Real-Time Face Landmark Detection OpenCV Python With Source Code
The Real-Time Face Landmark Detection OpenCV Python was developed using Python OpenCV, Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.
A Face Landmark Detection OpenCV Python is the process of detecting landmarks or regions of interest (key-points) on the face like Eyebrows, Eyes, Nose, Mouth. In this article the system can detect the face of the human in real-time using web camera.
In this OpenCV Python Project also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.
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To start executing Real-Time Face Landmark Detection With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.
Real-Time Face Landmark Detection OpenCV Python With Source Code : Steps on how to run the project
Time needed: 5 minutes.
These are the steps on how to run Real-Time Face Landmark Detection OpenCV Python With Source Code
- Step 1: Download the given source code below.
First, download the given source code below and unzip the source code.
- Step 2: Import the project to your PyCharm IDE.
Next, import the source code you’ve download to your PyCharm IDE.
- Step 3: Run the project.
last, run the project with the command “py main.py”
Complete Source Code
cap = cv2.VideoCapture(0)
hog_face_detector = dlib.get_frontal_face_detector()
dlib_facelandmark = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
_, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = hog_face_detector(gray)
for face in faces:
face_landmarks = dlib_facelandmark(gray, face)
for n in range(0, 16):
x = face_landmarks.part(n).x
y = face_landmarks.part(n).y
cv2.circle(frame, (x, y), 1, (0, 255, 255), 1)
cv2.imshow("Face Landmarks", frame)
key = cv2.waitKey(1)
if key == 50:
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Download Source Code below
In this article, Left Eye Detection OpenCV Python most successful application of eye detection would probably be photo taking. When you take a photo of your friends, the eye detection algorithm built into your digital camera detects where the eyes are and adjusts the focus accordingly.
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