├── Readme.md ├── camera.py ├── environment.yml ├── image.py ├── sample ├── 000.png ├── after.png ├── comparison.png ├── face.png ├── facial_landmarks.jpeg ├── mask.png └── output_video.mp4 └── utils.py /Readme.md: -------------------------------------------------------------------------------- 1 | # Virtual Makeup Using Mediapipe 2 | ## Clone and Run 3 | ``` 4 | git clone https://github.com/Jayanths9/Virtual_Makeup_opencv.git 5 | cd Virtual_Makeup_opencv 6 | conda env create -f environment.yml 7 | conda activate virtual_makeup 8 | ``` 9 | ### Run on Camera input 10 | ``` 11 | python camera.py 12 | ``` 13 | ### Run on sample image 14 | ``` 15 | python image.py --image sample/face.png 16 | ``` 17 | 18 | # Introduction 19 | 20 | In this project Mediapipe [1] facial landmarks and opencv is used to add makeup on facial features. 21 | - Mediapipe facial landmark library detects the face in the image and returns 478 landmarks on human face. (x,y) coordinates of each points is obtained w.r.t the image size. 22 | 23 |

24 | Landmarks image 25 |
26 | Media pipe facial landmarks example [2] 27 |

28 | 29 | - From all the facial landmarks, extract Lips, Eyebrow, Eyeliner & Eyeshadow points and create a colored mask with respect to the input image. 30 | 31 |

32 | mask 33 |
34 | Colored Mask for Lips, Eyebrow, Eyeliner & Eyeshadow 35 |

36 | 37 | - Blend the Original image and the mask with respect to its weights to add makeup on the original image. 38 | 39 |

40 | mask 41 |
42 | Original image and Transformed Image with Makeup [3] 43 |

44 | 45 | - Virtual Makeup on video. 46 | 47 |

48 | 49 | Watch the video 50 |
51 | Virtal makeup on video [4] 52 | 53 | 54 |

55 | 56 | # Refrences 57 | 1. https://ai.google.dev/edge/mediapipe/solutions/vision/face_landmarker 58 | 2. https://medium.com/@hotakoma/mediapipe-landmark-face-hand-pose-sequence-number-list-view-778364d6c414 59 | 3. https://i.pinimg.com/originals/a9/93/7d/a9937d95f962f477c486d701a5152752.jpg 60 | 4. https://www.pexels.com/video/attractive-woman-looking-at-the-camera-7048981/ 61 | 62 | --- 63 | Author: 64 | Jayanth S 65 | universitat Bremen, Bremen 66 | -------------------------------------------------------------------------------- /camera.py: -------------------------------------------------------------------------------- 1 | from utils import * 2 | 3 | # features to add makeup 4 | face_elements = [ 5 | "LIP_LOWER", 6 | "LIP_UPPER", 7 | "EYEBROW_LEFT", 8 | "EYEBROW_RIGHT", 9 | "EYELINER_LEFT", 10 | "EYELINER_RIGHT", 11 | "EYESHADOW_LEFT", 12 | "EYESHADOW_RIGHT", 13 | ] 14 | 15 | # change the color of features 16 | colors_map = { 17 | # upper lip and lower lips 18 | "LIP_UPPER": [0, 0, 255], # Red in BGR 19 | "LIP_LOWER": [0, 0, 255], # Red in BGR 20 | # eyeliner 21 | "EYELINER_LEFT": [139, 0, 0], # Dark Blue in BGR 22 | "EYELINER_RIGHT": [139, 0, 0], # Dark Blue in BGR 23 | # eye shadow 24 | "EYESHADOW_LEFT": [0, 100, 0], # Dark Green in BGR 25 | "EYESHADOW_RIGHT": [0, 100, 0], # Dark Green in BGR 26 | # eye brow 27 | "EYEBROW_LEFT": [19, 69, 139], # Dark Brown in BGR 28 | "EYEBROW_RIGHT": [19, 69, 139], # Dark Brown in BGR 29 | } 30 | 31 | 32 | face_connections=[face_points[idx] for idx in face_elements] 33 | colors=[colors_map[idx] for idx in face_elements] 34 | 35 | video_capture = cv2.VideoCapture(0) 36 | while True: 37 | # read image from camera 38 | success, image = video_capture.read() 39 | image = cv2.flip(image, 1) 40 | # if input from camera 41 | if success: 42 | # create a empty mask like image 43 | mask = np.zeros_like(image) 44 | # extract facial landmarks 45 | face_landmarks = read_landmarks(image=image) 46 | # create mask for facial features with color 47 | mask = add_mask( 48 | mask, 49 | idx_to_coordinates=face_landmarks, 50 | face_connections=face_connections,colors=colors 51 | ) 52 | # combine the image and mask with w.r.to weights 53 | output = cv2.addWeighted(image, 1.0, mask, 0.2, 1.0) 54 | cv2.imshow("Feature", output) 55 | # press q to exit the cv2 window 56 | if cv2.waitKey(100) & 0xFF == ord("q"): 57 | break 58 | video_capture.release() 59 | cv2.destroyAllWindows() 60 | -------------------------------------------------------------------------------- /environment.yml: -------------------------------------------------------------------------------- 1 | name: virtual_makeup 2 | channels: 3 | - defaults 4 | dependencies: 5 | - _libgcc_mutex=0.1 6 | - _openmp_mutex=5.1 7 | - bzip2=1.0.8 8 | - ca-certificates=2024.3.11 9 | - ld_impl_linux-64=2.38 10 | - libffi=3.4.4 11 | - libgcc-ng=11.2.0 12 | - libgomp=11.2.0 13 | - libstdcxx-ng=11.2.0 14 | - libuuid=1.41.5 15 | - ncurses=6.4 16 | - openssl=3.0.13 17 | - pip=24.0 18 | - python=3.11.9 19 | - readline=8.2 20 | - setuptools=69.5.1 21 | - sqlite=3.45.3 22 | - tk=8.6.14 23 | - tzdata=2024a 24 | - wheel=0.43.0 25 | - xz=5.4.6 26 | - zlib=1.2.13 27 | - pip: 28 | - absl-py==2.1.0 29 | - attrs==23.2.0 30 | - cffi==1.16.0 31 | - contourpy==1.2.1 32 | - cycler==0.12.1 33 | - flatbuffers==24.3.25 34 | - fonttools==4.52.4 35 | - jax==0.4.28 36 | - jaxlib==0.4.28 37 | - kiwisolver==1.4.5 38 | - matplotlib==3.9.0 39 | - mediapipe==0.10.14 40 | - ml-dtypes==0.4.0 41 | - numpy==1.26.4 42 | - opencv-contrib-python==4.9.0.80 43 | - opt-einsum==3.3.0 44 | - packaging==24.0 45 | - pillow==10.3.0 46 | - protobuf==4.25.3 47 | - pycparser==2.22 48 | - pyparsing==3.1.2 49 | - python-dateutil==2.9.0.post0 50 | - scipy==1.13.1 51 | - six==1.16.0 52 | - sounddevice==0.4.7 53 | -------------------------------------------------------------------------------- /image.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | import argparse 3 | from utils import * 4 | 5 | 6 | # features to add makeup 7 | face_elements = [ 8 | "LIP_LOWER", 9 | "LIP_UPPER", 10 | "EYEBROW_LEFT", 11 | "EYEBROW_RIGHT", 12 | "EYELINER_LEFT", 13 | "EYELINER_RIGHT", 14 | "EYESHADOW_LEFT", 15 | "EYESHADOW_RIGHT", 16 | ] 17 | 18 | # change the color of features 19 | colors_map = { 20 | # upper lip and lower lips 21 | "LIP_UPPER": [0, 0, 255], # Red in BGR 22 | "LIP_LOWER": [0, 0, 255], # Red in BGR 23 | # eyeliner 24 | "EYELINER_LEFT": [139, 0, 0], # Dark Blue in BGR 25 | "EYELINER_RIGHT": [139, 0, 0], # Dark Blue in BGR 26 | # eye shadow 27 | "EYESHADOW_LEFT": [0, 100, 0], # Dark Green in BGR 28 | "EYESHADOW_RIGHT": [0, 100, 0], # Dark Green in BGR 29 | # eye brow 30 | "EYEBROW_LEFT": [19, 69, 139], # Dark Brown in BGR 31 | "EYEBROW_RIGHT": [19, 69, 139], # Dark Brown in BGR 32 | } 33 | 34 | 35 | def main(image_path): 36 | # extract required facial points from face_elements 37 | face_connections=[face_points[idx] for idx in face_elements] 38 | # extract corresponding colors for each facial features 39 | colors=[colors_map[idx] for idx in face_elements] 40 | # read image 41 | image = cv2.imread(image_path) 42 | # create a empty mask like image 43 | mask = np.zeros_like(image) 44 | # extract facial landmarks 45 | face_landmarks = read_landmarks(image=image) 46 | # create mask for facial features with color 47 | mask = add_mask( 48 | mask, 49 | idx_to_coordinates=face_landmarks, 50 | face_connections=face_connections,colors=colors 51 | ) 52 | # combine the image and mask with w.r.to weights 53 | output = cv2.addWeighted(image, 1.0, mask, 0.2, 1.0) 54 | # display the image 55 | show_image(output) 56 | 57 | if __name__ == "__main__": 58 | # argument parser 59 | parser = argparse.ArgumentParser(description="Image to add Facial makeup ") 60 | # add image path as argumment 61 | parser.add_argument("--img", type=str, help="Path to the image.") 62 | args = parser.parse_args() 63 | main(args.img) 64 | -------------------------------------------------------------------------------- /sample/000.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Jayanths9/Virtual_Makeup/0bb60d8e6318d5538c7ddca73e1832c7915c5ed4/sample/000.png -------------------------------------------------------------------------------- /sample/after.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Jayanths9/Virtual_Makeup/0bb60d8e6318d5538c7ddca73e1832c7915c5ed4/sample/after.png -------------------------------------------------------------------------------- /sample/comparison.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Jayanths9/Virtual_Makeup/0bb60d8e6318d5538c7ddca73e1832c7915c5ed4/sample/comparison.png -------------------------------------------------------------------------------- /sample/face.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Jayanths9/Virtual_Makeup/0bb60d8e6318d5538c7ddca73e1832c7915c5ed4/sample/face.png -------------------------------------------------------------------------------- /sample/facial_landmarks.jpeg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Jayanths9/Virtual_Makeup/0bb60d8e6318d5538c7ddca73e1832c7915c5ed4/sample/facial_landmarks.jpeg -------------------------------------------------------------------------------- /sample/mask.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Jayanths9/Virtual_Makeup/0bb60d8e6318d5538c7ddca73e1832c7915c5ed4/sample/mask.png -------------------------------------------------------------------------------- /sample/output_video.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Jayanths9/Virtual_Makeup/0bb60d8e6318d5538c7ddca73e1832c7915c5ed4/sample/output_video.mp4 -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import mediapipe as mp 3 | import cv2 4 | 5 | 6 | # landmarks of features from mediapipe 7 | face_points={ 8 | "BLUSH_LEFT": [50], 9 | "BLUSH_RIGHT": [280], 10 | "LEFT_EYE": [33, 246, 161, 160, 159, 158, 157, 173, 133, 155, 154, 153, 145, 144, 163, 7, 33], 11 | "RIGHT_EYE": [362, 298, 384, 385, 386, 387, 388, 466, 263, 249, 390, 373, 374, 380, 381, 382, 362], 12 | "EYELINER_LEFT": [243, 112, 26, 22, 23, 24, 110, 25, 226, 130, 33, 7, 163, 144, 145, 153, 154, 155, 133, 243], 13 | "EYELINER_RIGHT": [463, 362, 382, 381, 380, 374, 373, 390, 249, 263, 359, 446, 255, 339, 254, 253, 252, 256, 341, 463], 14 | "EYESHADOW_LEFT": [226, 247, 30, 29, 27, 28, 56, 190, 243, 173, 157, 158, 159, 160, 161, 246, 33, 130, 226], 15 | "EYESHADOW_RIGHT": [463, 414, 286, 258, 257, 259, 260, 467, 446, 359, 263, 466, 388, 387, 386, 385, 384, 398, 362, 463], 16 | "FACE": [152, 148, 176, 149, 150, 136, 172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109, 10, 338, 297, 332, 284, 251, 389, 454, 323, 401, 361, 435, 288, 397, 365, 379, 378, 400, 377, 152], 17 | "LIP_UPPER": [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291, 308, 415, 310, 312, 13, 82, 81, 80, 191, 78], 18 | "LIP_LOWER": [61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291, 308, 324, 402, 317, 14, 87, 178, 88, 95, 78, 61], 19 | "EYEBROW_LEFT": [55, 107, 66, 105, 63, 70, 46, 53, 52, 65, 55], 20 | "EYEBROW_RIGHT": [285, 336, 296, 334, 293, 300, 276, 283, 295, 285] 21 | } 22 | 23 | # initialize mediapipe functions 24 | mp_face_mesh = mp.solutions.face_mesh 25 | mp_drawing = mp.solutions.drawing_utils 26 | 27 | 28 | # to display image in cv2 window 29 | def show_image(image: np.array, msg: str = "Loaded Image"): 30 | """ 31 | image : image as np array 32 | msg : cv2 window name 33 | """ 34 | image_copy = image.copy() 35 | cv2.imshow(msg, image_copy) 36 | cv2.waitKey(0) 37 | cv2.destroyAllWindows() 38 | 39 | 40 | def read_landmarks(image: np.array): 41 | """ 42 | image : image as np.array 43 | """ 44 | landmark_cordinates = {} 45 | # load mediapipe facemesh and detect facial landmarks 46 | # face landmarks returns normalized points of all facial landmarks from 0 to 477 47 | with mp_face_mesh.FaceMesh(refine_landmarks=True) as face_mesh: 48 | results = face_mesh.process(image) 49 | face_landmarks = results.multi_face_landmarks[0].landmark 50 | 51 | # convert normalized points w.r.to image dimensions 52 | for idx, landmark in enumerate(face_landmarks): 53 | landmark_px = mp_drawing._normalized_to_pixel_coordinates( 54 | landmark.x, landmark.y, image.shape[1], image.shape[0] 55 | ) 56 | # create a map of facial landmarks to (x,y) coordinates 57 | if landmark_px: 58 | landmark_cordinates[idx] = landmark_px 59 | return landmark_cordinates 60 | 61 | 62 | # based on input facial features create make w.r.to colors 63 | def add_mask( 64 | mask: np.array, idx_to_coordinates: dict, face_connections: list, colors: list 65 | ): 66 | """ 67 | mask: image filled with 0's 68 | idx_to_coordinates : dict with (x,y) cordinates for each face landmarks 69 | face_connections : list of (x,y) cordinates for each facial features 70 | colors : list of [B,G,R] color for each features 71 | """ 72 | for i, connection in enumerate(face_connections): 73 | # extract (x,y) w.r.to image for each cordinates 74 | points = np.array([idx_to_coordinates[idx] for idx in connection]) 75 | # make a shape of feature in the mask and add color 76 | cv2.fillPoly(mask, [points], colors[i]) 77 | 78 | # smoothening of image 79 | mask = cv2.GaussianBlur(mask, (7, 7), 4) 80 | return mask --------------------------------------------------------------------------------