def takeImages():
Id = input("Enter Your Id: ")
name = input("Enter Your Name: ")
if (is_number(Id) and name.isalpha()):
cam = cv2.videoCapture(0)
harcascadePath = "haarcascade_default.xml"
detector = cv2.cascadeClassifier(harcascadePath)
sampleNum = 0
while (True):
ret, img = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = detector.detectMultiScale(gray,
1.3,
5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (10, 159, 255), 2)
sampleNum = sampleNum + 1
#saving the captured face in the dataset folder TrainingImage
cv2.imwrite(
"TrainingImage" + os.sep + name + "." + Id + '.' +
str(sampleNum) + ".jpg", gray[y:y + h, x:x + w])
cv2.imshow('frame', img)
if cv2.waitKey(100) & 0xFF == ord('q'):
break
elif sampleNum > 100:
break
cam.release()
cv2.destroyAllWindows()
res = "Images Saved for ID : " + Id + " Name : " + name
row = [Id, name]
with open("StudentDetails" + os.sep + "StudentDetails.csv",
'a+') as csvFile:
writer = csv.writer(csvFile)
writer.writerow(row)
csvFile.close()
else:
if (is_number(Id)):
print("Enter Alphabetical Name")
if (name.isalpha()):
print("Enter Numeric ID")
def camer():
import cv2
# Load the cascade
cascade_face = cv2.cascadeClassifier('haarcascade_default.xml')
# To capture video from webcam.
cap = cv2.captureVideo(0)
while True:
# Read the frame
_, img = cap.read()
# Convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Detect the faces
faces = cascade_face.multiScale(gray,
1.3,
5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE)
# Draw the rectangle around each face
for (a, b, c, d) in faces:
cv2.rectangle(img, (a, b), (a + c, b + d), (10, 159, 255), 2)
# Display
cv2.imshow('Webcam Check', img)
# Stop if escape key is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release the captureVideo object
cap.release()
cv2.destroyAllWindows()
import cv2
face_cascade=cv2.cascadeClassifier("C:\\Users\\luvku\\CS 2019\\task0#sb (1)\\Task0.2\\Image Processing\\Images\\bird.jpg")
img=cv2.imread("C:\\Users\\luvku\\CS 2019\\task0#sb (1)\\Task0.2\\Image Processing\\Images\\bird.jpg",1)
gray_img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces=face_cascade.detectMultiScale(gray_img,scaleFactor_=_1,minNeighbors=5)
print(type(faces))
print(faces)
for x,y,w,h in faces:
img=cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),3)
cv2.imshow("bird",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
## importing libraries
import cv2
## Load the cascade
face_cascade = cv2.cascadeClassifier('haarcascade_frontalface_default.xml')
## Read the input image
img = cv2.imread('test.jpg')
## Convert the image into grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
## Detect faces
faces = face_cascade.detectMultiscale(gray, 1.1, 4)
## Draw rectangle around the face
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
## Show the output
cv2.imshow('output.jpg', img)
cv2.waitkey()
import cv2
cap=cv2.videoCapture(0)
face_cascade=cv2.cascadeClassifier("haarcascade_frontalface_alt.xml")
while True:
ret,frame=cap.read()
gray_frame=cv2.cvtColour(frame,cv2.COLOUR_BGR2GRAY)
if ret==False:
continue
face=face_cascade.detectMultiScale(gray_frame,1.3,5)
print(faces)
for(x,y,w,h) in faces:
cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
cv2.imshow("Video Frame",frame)
key_pressed=cv2.waitkey(1) & 0xFF
if key_pressed==ord('q');
break
import cv2
detect=cv2.cascadeClassifier("file.xml")
imp_img=cv2.VideoCapture("roman.jpg")
res,img=imp_img.read()
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces=detect.detectMultiSclae(gray,1.3,5)
for(x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
cv2.imshow("roman.jpg",img)
cv2.waitKey(0)
imp_img.release()
cv2.destroyAllWindow()
def get_face_boundingbox(image):
faces = cv2.detectMultiScale(image, cv2.cascadeClassifier())
return faces