Python OpenCV Real Time projects
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The document provides step-by-step instructions for real-time face, eye, nose, and mouth detection projects using Python and OpenCV. It includes source code examples for each detection type, showcasing how to process video input and apply Haar Cascades for object detection. Contact information for the author, Amarjeet Singh Thakur, is also provided for further inquiries.
![Python programming with Open CV Page 3
Step2: Source Code
import numpy as np
import cv2 #Import Open Source Computer Vision Package
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
cap = cv2.VideoCapture(0) #Capture video from front camera of our laptop
while 1:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #By default in CV the image is read in BGR format
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2) #Rectangular box size initialization
roi_gray = gray[y:y + h, x:x + w]
roi_color = img[y:y + h, x:x + w]
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
cv2.imshow('img', img)
k = cv2.waitKey(30) & 0xff # cv2.waitKey() will show the image for assigned time duration
if k == 27: #If user presses Esc Key then video capturing will be terminated
break
cap.release() #Its mandatory to release video capture
cv2.destroyAllWindows()#Once the task completes then we will close all the opened windows
Step3: Run the code
Result:
1. Showing my face and eyes detected and enclosed in a box](https://image.slidesharecdn.com/opencvprojects-200531075224/85/Python-OpenCV-Real-Time-projects-3-320.jpg)
Python OpenCV Real Time projects
- 1. Python programming with Open CV Page 1 " PYTHON OPEnCV real time Projects " Prepared by: AMARjeetsingh thakur
- 2. Python programming with Open CV Page 2 1.The Face & Eyes Detection Step1: Open The Pycharm IDE
- 3. Python programming with Open CV Page 3 Step2: Source Code import numpy as np import cv2 #Import Open Source Computer Vision Package face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') cap = cv2.VideoCapture(0) #Capture video from front camera of our laptop while 1: ret, img = cap.read() gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #By default in CV the image is read in BGR format faces = face_cascade.detectMultiScale(gray, 1.3, 5) for (x, y, w, h) in faces: cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2) #Rectangular box size initialization roi_gray = gray[y:y + h, x:x + w] roi_color = img[y:y + h, x:x + w] eyes = eye_cascade.detectMultiScale(roi_gray) for (ex, ey, ew, eh) in eyes: cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2) cv2.imshow('img', img) k = cv2.waitKey(30) & 0xff # cv2.waitKey() will show the image for assigned time duration if k == 27: #If user presses Esc Key then video capturing will be terminated break cap.release() #Its mandatory to release video capture cv2.destroyAllWindows()#Once the task completes then we will close all the opened windows Step3: Run the code Result: 1. Showing my face and eyes detected and enclosed in a box
- 4. Python programming with Open CV Page 4 2. Showing face and eyes of mine and the person in my cell phone and also in photo detected and enclosed in a box
- 5. Python programming with Open CV Page 5 2. Nose Detection of Human Source Code: import cv2 import numpy as np nose_cascade = cv2.CascadeClassifier('haarcascade_mcs_nose.xml') cap = cv2.VideoCapture(0) ds_factor = 0.5 while True: ret, frame = cap.read() frame = cv2.resize(frame, None, fx=ds_factor, fy=ds_factor, interpolation=cv2.INTER_AREA) gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) nose_rects = nose_cascade.detectMultiScale(gray, 1.3, 5) for (x,y,w,h) in nose_rects: cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 3) break cv2.imshow('Nose Detected', frame) c = cv2.waitKey(1) if c == 27: break cap.release() cv2.destroyAllWindows() Result: Nose being detected
- 6. Python programming with Open CV Page 6 3. Mouth Detection of Human Source Code: import cv2 import numpy as np mouth_cascade = cv2.CascadeClassifier('haarcascade_mcs_mouth.xml') cap = cv2.VideoCapture(0) ds_factor = 0.5 while True: ret, frame = cap.read() frame = cv2.resize(frame, None, fx=ds_factor, fy=ds_factor, interpolation=cv2.INTER_AREA) gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) mouth_rects = mouth_cascade.detectMultiScale(gray, 1.7, 11) for (x,y,w,h) in mouth_rects: y = int(y - 0.15*h) cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 3) break cv2.imshow('Mouth Detected', frame) c = cv2.waitKey(1) if c == 27: break cap.release() cv2.destroyAllWindows() Result: Mouth being detected
- 7. Python programming with Open CV Page 7 For more information contact: [email protected] linkedin.com/in/amarjeetsingh-thakur-54915955 Mob: +91-9035508516