diff --git a/images/cadvisor-ui-image.png b/images/cadvisor-ui-image.png
new file mode 100644
index 0000000000000000000000000000000000000000..1f4274c7296172874da923029459cb877f0bec61
Binary files /dev/null and b/images/cadvisor-ui-image.png differ
diff --git a/images/jaeger-ui-image.png b/images/jaeger-ui-image.png
new file mode 100644
index 0000000000000000000000000000000000000000..bbbe32b348ed8fce539c4554131ebf10f95bf1ba
Binary files /dev/null and b/images/jaeger-ui-image.png differ
diff --git a/images/object-recognizer-ui-image.png b/images/object-recognizer-ui-image.png
new file mode 100644
index 0000000000000000000000000000000000000000..43cce140e8b378d6e1d00a6af5a1a13fab9c509c
Binary files /dev/null and b/images/object-recognizer-ui-image.png differ
diff --git a/images/prometheus-ui-image.png b/images/prometheus-ui-image.png
new file mode 100644
index 0000000000000000000000000000000000000000..8db24869abe6e9e65600db8828f051a9e29d82d6
Binary files /dev/null and b/images/prometheus-ui-image.png differ
diff --git a/images/zipkin-ui-image.png b/images/zipkin-ui-image.png
new file mode 100644
index 0000000000000000000000000000000000000000..b6e3c29b8d00cf0bba92d9716bf634e5359e6360
Binary files /dev/null and b/images/zipkin-ui-image.png differ
diff --git a/readme.md b/readme.md
index aee8cfb6ae05ba3df8ebd33f73c50ac45d685a05..906672130a781607e50662e18d305bc884b1255a 100644
--- a/readme.md
+++ b/readme.md
@@ -328,11 +328,21 @@ services:
```
2. **Access the services**:
- - Access Jaeger UI: [http://localhost:16686](http://localhost:16686)
- - Access Zipkin UI: [http://localhost:9411](http://localhost:9411)
- - Access Prometheus UI: [http://localhost:9090](http://localhost:9090)
- - Access cAdvisor UI: [http://localhost:8080](http://localhost:8080)
- - Access object recognizer interface : [http://localhost:5000](http://localhost:5000)
+
+ - Access Jaeger UI: [http://localhost:16686](http://localhost:16686)
+ 
+
+ - Access Zipkin UI: [http://localhost:9411](http://localhost:9411)
+ 
+
+ - Access Prometheus UI: [http://localhost:9090](http://localhost:9090)
+ 
+
+ - Access cAdvisor UI: [http://localhost:8080](http://localhost:8080)
+ 
+
+ - Access Object Recognizer Interface: [http://localhost:5000](http://localhost:5000)
+ 
## **Deploying on K3S using Enoslib on Grid'5000**
diff --git a/services/camera/src/camera.py b/services/camera/src/camera.py
index c74b37194b797c417c3134085f9bfacdd233e6ce..eb2f091d239f01f1ab947717620aa89d0a133e4c 100644
--- a/services/camera/src/camera.py
+++ b/services/camera/src/camera.py
@@ -9,7 +9,7 @@ import os # Import os for environment variables
from telemetry.tracerprovider import tracer, meter
import imutils # pip install imutils
import logging
-
+from opentelemetry.propagate import inject
# Configure logging
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(message)s',
@@ -108,8 +108,10 @@ def main():
logging.info(f"Motion: {motion}")
while (frame_number < interval_frame_count) or (not motion):
frame_number += 1
- with tracer.start_as_current_span("sending frame") as span:
+ 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:
@@ -126,7 +128,9 @@ def main():
data = {
'frame': frame,
- 'capture_time': current_time
+ 'capture_time': current_time,
+ 'carrier': carrier
+
}
a = pickle.dumps(data)
message = struct.pack("Q", len(a)) + a
diff --git a/services/motion_detector/src/motion_detection.py b/services/motion_detector/src/motion_detection.py
index a6b74122f9b02855748d55d5ac178e110fcfc560..c02ac1204cdf421a9b3c3513a78ce3b66d363243 100644
--- a/services/motion_detector/src/motion_detection.py
+++ b/services/motion_detector/src/motion_detection.py
@@ -11,7 +11,9 @@ import queue
import psutil
import imutils
import logging # Import the logging module
-from telemetry.tracerprovider import meter
+from telemetry.tracerprovider import tracer , meter
+from opentelemetry import trace
+from opentelemetry.propagate import extract, inject
# Configure logging
logging.basicConfig(
@@ -40,6 +42,7 @@ def receive_frames(client_socket, frame_queue):
unit="s"
)
while True:
+
try:
while len(data) < payload_size:
packet = client_socket.recv(4 * 1024) # 4K
@@ -106,77 +109,87 @@ def process_frames(addr, frame_queue, or_host_ip, or_port):
except queue.Empty:
logging.info(f"Queue is empty for {addr}, waiting for frames...")
continue
-
- frame = recieveddata['frame']
- logging.debug("Frame loaded for processing.")
- text = f"CLIENT: {addr}"
-
- gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
- gray = cv2.GaussianBlur(gray, (21, 21), 0)
- logging.debug("Frame converted to grayscale and blurred.")
-
- if firstFrame is None:
- firstFrame = gray
- logging.info("Initialized reference frame for motion detection.")
- continue
-
- starting_processing_time = time.time()
- fps_frame_count += 1
- elapsed_time = time.time() - fps_start_time
- if elapsed_time >= 10.0:
- fps = round(fps_frame_count / elapsed_time, 2)
- fps_count.set(fps)
- logging.info(f"FPS: {fps}")
- fps_frame_count = 0
- fps_start_time = time.time()
-
- frameDelta = cv2.absdiff(firstFrame, gray)
- thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
- thresh = cv2.dilate(thresh, None, iterations=2)
- cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
- cv2.CHAIN_APPROX_SIMPLE)
- cnts = imutils.grab_contours(cnts)
-
- detected_cnt = 0
- detected = False
- for c in cnts:
- if cv2.contourArea(c) < 10000:
- continue
- detected = True
- detected_cnt += 1
- logging.debug(f"Motion detected. Contour area: {cv2.contourArea(c)}.")
-
- (x, y, w, h) = cv2.boundingRect(c)
- cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
- text = "md: motion detected"
- if detected:
- logging.info("Motion detected, preparing to send frame to Object Recognizer.")
- md_detected_motion.set(1)
- orclient_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
- orclient_socket.connect((or_host_ip, or_port))
- ordata = {
- "frame": frame,
- "capture_time": recieveddata["capture_time"],
- "sentfromedgetime": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
- }
- while True:
- try:
- a = pickle.dumps(ordata)
- message = struct.pack("Q", len(a)) + a
- logging.info(f"Packet size: {len(message)} bytes.") # Log the size of the packet
- orclient_socket.sendall(message)
- logging.info("Frame successfully sent to Object Recognizer.")
- break
- except Exception as e:
- logging.error(f"Sending frame to Object Recognizer failed: {e}")
- time.sleep(1)
+ received_carrier=recieveddata['carrier']
+ extracted_context = extract(received_carrier)
+ carrier = {}
+ with tracer.start_as_current_span("processing the frame",context=extracted_context) as span:
+ try:
+ inject(carrier)
+ frame = recieveddata['frame']
+ logging.debug("Frame loaded for processing.")
+ text = f"CLIENT: {addr}"
+
+ gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+ gray = cv2.GaussianBlur(gray, (21, 21), 0)
+ logging.debug("Frame converted to grayscale and blurred.")
+
+ if firstFrame is None:
+ firstFrame = gray
+ logging.info("Initialized reference frame for motion detection.")
continue
- orclient_socket.close()
-
- md_detected_motion.set(0)
- processing_time.set(time.time() - starting_processing_time)
- logging.debug("Processing time logged for frame.")
+ starting_processing_time = time.time()
+ fps_frame_count += 1
+ elapsed_time = time.time() - fps_start_time
+ if elapsed_time >= 10.0:
+ fps = round(fps_frame_count / elapsed_time, 2)
+ fps_count.set(fps)
+ logging.info(f"FPS: {fps}")
+ fps_frame_count = 0
+ fps_start_time = time.time()
+
+ frameDelta = cv2.absdiff(firstFrame, gray)
+ thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
+ thresh = cv2.dilate(thresh, None, iterations=2)
+ cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+ cnts = imutils.grab_contours(cnts)
+
+ detected_cnt = 0
+ detected = False
+ for c in cnts:
+ if cv2.contourArea(c) < 10000:
+ continue
+ detected = True
+ detected_cnt += 1
+ logging.debug(f"Motion detected. Contour area: {cv2.contourArea(c)}.")
+
+ (x, y, w, h) = cv2.boundingRect(c)
+ cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+ text = "md: motion detected"
+ if detected:
+ logging.info("Motion detected, preparing to send frame to Object Recognizer.")
+
+ md_detected_motion.set(1)
+ orclient_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+ orclient_socket.connect((or_host_ip, or_port))
+ ordata = {
+ "frame": frame,
+ "capture_time": recieveddata["capture_time"],
+ "sentfromedgetime": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+ 'carrier':carrier
+ }
+ while True:
+ try:
+ a = pickle.dumps(ordata)
+ message = struct.pack("Q", len(a)) + a
+ logging.info(f"Packet size: {len(message)} bytes.") # Log the size of the packet
+ orclient_socket.sendall(message)
+ logging.info("Frame successfully sent to Object Recognizer.")
+ break
+ except Exception as e:
+ logging.error(f"Sending frame to Object Recognizer failed: {e}")
+ time.sleep(1)
+ continue
+ orclient_socket.close()
+
+ md_detected_motion.set(0)
+ processing_time.set(time.time() - starting_processing_time)
+ logging.debug("Processing time logged for frame.")
+ except Exception as e:
+ logging.error(f"Error processing frame: {e}")
+
+ break
def main():
# Retrieve environment variables instead of command-line arguments
diff --git a/services/motion_detector/src/telemetry/tracerprovider.py b/services/motion_detector/src/telemetry/tracerprovider.py
index 68cb24d89702fe33fa301c44edbc0531e7fc0d03..515d81cf54a6368b1f5f998d4dd3430ac7db7e3c 100644
--- a/services/motion_detector/src/telemetry/tracerprovider.py
+++ b/services/motion_detector/src/telemetry/tracerprovider.py
@@ -33,7 +33,7 @@ otlp_trace_exporter = OTLPSpanExporter(endpoint="otel-collector:4317", insecure=
trace.get_tracer_provider().add_span_processor(
BatchSpanProcessor(otlp_trace_exporter)
)
-tracer = trace.get_tracer("md tracer")
+tracer = trace.get_tracer("motion detector tracer")
# Set up the meter provider for metrics
meter_provider = MeterProvider()
@@ -49,4 +49,4 @@ reader = PeriodicExportingMetricReader(
)
meterProvider = MeterProvider(resource=resource, metric_readers=[reader])
metrics.set_meter_provider(meterProvider)
-meter = metrics.get_meter("md meter")
\ No newline at end of file
+meter = metrics.get_meter("motion detector meter")
\ No newline at end of file
diff --git a/services/object_recognizer/src/object_recognizer.py b/services/object_recognizer/src/object_recognizer.py
index e698fb0e1807c0af6149a2e9eca104ba5a24f712..68106b2b6397f9487b3b3f4573df82841998cbb8 100644
--- a/services/object_recognizer/src/object_recognizer.py
+++ b/services/object_recognizer/src/object_recognizer.py
@@ -6,10 +6,10 @@ import pickle
import struct
import cv2
import logging
-
+from opentelemetry.propagate import extract
from model.model import recognize
from webserver import run_flask
-from telemetry.tracerprovider import meter
+from telemetry.tracerprovider import meter, tracer
# Configure logging
logging.basicConfig(
@@ -48,7 +48,12 @@ def draw_prediction(img, class_id, confidence, x, y, x_plus_w, y_plus_h, classes
def process_frame(mddata):
- recognize(mddata['frame'])
+ received_carrier = mddata['carrier']
+ extracted_context = extract(received_carrier)
+ carrier = {}
+ with tracer.start_as_current_span("detecting motion in the frame", context=extracted_context) as span:
+
+ recognize(mddata['frame'])
def receive_frames(client_socket, frame_queue):
data = b""
diff --git a/services/object_recognizer/src/webserver.py b/services/object_recognizer/src/webserver.py
index 37a550c9982c6a5e5bd02adc34f5f2a44635985f..99e673e98b5f2b46aaae356dd6bfdc32ede32f87 100644
--- a/services/object_recognizer/src/webserver.py
+++ b/services/object_recognizer/src/webserver.py
@@ -1,30 +1,68 @@
-from flask import Flask, send_file
-import threading
+from flask import Flask, send_file, render_template_string
import os
-import time
# Flask application setup
app = Flask(__name__)
IMAGE_PATH = "/app/output/res.jpg"
+
# Disable browser caching by adding cache headers
@app.after_request
def add_no_cache_headers(response):
response.cache_control.no_store = True
return response
+
@app.route("/")
def home():
return "<h1>Object Recognizer</h1><p>Go to <a href='/image'>/image</a> to see the latest detection.</p>"
+
@app.route("/image")
def serve_image():
if os.path.exists(IMAGE_PATH):
- return send_file(IMAGE_PATH, mimetype='image/jpeg')
+ html_template = """
+ <!DOCTYPE html>
+ <html>
+ <head>
+ <title>Object Recognizer</title>
+ <script>
+ // Refresh the image every 5 seconds
+ function refreshImage() {
+ const image = document.getElementById('image');
+ image.src = '/static_image?' + new Date().getTime(); // Append timestamp to bypass cache
+ }
+
+ // Update the date-time every second
+ function updateDateTime() {
+ const now = new Date();
+ document.getElementById('datetime').innerText = now.toLocaleString();
+ }
+
+ setInterval(refreshImage, 5000); // Refresh every 5 seconds
+ setInterval(updateDateTime, 1000); // Update date-time every second
+ </script>
+ </head>
+ <body>
+ <h1>Object Recognizer</h1>
+ <p id="datetime"></p>
+ <img id="image" src="/static_image" alt="Latest detection" width="600">
+ </body>
+ </html>
+ """
+ return render_template_string(html_template)
else:
return "<h1>No image available</h1>", 404
+@app.route("/static_image")
+def static_image():
+ if os.path.exists(IMAGE_PATH):
+ return send_file(IMAGE_PATH, mimetype='image/jpeg')
+ else:
+ return "", 404
+
+
# Flask server runner
def run_flask():
- app.run(host="0.0.0.0", port=5000, debug=False, threaded=True)
\ No newline at end of file
+ app.run(host="0.0.0.0", port=5000, debug=False, threaded=True)