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Commit 81dee24d authored by sidi mohammed kaddour's avatar sidi mohammed kaddour
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fixed bugs

parent 7205b544
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deploy.sh
+ 10
− 10
View file @ 81dee24d
......@@ -4,28 +4,28 @@
echo "Building Docker images for services..."
# Build images for camera, motion_detector, and object_recognizer
docker build -t camera:latest --platform linux/amd64 ./services/camera
docker build -t motion_detector:latest --platform linux/amd64 ./services/motion_detector
docker build -t object_recognizer:latest --platform linux/amd64 ./services/object_recognizer
sudo docker build -t camera:latest --platform linux/amd64 ./services/camera
sudo docker build -t motion_detector:latest --platform linux/amd64 ./services/motion_detector
sudo docker build -t object_recognizer:latest --platform linux/amd64 ./services/object_recognizer
# Step 3: Optional - Tag and push the images to Docker Hub
# Replace <your-username> with your Docker Hub username
# Tag images for Docker Hub
echo "Tagging images for Docker Hub..."
docker tag camera:latest medkaddour/camera:latest
docker tag motion_detector:latest medkaddour/motion_detector:latest
docker tag object_recognizer:latest medkaddour/object_recognizer:latest
sudo docker tag camera:latest medkaddour/camera:latest
sudo docker tag motion_detector:latest medkaddour/motion_detector:latest
sudo docker tag object_recognizer:latest medkaddour/object_recognizer:latest
# Log in to Docker Hub
echo "Logging into Docker Hub..."
docker login
sudo docker login
# Push images to Docker Hub
echo "Pushing images to Docker Hub..."
docker push medkaddour/camera:latest
docker push medkaddour/motion_detector:latest
docker push medkaddour/object_recognizer:latest
sudo docker push medkaddour/camera:latest
sudo docker push medkaddour/motion_detector:latest
sudo docker push medkaddour/object_recognizer:latest
# Step 4: Set up docker-compose for deployment
echo "Navigating to deployment directory..."
......
services/camera/src/camera.py
+ 61
− 60
View file @ 81dee24d
......@@ -97,66 +97,67 @@ def main():
if client_socket:
while True:
for interval in generate_random_intervals(appearance_rate):
interval_frame_count = interval * 30
frame_number = 0
if motion:
vid = cv2.VideoCapture(with_animal_video)
motion = False
else:
vid = cv2.VideoCapture(no_animal_video)
motion = True
logging.info(f"Motion: {motion}")
while (frame_number < interval_frame_count) or (not motion):
frame_number += 1
carrier = {}
with tracer.start_as_current_span("sending frame from camera") as span:
try:
inject(carrier)
img, frame = vid.read()
if not img:
if motion:
vid = cv2.VideoCapture(no_animal_video)
continue
else:
logging.info(f"Motion frames count: {frame_number}")
break
frame = imutils.resize(frame, width=640)
start_time = time.time()
current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
data = {
'frame': frame,
'capture_time': current_time,
'carrier': carrier
}
a = pickle.dumps(data)
message = struct.pack("Q", len(a)) + a
client_socket.sendall(message)
# Update FPS calculation
fps_frame_count += 1
elapsed_time = time.time() - fps_start_time
if elapsed_time >= 10.0:
fps = round(fps_frame_count / elapsed_time, 2)
logging.info(f"FPS: {fps} (Total frames: {fps_frame_count}, Time: {elapsed_time})")
fps_histo.record(fps)
fps_count.set(fps)
fps_frame_count = 0
fps_start_time = time.time()
# Maintain the frame rate
end_time = time.time()
elapsed_time = end_time - start_time
if elapsed_time < frame_interval:
time.sleep(0.025) # frame_interval - elapsed_time
except Exception as e:
logging.error(f"Error sending frame: {e}")
client_socket.close()
break
for motion in (False, True):
frame_number = 0
if motion:
vid = cv2.VideoCapture(with_animal_video)
interval_frame_count= int(vid.get(cv2.CAP_PROP_FRAME_COUNT))
else:
vid = cv2.VideoCapture(no_animal_video)
interval_frame_count = interval * 30
logging.info(f"Motion: {motion} max frame count: {interval_frame_count}")
while (frame_number < interval_frame_count):
frame_number += 1
carrier = {}
with tracer.start_as_current_span("sending frame from camera") as span:
try:
inject(carrier)
img, frame = vid.read()
if not img:
if motion:
vid = cv2.VideoCapture(no_animal_video)
continue
else:
logging.info(f"Motion frames count: {frame_number}")
break
frame = imutils.resize(frame, width=640)
start_time = time.time()
current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
data = {
'frame': frame,
'capture_time': current_time,
'carrier': carrier
}
a = pickle.dumps(data)
message = struct.pack("Q", len(a)) + a
client_socket.sendall(message)
# Update FPS calculation
fps_frame_count += 1
elapsed_time = time.time() - fps_start_time
if elapsed_time >= 10.0:
fps = round(fps_frame_count / elapsed_time, 2)
logging.info(f"FPS: {fps} (Total frames: {fps_frame_count}, Time: {elapsed_time})")
fps_histo.record(fps)
fps_count.set(fps)
fps_frame_count = 0
fps_start_time = time.time()
# Maintain the frame rate
end_time = time.time()
elapsed_time = end_time - start_time
if elapsed_time < frame_interval:
time.sleep(0.025) # frame_interval - elapsed_time
except Exception as e:
logging.error(f"Error sending frame: {e}")
client_socket.close()
break
if __name__ == "__main__":
......
services/motion_detector/src/motion_detection.py
+ 7
− 1
View file @ 81dee24d
......@@ -100,6 +100,11 @@ def process_frames(addr, frame_queue, or_host_ip, or_port):
name="md_detected_motion",
description="Detected motions 1 or 0",
)
md_detected_motion_nbr = meter.create_gauge(
name="md_detected_motion_nbr",
description="number of detected motions from the starting of the service",
)
md_detected_motion_nbr_rec=0
fps_start_time = time.time()
while True:
try:
......@@ -159,7 +164,8 @@ def process_frames(addr, frame_queue, or_host_ip, or_port):
text = "md: motion detected"
if detected:
logging.info("Motion detected, preparing to send frame to Object Recognizer.")
md_detected_motion_nbr_rec += 1
md_detected_motion_nbr.set(md_detected_motion_nbr_rec)
md_detected_motion.set(1)
orclient_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
orclient_socket.connect((or_host_ip, or_port))
......
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