 3)
|
||||
target_mean = target_mean.reshape(1, 1, 3)
|
||||
target_std = target_std.reshape(1, 1, 3)
|
||||
|
||||
# Perform the color transfer
|
||||
source = (source - source_mean) * (target_std / source_std) + target_mean
|
||||
|
||||
return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)
|
||||
|
||||
|
||||
def create_eyes_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
|
||||
mask = np.zeros(frame.shape[:2], dtype=np.uint8)
|
||||
eyes_cutout = None
|
||||
landmarks = face.landmark_2d_106
|
||||
if landmarks is not None:
|
||||
# Left eye landmarks (87-96) and right eye landmarks (33-42)
|
||||
left_eye = landmarks[87:96]
|
||||
right_eye = landmarks[33:42]
|
||||
|
||||
# Calculate centers and dimensions for each eye
|
||||
left_eye_center = np.mean(left_eye, axis=0).astype(np.int32)
|
||||
right_eye_center = np.mean(right_eye, axis=0).astype(np.int32)
|
||||
|
||||
# Calculate eye dimensions
|
||||
def get_eye_dimensions(eye_points):
|
||||
x_coords = eye_points[:, 0]
|
||||
y_coords = eye_points[:, 1]
|
||||
width = int((np.max(x_coords) - np.min(x_coords)) * (1 + modules.globals.mask_down_size))
|
||||
height = int((np.max(y_coords) - np.min(y_coords)) * (1 + modules.globals.mask_down_size))
|
||||
return width, height
|
||||
|
||||
left_width, left_height = get_eye_dimensions(left_eye)
|
||||
right_width, right_height = get_eye_dimensions(right_eye)
|
||||
|
||||
# Add extra padding
|
||||
padding = int(max(left_width, right_width) * 0.2)
|
||||
|
||||
# Calculate bounding box for both eyes
|
||||
min_x = min(left_eye_center[0] - left_width//2, right_eye_center[0] - right_width//2) - padding
|
||||
max_x = max(left_eye_center[0] + left_width//2, right_eye_center[0] + right_width//2) + padding
|
||||
min_y = min(left_eye_center[1] - left_height//2, right_eye_center[1] - right_height//2) - padding
|
||||
max_y = max(left_eye_center[1] + left_height//2, right_eye_center[1] + right_height//2) + padding
|
||||
|
||||
# Ensure coordinates are within frame bounds
|
||||
min_x = max(0, min_x)
|
||||
min_y = max(0, min_y)
|
||||
max_x = min(frame.shape[1], max_x)
|
||||
max_y = min(frame.shape[0], max_y)
|
||||
|
||||
# Create mask for the eyes region
|
||||
mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
|
||||
|
||||
# Draw ellipses for both eyes
|
||||
left_center = (left_eye_center[0] - min_x, left_eye_center[1] - min_y)
|
||||
right_center = (right_eye_center[0] - min_x, right_eye_center[1] - min_y)
|
||||
|
||||
# Calculate axes lengths (half of width and height)
|
||||
left_axes = (left_width//2, left_height//2)
|
||||
right_axes = (right_width//2, right_height//2)
|
||||
|
||||
# Draw filled ellipses
|
||||
cv2.ellipse(mask_roi, left_center, left_axes, 0, 0, 360, 255, -1)
|
||||
cv2.ellipse(mask_roi, right_center, right_axes, 0, 0, 360, 255, -1)
|
||||
|
||||
# Apply Gaussian blur to soften mask edges
|
||||
mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
|
||||
|
||||
# Place the mask ROI in the full-sized mask
|
||||
mask[min_y:max_y, min_x:max_x] = mask_roi
|
||||
|
||||
# Extract the masked area from the frame
|
||||
eyes_cutout = frame[min_y:max_y, min_x:max_x].copy()
|
||||
|
||||
# Create polygon points for visualization
|
||||
def create_ellipse_points(center, axes):
|
||||
t = np.linspace(0, 2*np.pi, 32)
|
||||
x = center[0] + axes[0] * np.cos(t)
|
||||
y = center[1] + axes[1] * np.sin(t)
|
||||
return np.column_stack((x, y)).astype(np.int32)
|
||||
|
||||
# Generate points for both ellipses
|
||||
left_points = create_ellipse_points((left_eye_center[0], left_eye_center[1]), (left_width//2, left_height//2))
|
||||
right_points = create_ellipse_points((right_eye_center[0], right_eye_center[1]), (right_width//2, right_height//2))
|
||||
|
||||
# Combine points for both eyes
|
||||
eyes_polygon = np.vstack([left_points, right_points])
|
||||
|
||||
return mask, eyes_cutout, (min_x, min_y, max_x, max_y), eyes_polygon
|
||||
|
||||
|
||||
def apply_eyes_area(
|
||||
frame: np.ndarray,
|
||||
eyes_cutout: np.ndarray,
|
||||
eyes_box: tuple,
|
||||
face_mask: np.ndarray,
|
||||
eyes_polygon: np.ndarray,
|
||||
) -> np.ndarray:
|
||||
min_x, min_y, max_x, max_y = eyes_box
|
||||
box_width = max_x - min_x
|
||||
box_height = max_y - min_y
|
||||
|
||||
if (
|
||||
eyes_cutout is None
|
||||
or box_width is None
|
||||
or box_height is None
|
||||
or face_mask is None
|
||||
or eyes_polygon is None
|
||||
):
|
||||
return frame
|
||||
|
||||
try:
|
||||
resized_eyes_cutout = cv2.resize(eyes_cutout, (box_width, box_height))
|
||||
roi = frame[min_y:max_y, min_x:max_x]
|
||||
|
||||
if roi.shape != resized_eyes_cutout.shape:
|
||||
resized_eyes_cutout = cv2.resize(
|
||||
resized_eyes_cutout, (roi.shape[1], roi.shape[0])
|
||||
)
|
||||
|
||||
color_corrected_eyes = apply_color_transfer(resized_eyes_cutout, roi)
|
||||
|
||||
# Create mask for both eyes
|
||||
polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
|
||||
|
||||
# Split points for left and right eyes
|
||||
mid_point = len(eyes_polygon) // 2
|
||||
left_eye_points = eyes_polygon[:mid_point] - [min_x, min_y]
|
||||
right_eye_points = eyes_polygon[mid_point:] - [min_x, min_y]
|
||||
|
||||
# Draw filled ellipses using points
|
||||
left_rect = cv2.minAreaRect(left_eye_points)
|
||||
right_rect = cv2.minAreaRect(right_eye_points)
|
||||
|
||||
# Convert rect to ellipse parameters
|
||||
def rect_to_ellipse_params(rect):
|
||||
center = rect[0]
|
||||
size = rect[1]
|
||||
angle = rect[2]
|
||||
return (int(center[0]), int(center[1])), (int(size[0]/2), int(size[1]/2)), angle
|
||||
|
||||
# Draw filled ellipses
|
||||
left_params = rect_to_ellipse_params(left_rect)
|
||||
right_params = rect_to_ellipse_params(right_rect)
|
||||
cv2.ellipse(polygon_mask, left_params[0], left_params[1], left_params[2], 0, 360, 255, -1)
|
||||
cv2.ellipse(polygon_mask, right_params[0], right_params[1], right_params[2], 0, 360, 255, -1)
|
||||
|
||||
# Apply feathering
|
||||
feather_amount = min(
|
||||
30,
|
||||
box_width // modules.globals.mask_feather_ratio,
|
||||
box_height // modules.globals.mask_feather_ratio,
|
||||
)
|
||||
feathered_mask = cv2.GaussianBlur(
|
||||
polygon_mask.astype(float), (0, 0), feather_amount
|
||||
)
|
||||
feathered_mask = feathered_mask / feathered_mask.max()
|
||||
|
||||
face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
|
||||
combined_mask = feathered_mask * (face_mask_roi / 255.0)
|
||||
|
||||
combined_mask = combined_mask[:, :, np.newaxis]
|
||||
blended = (
|
||||
color_corrected_eyes * combined_mask + roi * (1 - combined_mask)
|
||||
).astype(np.uint8)
|
||||
|
||||
# Apply face mask to blended result
|
||||
face_mask_3channel = (
|
||||
np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
|
||||
)
|
||||
final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
|
||||
|
||||
frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
return frame
|
||||
|
||||
|
||||
def draw_eyes_mask_visualization(
|
||||
frame: Frame, face: Face, eyes_mask_data: tuple
|
||||
) -> Frame:
|
||||
landmarks = face.landmark_2d_106
|
||||
if landmarks is not None and eyes_mask_data is not None:
|
||||
mask, eyes_cutout, (min_x, min_y, max_x, max_y), eyes_polygon = eyes_mask_data
|
||||
|
||||
vis_frame = frame.copy()
|
||||
|
||||
# Ensure coordinates are within frame bounds
|
||||
height, width = vis_frame.shape[:2]
|
||||
min_x, min_y = max(0, min_x), max(0, min_y)
|
||||
max_x, max_y = min(width, max_x), min(height, max_y)
|
||||
|
||||
# Draw the eyes ellipses
|
||||
mid_point = len(eyes_polygon) // 2
|
||||
left_points = eyes_polygon[:mid_point]
|
||||
right_points = eyes_polygon[mid_point:]
|
||||
|
||||
try:
|
||||
# Fit ellipses to points - need at least 5 points
|
||||
if len(left_points) >= 5 and len(right_points) >= 5:
|
||||
# Convert points to the correct format for ellipse fitting
|
||||
left_points = left_points.astype(np.float32)
|
||||
right_points = right_points.astype(np.float32)
|
||||
|
||||
# Fit ellipses
|
||||
left_ellipse = cv2.fitEllipse(left_points)
|
||||
right_ellipse = cv2.fitEllipse(right_points)
|
||||
|
||||
# Draw the ellipses
|
||||
cv2.ellipse(vis_frame, left_ellipse, (0, 255, 0), 2)
|
||||
cv2.ellipse(vis_frame, right_ellipse, (0, 255, 0), 2)
|
||||
except Exception as e:
|
||||
# If ellipse fitting fails, draw simple rectangles as fallback
|
||||
left_rect = cv2.boundingRect(left_points)
|
||||
right_rect = cv2.boundingRect(right_points)
|
||||
cv2.rectangle(vis_frame,
|
||||
(left_rect[0], left_rect[1]),
|
||||
(left_rect[0] + left_rect[2], left_rect[1] + left_rect[3]),
|
||||
(0, 255, 0), 2)
|
||||
cv2.rectangle(vis_frame,
|
||||
(right_rect[0], right_rect[1]),
|
||||
(right_rect[0] + right_rect[2], right_rect[1] + right_rect[3]),
|
||||
(0, 255, 0), 2)
|
||||
|
||||
# Add label
|
||||
cv2.putText(
|
||||
vis_frame,
|
||||
"Eyes Mask",
|
||||
(min_x, min_y - 10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX,
|
||||
0.5,
|
||||
(255, 255, 255),
|
||||
1,
|
||||
)
|
||||
|
||||
return vis_frame
|
||||
return frame
|
||||
|
||||
|
||||
def create_eyebrows_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
|
||||
mask = np.zeros(frame.shape[:2], dtype=np.uint8)
|
||||
eyebrows_cutout = None
|
||||
landmarks = face.landmark_2d_106
|
||||
if landmarks is not None:
|
||||
# Left eyebrow landmarks (97-105) and right eyebrow landmarks (43-51)
|
||||
left_eyebrow = landmarks[97:105].astype(np.float32)
|
||||
right_eyebrow = landmarks[43:51].astype(np.float32)
|
||||
|
||||
# Calculate centers and dimensions for each eyebrow
|
||||
left_center = np.mean(left_eyebrow, axis=0)
|
||||
right_center = np.mean(right_eyebrow, axis=0)
|
||||
|
||||
# Calculate bounding box with padding
|
||||
all_points = np.vstack([left_eyebrow, right_eyebrow])
|
||||
min_x = np.min(all_points[:, 0]) - 25
|
||||
max_x = np.max(all_points[:, 0]) + 25
|
||||
min_y = np.min(all_points[:, 1]) - 20
|
||||
max_y = np.max(all_points[:, 1]) + 15
|
||||
|
||||
# Ensure coordinates are within frame bounds
|
||||
min_x = max(0, int(min_x))
|
||||
min_y = max(0, int(min_y))
|
||||
max_x = min(frame.shape[1], int(max_x))
|
||||
max_y = min(frame.shape[0], int(max_y))
|
||||
|
||||
# Create mask for the eyebrows region
|
||||
mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
|
||||
|
||||
try:
|
||||
# Convert points to local coordinates
|
||||
left_local = left_eyebrow - [min_x, min_y]
|
||||
right_local = right_eyebrow - [min_x, min_y]
|
||||
|
||||
def create_curved_eyebrow(points):
|
||||
if len(points) >= 5:
|
||||
# Sort points by x-coordinate
|
||||
sorted_idx = np.argsort(points[:, 0])
|
||||
sorted_points = points[sorted_idx]
|
||||
|
||||
# Calculate dimensions
|
||||
x_min, y_min = np.min(sorted_points, axis=0)
|
||||
x_max, y_max = np.max(sorted_points, axis=0)
|
||||
width = x_max - x_min
|
||||
height = y_max - y_min
|
||||
|
||||
# Create more points for smoother curve
|
||||
num_points = 50
|
||||
x = np.linspace(x_min, x_max, num_points)
|
||||
|
||||
# Fit cubic curve through points for more natural arch
|
||||
coeffs = np.polyfit(sorted_points[:, 0], sorted_points[:, 1], 3)
|
||||
y = np.polyval(coeffs, x)
|
||||
|
||||
# Create points for top and bottom curves with varying offsets
|
||||
top_offset = np.linspace(height * 0.4, height * 0.3, num_points) # Varying offset for more natural shape
|
||||
bottom_offset = np.linspace(height * 0.2, height * 0.15, num_points)
|
||||
|
||||
# Add some randomness to the offsets for more natural look
|
||||
top_offset += np.random.normal(0, height * 0.02, num_points)
|
||||
bottom_offset += np.random.normal(0, height * 0.01, num_points)
|
||||
|
||||
# Smooth the offsets
|
||||
top_offset = cv2.GaussianBlur(top_offset.reshape(-1, 1), (1, 3), 1).reshape(-1)
|
||||
bottom_offset = cv2.GaussianBlur(bottom_offset.reshape(-1, 1), (1, 3), 1).reshape(-1)
|
||||
|
||||
top_curve = y - top_offset
|
||||
bottom_curve = y + bottom_offset
|
||||
|
||||
# Create curved endpoints
|
||||
end_points = 5
|
||||
start_curve = np.column_stack((
|
||||
np.linspace(x[0] - width * 0.05, x[0], end_points),
|
||||
np.linspace(bottom_curve[0], top_curve[0], end_points)
|
||||
))
|
||||
end_curve = np.column_stack((
|
||||
np.linspace(x[-1], x[-1] + width * 0.05, end_points),
|
||||
np.linspace(bottom_curve[-1], top_curve[-1], end_points)
|
||||
))
|
||||
|
||||
# Combine all points to form a smooth contour
|
||||
contour_points = np.vstack([
|
||||
start_curve,
|
||||
np.column_stack((x, top_curve)),
|
||||
end_curve,
|
||||
np.column_stack((x[::-1], bottom_curve[::-1]))
|
||||
])
|
||||
|
||||
# Add padding and smooth the shape
|
||||
center = np.mean(contour_points, axis=0)
|
||||
vectors = contour_points - center
|
||||
padded_points = center + vectors * 1.2 # 20% padding
|
||||
|
||||
# Convert to integer coordinates and draw
|
||||
cv2.fillPoly(mask_roi, [padded_points.astype(np.int32)], 255)
|
||||
|
||||
return padded_points
|
||||
return points
|
||||
|
||||
# Generate and draw eyebrow shapes
|
||||
left_shape = create_curved_eyebrow(left_local)
|
||||
right_shape = create_curved_eyebrow(right_local)
|
||||
|
||||
# Apply multi-stage blurring for natural feathering
|
||||
# First, strong Gaussian blur for initial softening
|
||||
mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
|
||||
|
||||
# Second, medium blur for transition areas
|
||||
mask_roi = cv2.GaussianBlur(mask_roi, (11, 11), 3)
|
||||
|
||||
# Finally, light blur for fine details
|
||||
mask_roi = cv2.GaussianBlur(mask_roi, (5, 5), 1)
|
||||
|
||||
# Normalize mask values
|
||||
mask_roi = cv2.normalize(mask_roi, None, 0, 255, cv2.NORM_MINMAX)
|
||||
|
||||
# Place the mask ROI in the full-sized mask
|
||||
mask[min_y:max_y, min_x:max_x] = mask_roi
|
||||
|
||||
# Extract the masked area from the frame
|
||||
eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
|
||||
|
||||
# Combine points for visualization
|
||||
eyebrows_polygon = np.vstack([
|
||||
left_shape + [min_x, min_y],
|
||||
right_shape + [min_x, min_y]
|
||||
]).astype(np.int32)
|
||||
|
||||
except Exception as e:
|
||||
# Fallback to simple polygons if curve fitting fails
|
||||
left_local = left_eyebrow - [min_x, min_y]
|
||||
right_local = right_eyebrow - [min_x, min_y]
|
||||
cv2.fillPoly(mask_roi, [left_local.astype(np.int32)], 255)
|
||||
cv2.fillPoly(mask_roi, [right_local.astype(np.int32)], 255)
|
||||
mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
|
||||
mask[min_y:max_y, min_x:max_x] = mask_roi
|
||||
eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
|
||||
eyebrows_polygon = np.vstack([left_eyebrow, right_eyebrow]).astype(np.int32)
|
||||
|
||||
return mask, eyebrows_cutout, (min_x, min_y, max_x, max_y), eyebrows_polygon
|
||||
|
||||
|
||||
def apply_eyebrows_area(
|
||||
frame: np.ndarray,
|
||||
eyebrows_cutout: np.ndarray,
|
||||
eyebrows_box: tuple,
|
||||
face_mask: np.ndarray,
|
||||
eyebrows_polygon: np.ndarray,
|
||||
) -> np.ndarray:
|
||||
min_x, min_y, max_x, max_y = eyebrows_box
|
||||
box_width = max_x - min_x
|
||||
box_height = max_y - min_y
|
||||
|
||||
if (
|
||||
eyebrows_cutout is None
|
||||
or box_width is None
|
||||
or box_height is None
|
||||
or face_mask is None
|
||||
or eyebrows_polygon is None
|
||||
):
|
||||
return frame
|
||||
|
||||
try:
|
||||
resized_eyebrows_cutout = cv2.resize(eyebrows_cutout, (box_width, box_height))
|
||||
roi = frame[min_y:max_y, min_x:max_x]
|
||||
|
||||
if roi.shape != resized_eyebrows_cutout.shape:
|
||||
resized_eyebrows_cutout = cv2.resize(
|
||||
resized_eyebrows_cutout, (roi.shape[1], roi.shape[0])
|
||||
)
|
||||
|
||||
color_corrected_eyebrows = apply_color_transfer(resized_eyebrows_cutout, roi)
|
||||
|
||||
# Create mask for both eyebrows
|
||||
polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
|
||||
|
||||
# Split points for left and right eyebrows
|
||||
mid_point = len(eyebrows_polygon) // 2
|
||||
left_points = eyebrows_polygon[:mid_point] - [min_x, min_y]
|
||||
right_points = eyebrows_polygon[mid_point:] - [min_x, min_y]
|
||||
|
||||
# Draw filled polygons
|
||||
cv2.fillPoly(polygon_mask, [left_points], 255)
|
||||
cv2.fillPoly(polygon_mask, [right_points], 255)
|
||||
|
||||
# Apply strong initial feathering
|
||||
polygon_mask = cv2.GaussianBlur(polygon_mask, (21, 21), 7)
|
||||
|
||||
# Apply additional feathering
|
||||
feather_amount = min(
|
||||
30,
|
||||
box_width // modules.globals.mask_feather_ratio,
|
||||
box_height // modules.globals.mask_feather_ratio,
|
||||
)
|
||||
feathered_mask = cv2.GaussianBlur(
|
||||
polygon_mask.astype(float), (0, 0), feather_amount
|
||||
)
|
||||
feathered_mask = feathered_mask / feathered_mask.max()
|
||||
|
||||
# Apply additional smoothing to the mask edges
|
||||
feathered_mask = cv2.GaussianBlur(feathered_mask, (5, 5), 1)
|
||||
|
||||
face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
|
||||
combined_mask = feathered_mask * (face_mask_roi / 255.0)
|
||||
|
||||
combined_mask = combined_mask[:, :, np.newaxis]
|
||||
blended = (
|
||||
color_corrected_eyebrows * combined_mask + roi * (1 - combined_mask)
|
||||
).astype(np.uint8)
|
||||
|
||||
# Apply face mask to blended result
|
||||
face_mask_3channel = (
|
||||
np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
|
||||
)
|
||||
final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
|
||||
|
||||
frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
return frame
|
||||
|
||||
|
||||
def draw_eyebrows_mask_visualization(
|
||||
frame: Frame, face: Face, eyebrows_mask_data: tuple
|
||||
) -> Frame:
|
||||
landmarks = face.landmark_2d_106
|
||||
if landmarks is not None and eyebrows_mask_data is not None:
|
||||
mask, eyebrows_cutout, (min_x, min_y, max_x, max_y), eyebrows_polygon = eyebrows_mask_data
|
||||
|
||||
vis_frame = frame.copy()
|
||||
|
||||
# Ensure coordinates are within frame bounds
|
||||
height, width = vis_frame.shape[:2]
|
||||
min_x, min_y = max(0, min_x), max(0, min_y)
|
||||
max_x, max_y = min(width, max_x), min(height, max_y)
|
||||
|
||||
# Draw the eyebrows curves
|
||||
mid_point = len(eyebrows_polygon) // 2
|
||||
left_points = eyebrows_polygon[:mid_point]
|
||||
right_points = eyebrows_polygon[mid_point:]
|
||||
|
||||
# Draw smooth curves with anti-aliasing
|
||||
cv2.polylines(vis_frame, [left_points], True, (0, 255, 0), 2, cv2.LINE_AA)
|
||||
cv2.polylines(vis_frame, [right_points], True, (0, 255, 0), 2, cv2.LINE_AA)
|
||||
|
||||
# Add label
|
||||
cv2.putText(
|
||||
vis_frame,
|
||||
"Eyebrows Mask",
|
||||
(min_x, min_y - 10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX,
|
||||
0.5,
|
||||
(255, 255, 255),
|
||||
1,
|
||||
)
|
||||
|
||||
return vis_frame
|
||||
return frame
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user