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import cv2
import gradio as gr
import mediapipe as mp
import dlib
import imutils
import numpy as np
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_face_mesh = mp.solutions.face_mesh
mp_face_detection = mp.solutions.face_detection
def apply_media_pipe_face_detection(image):
with mp_face_detection.FaceDetection(
model_selection=1, min_detection_confidence=0.5) as face_detection:
results = face_detection.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
if not results.detections:
return image
annotated_image = image.copy()
for detection in results.detections:
mp_drawing.draw_detection(annotated_image, detection)
return annotated_image
def apply_media_pipe_facemesh(image):
with mp_face_mesh.FaceMesh(
static_image_mode=True,
max_num_faces=1,
refine_landmarks=True,
min_detection_confidence=0.5) as face_mesh:
results = face_mesh.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
if not results.multi_face_landmarks:
return image
annotated_image = image.copy()
for face_landmarks in results.multi_face_landmarks:
mp_drawing.draw_landmarks(
image=annotated_image,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_TESSELATION,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles
.get_default_face_mesh_tesselation_style())
mp_drawing.draw_landmarks(
image=annotated_image,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_CONTOURS,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles
.get_default_face_mesh_contours_style())
mp_drawing.draw_landmarks(
image=annotated_image,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_IRISES,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles
.get_default_face_mesh_iris_connections_style())
return annotated_image
class FaceOrientation(object):
def __init__(self):
self.detect = dlib.get_frontal_face_detector()
self.predict = dlib.shape_predictor("model/shape_predictor_68_face_landmarks.dat")
def create_orientation(self, frame):
draw_rect1 = True
draw_rect2 = True
draw_lines = True
frame = imutils.resize(frame, width=800)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
subjects = self.detect(gray, 0)
for subject in subjects:
landmarks = self.predict(gray, subject)
size = frame.shape
# 2D image points. If you change the image, you need to change vector
image_points = np.array([
(landmarks.part(33).x, landmarks.part(33).y), # Nose tip
(landmarks.part(8).x, landmarks.part(8).y), # Chin
(landmarks.part(36).x, landmarks.part(36).y), # Left eye left corner
(landmarks.part(45).x, landmarks.part(45).y), # Right eye right corne
(landmarks.part(48).x, landmarks.part(48).y), # Left Mouth corner
(landmarks.part(54).x, landmarks.part(54).y) # Right mouth corner
], dtype="double")
# 3D model points.
model_points = np.array([
(0.0, 0.0, 0.0), # Nose tip
(0.0, -330.0, -65.0), # Chin
(-225.0, 170.0, -135.0), # Left eye left corner
(225.0, 170.0, -135.0), # Right eye right corne
(-150.0, -150.0, -125.0), # Left Mouth corner
(150.0, -150.0, -125.0) # Right mouth corner
])
# Camera internals
focal_length = size[1]
center = (size[1] / 2, size[0] / 2)
camera_matrix = np.array(
[[focal_length, 0, center[0]],
[0, focal_length, center[1]],
[0, 0, 1]], dtype="double"
)
dist_coeffs = np.zeros((4, 1)) # Assuming no lens distortion
(success, rotation_vector, translation_vector) = cv2.solvePnP(model_points, image_points, camera_matrix,
dist_coeffs)
(b1, jacobian) = cv2.projectPoints(np.array([(350.0, 270.0, 0.0)]), rotation_vector, translation_vector,
camera_matrix, dist_coeffs)
(b2, jacobian) = cv2.projectPoints(np.array([(-350.0, -270.0, 0.0)]), rotation_vector,
translation_vector, camera_matrix, dist_coeffs)
(b3, jacobian) = cv2.projectPoints(np.array([(-350.0, 270, 0.0)]), rotation_vector, translation_vector,
camera_matrix, dist_coeffs)
(b4, jacobian) = cv2.projectPoints(np.array([(350.0, -270.0, 0.0)]), rotation_vector,
translation_vector, camera_matrix, dist_coeffs)
(b11, jacobian) = cv2.projectPoints(np.array([(450.0, 350.0, 400.0)]), rotation_vector,
translation_vector, camera_matrix, dist_coeffs)
(b12, jacobian) = cv2.projectPoints(np.array([(-450.0, -350.0, 400.0)]), rotation_vector,
translation_vector, camera_matrix, dist_coeffs)
(b13, jacobian) = cv2.projectPoints(np.array([(-450.0, 350, 400.0)]), rotation_vector,
translation_vector, camera_matrix, dist_coeffs)
(b14, jacobian) = cv2.projectPoints(np.array([(450.0, -350.0, 400.0)]), rotation_vector,
translation_vector, camera_matrix, dist_coeffs)
b1 = (int(b1[0][0][0]), int(b1[0][0][1]))
b2 = (int(b2[0][0][0]), int(b2[0][0][1]))
b3 = (int(b3[0][0][0]), int(b3[0][0][1]))
b4 = (int(b4[0][0][0]), int(b4[0][0][1]))
b11 = (int(b11[0][0][0]), int(b11[0][0][1]))
b12 = (int(b12[0][0][0]), int(b12[0][0][1]))
b13 = (int(b13[0][0][0]), int(b13[0][0][1]))
b14 = (int(b14[0][0][0]), int(b14[0][0][1]))
if draw_rect1 == True:
cv2.line(frame, b1, b3, (255, 255, 0), 10)
cv2.line(frame, b3, b2, (255, 255, 0), 10)
cv2.line(frame, b2, b4, (255, 255, 0), 10)
cv2.line(frame, b4, b1, (255, 255, 0), 10)
if draw_rect2 == True:
cv2.line(frame, b11, b13, (255, 255, 0), 10)
cv2.line(frame, b13, b12, (255, 255, 0), 10)
cv2.line(frame, b12, b14, (255, 255, 0), 10)
cv2.line(frame, b14, b11, (255, 255, 0), 10)
if draw_lines == True:
cv2.line(frame, b11, b1, (0, 255, 0), 10)
cv2.line(frame, b13, b3, (0, 255, 0), 10)
cv2.line(frame, b12, b2, (0, 255, 0), 10)
cv2.line(frame, b14, b4, (0, 255, 0), 10)
return frame
face_orientation_obj = FaceOrientation()
class FaceProcessing(object):
def __init__(self, ui_obj):
self.name = "Face Image Processing"
self.description = "Call for Face Image and video Processing"
self.ui_obj = ui_obj
def take_webcam_photo(self, image):
return image
def take_webcam_video(self, images):
return images
def mp_webcam_photo(self, image):
return image
def mp_webcam_face_mesh(self, image):
face_mesh_image = apply_media_pipe_facemesh(image)
return face_mesh_image
def mp_webcam_face_detection(self, image):
face_detection_img = apply_media_pipe_face_detection(image)
return face_detection_img
def dlib_apply_face_orientation(self, image):
image = face_orientation_obj.create_orientation(image)
return image
def webcam_stream_update(self, video_frame):
video_out = face_orientation_obj.create_orientation(video_frame)
return video_out
def create_ui(self):
with self.ui_obj:
gr.Markdown("""
### 👨💻Made By Bishal Kumar Rauniyar👨💻
## Project: Face Processing based on DLIB Shape Predictor Model
""")
with gr.Tabs():
with gr.TabItem("Processing Webcam"):
with gr.Row():
webcam_image_in = gr.Image(label="Webcam Image Input")
webcam_video_in = gr.Video(label="Webcam Video Input")
with gr.Row():
webcam_photo_action = gr.Button("Take the Photo")
webcam_video_action = gr.Button("Take the Video")
with gr.Row():
webcam_photo_out = gr.Image(label="Webcam Photo Output")
webcam_video_out = gr.Video(label="Webcam Video")
with gr.TabItem("Mediapipe Facemesh with Webcam"):
with gr.Row():
with gr.Column():
mp_image_in = gr.Image(label="Webcam Image Input")
with gr.Column():
mp_photo_action = gr.Button("Take the Photo")
mp_apply_fm_action = gr.Button("Apply Face Mesh the Photo")
mp_apply_landmarks_action = gr.Button("Apply Face Landmarks the Photo")
with gr.Row():
mp_photo_out = gr.Image(label="Webcam Photo Output")
mp_fm_photo_out = gr.Image(label="Face Mesh Photo Output")
mp_lm_photo_out = gr.Image(label="Face Landmarks Photo Output")
with gr.TabItem("DLib Model Based Face Orientation"):
with gr.Row():
with gr.Column():
dlib_image_in = gr.Image(label="Webcam Image Input")
with gr.Column():
dlib_photo_action = gr.Button("Take the Photo")
dlib_apply_orientation_action = gr.Button("Apply Face Mesh the Photo")
with gr.Row():
dlib_photo_out = gr.Image(label="Webcam Photo Output")
dlib_orientation_photo_out = gr.Image(label="Face Mesh Photo Output")
with gr.TabItem("Face Orientation on Live Webcam Stream"):
with gr.Row():
webcam_stream_in = gr.Image(label="Webcam Stream Input",
streaming=True)
webcam_stream_out = gr.Image(label="Webcam Stream Output")
webcam_stream_in.change(
self.webcam_stream_update,
inputs=webcam_stream_in,
outputs=webcam_stream_out
)
dlib_photo_action.click(
self.mp_webcam_photo,
[
dlib_image_in
],
[
dlib_photo_out
]
)
dlib_apply_orientation_action.click(
self.dlib_apply_face_orientation,
[
dlib_image_in
],
[
dlib_orientation_photo_out
]
)
mp_photo_action.click(
self.mp_webcam_photo,
[
mp_image_in
],
[
mp_photo_out
]
)
mp_apply_fm_action.click(
self.mp_webcam_face_mesh,
[
mp_image_in
],
[
mp_fm_photo_out
]
)
mp_apply_landmarks_action.click(
self.mp_webcam_face_detection,
[
mp_image_in
],
[
mp_lm_photo_out
]
)
webcam_photo_action.click(
self.take_webcam_photo,
[
webcam_image_in
],
[
webcam_photo_out
]
)
webcam_video_action.click(
self.take_webcam_video,
[
webcam_video_in
],
[
webcam_video_out
]
)
def launch_ui(self):
self.ui_obj.launch()
if __name__ == '__main__':
my_app = gr.Blocks()
face_ui = FaceProcessing(my_app)
face_ui.create_ui()
face_ui.launch_ui() |