O‘ZBEKISTON RESPUBLIKASI AXBOROT TEXNOLOGIYALARI VA KOMMUNIKATSIYALARINI RIVOJLANTIRISH VAZIRLIGI MUHAMMAD AL-XORAZMIY NOMIDAGI TOSHKENT AXBOROT TEXNOLOGIYALARI UNIVERSITETI
“KOMPYUTER TIZIMLARI” kafedrasi
Kompyuter ko‘rishni raspberry pi bilan dasturlash fanidan tayyorlagan
Amaliy ish-7
Bajardi:Karimova Gavhar
Tekshirdi: Karimberdiyev Jaxongir
TOSHKENT – 2024
“Kompyuter ko‘rishni raspberry pi bilan dasturlash” fanidan 6-amaliy ish uchun topshiriq
Yuzdan tanib oluvchi (face recognition) dastur yarating.
Talaba o‘zining yuzini dastur orqali aniqlash jarayonini amalga oshirishi kerak va skrinshot tarzda word hujjat tayyorlashi lozim.
Dastur kodini va .doc hujjatlarni tizimga yuklashi zarur.
import cv2
import numpy as np
# Load the image of the known person
known_image = cv2.imread('image1.jpg', cv2.IMREAD_GRAYSCALE)
# Load the classifier for face detection
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
# Initialize the camera
cap = cv2.VideoCapture(0)
while True:
# Read a frame from the camera
ret, frame = cap.read()
if not ret:
print("Error reading frame from camera")
break
# Convert the frame to grayscale
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Detect faces in the frame
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
for (x, y, w, h) in faces:
# Extract the face region from the frame
face = gray[y:y+h, x:x+w]
# Resize the known image to match the size of the detected face
resized_known_image = cv2.resize(known_image, (w, h))
# Compare the detected face with the known image
diff = cv2.absdiff(face, resized_known_image)
similarity = np.mean(diff)
# Draw a rectangle around the detected face
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
# Display the person's name if similarity is below a certain threshold
if similarity < 100: # Adjust this threshold as needed
cv2.putText(frame, "Zuhriddin", (x, y+h+30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
else:
cv2.putText(frame, "Unknown person", (x, y+h+30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
# Display the resulting frame
cv2.imshow('Face Recognition', frame)
# Exit loop if 'q' is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release the camera and close all windows
cap.release()
cv2.destroyAllWindows()
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