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2024-06-09T16:47:18Z

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Return back to project page: [[Spike Prime - Door camera - Jakub Vojtek| Door camera - Jakub Vojtek]]

Python code for the Door Camera project:
<syntaxhighlight lang=python>
import cv2
from buildhat import DistanceSensor
from datetime import datetime
import threading
import sqlite3
import os
import time

distance_sensor = DistanceSensor('A')

video_capture = cv2.VideoCapture(0)
frame_width = 480
frame_height = 360
video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, frame_width)
video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, frame_height)

# face detector
face_classifier = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")

current_frame = None
lock = threading.Lock()

# create camera_pictures directory if it doesn't exist
if not os.path.exists("camera_pictures"):
os.makedirs("camera_pictures")

db_directory = "database"
if not os.path.exists(db_directory):
os.makedirs(db_directory)

db_filename = os.path.join(db_directory, "face_images.db")

conn = sqlite3.connect(db_filename)
c = conn.cursor()

c.execute('''
CREATE TABLE IF NOT EXISTS images (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TEXT NOT NULL,
detected_faces INTEGER NOT NULL
)
''')
conn.commit()

def camera_thread():
global current_frame
while True:
result, frame = video_capture.read()
if result:
with lock:
current_frame = frame

def take_and_save_picture():
with lock:
if current_frame is not None:
video_frame = current_frame.copy()
gframe = cv2.cvtColor(video_frame, cv2.COLOR_BGR2GRAY)

faces = face_classifier.detectMultiScale(gframe, 1.1, 5, minSize=(40, 40))

detected_faces = len(faces)
if detected_faces > 0:
faces = sorted(faces, key=lambda x: x[2] * x[3], reverse=True)
x, y, width, height = faces[0]
cv2.rectangle(video_frame, (x, y), (x + width, y + height), (0, 255, 0), 4)
else:
cv2.putText(video_frame, "Face couldn't be detected", (video_frame.shape[1] - 250, video_frame.shape[0] - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1, cv2.LINE_AA)

timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
cv2.putText(video_frame, timestamp, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2, cv2.LINE_AA)

filename = f"camera_pictures/face_detected_{datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg"
cv2.imwrite(filename, video_frame)
print(f"Saved image: {filename}")

# save time and amount of detected faces to database
c.execute('''
INSERT INTO images (timestamp, detected_faces)
VALUES (?, ?)
''', (timestamp, detected_faces))
conn.commit()

time.sleep(1)

if __name__ == '__main__':
threading.Thread(target=camera_thread, daemon=True).start()

try:
while True:
distance = distance_sensor.get_distance()
if distance < 300:
take_and_save_picture()
finally:
video_capture.release()
cv2.destroyAllWindows()
conn.close()

</syntaxhighlight>

Door Camera - Code - Revision history

Robot: Created page with "Return back to project page: Door camera - Jakub Vojtek Python code for the Door Camera project: ..."