feat: spike for replicas docker-compose adding gst and capi ovms prof…

…iles test cases (intel-retail#470)

* feat: spike for replicas docker-compose adding gst and capi ovms profiles test cases
* fix: update gstreamer scripts and docker-compose to work for replicas

Signed-off-by: Jim Wang <[email protected]>

* feat: add CAPI-yolov5 for replicas docker-compose

Signed-off-by: Jim Wang <[email protected]>

* feat: add and update capi_yolov5_ensemble replicas docker-compose

Signed-off-by: Jim Wang <[email protected]>

* feat: add capi-face-detection replicas docker-compose

Signed-off-by: Jim Wang <[email protected]>

---------

Signed-off-by: Jim Wang <[email protected]>

Dockerfile.dlstreamer

@@ -10,6 +10,9 @@ USER root
 
 FROM base as build-default
 COPY ./requirements.txt /requirements.txt
+COPY ./configs/opencv-ovms/gst /opencv-ovms/gst
+COPY ./configs/opencv-ovms/scripts/run_gst.sh /opencv-ovms/scripts/run_gst.sh
+COPY ./configs/opencv-ovms/scripts/docker_compose_generic_entrypoint.sh /opencv-ovms/scripts/docker_compose_generic_entrypoint.sh
 RUN pip3 install --upgrade pip --no-cache-dir -r /requirements.txt
 WORKDIR /
 

Makefile

@@ -17,6 +17,7 @@
 
 MKDOCS_IMAGE ?= asc-mkdocs
 DGPU_TYPE ?= arc  # arc|flex
+DOCKER_COMPOSE ?= docker-compose.yml
 
 build-dlstreamer:
 	docker build --no-cache --build-arg HTTPS_PROXY=${HTTPS_PROXY} --build-arg HTTP_PROXY=${HTTP_PROXY} --target build-default -t dlstreamer:dev -f Dockerfile.dlstreamer .
@@ -41,7 +42,7 @@ run-portainer:
 
 run-pipelines:
 	@./scripts/gen_ovms_model_config_json.sh
-	docker compose -f docker-compose.yml up -d
+	docker compose -f $(DOCKER_COMPOSE) up -d
 
 clean:
 	./clean-containers.sh automated-self-checkout
@@ -114,7 +115,7 @@ down-portainer:
 	docker compose -p portainer -f docker-compose-portainer.yml down
 
 down-pipelines:
-	docker compose -f docker-compose.yml down
+	docker compose -f $(DOCKER_COMPOSE) down
 	@if [ -f ./configs/opencv-ovms/models/2022/config.json ]; then rm ./configs/opencv-ovms/models/2022/config.json; fi;
 
 clean-all: clean clean-ovms clean-simulator clean-results clean-telegraf clean-webcam down-pipelines

configs/opencv-ovms/demos/classification/python/entrypoint.sh

@@ -13,7 +13,10 @@ then
 fi
 
 echo "Note: Pipeline log and results are available at location - ./results"
+# generate unique container id based on the date with the precision upto nano-seconds
+cid=$(date +%Y%m%d%H%M%S%N)
+echo "cid: $cid"
 
 python3 classification/python/classification_demo.py -m localhost:"$GRPC_PORT"/models/"$CLASSIFICATION_MODEL_NAME" \
 	--label classification/python/labels/"$CLASSIFICATION_LABEL_FILE" -i $INPUTSRC \
-	--adapter ovms --output_resolution "$CLASSIFICATION_OUTPUT_RESOLUTION" $mqttArgs 2>&1  | tee >/tmp/results/r$cid_count.jsonl >(stdbuf -oL sed -n -e 's/^.*fps: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid_count.log)
+	--adapter ovms --output_resolution "$CLASSIFICATION_OUTPUT_RESOLUTION" $mqttArgs 2>&1  | tee >/tmp/results/r$cid"_classification".jsonl >(stdbuf -oL sed -n -e 's/^.*fps: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid"_classification".log)

configs/opencv-ovms/demos/object_detection/python/entrypoint.sh

@@ -13,8 +13,11 @@ then
 fi
 
 echo "Note: Pipeline log and results are available at location - ./results"
+# generate unique container id based on the date with the precision upto nano-seconds
+cid=$(date +%Y%m%d%H%M%S%N)
+echo "cid: $cid"
 
 python3 object_detection/python/object_detection_demo.py -m localhost:"$GRPC_PORT"/models/"$DETECTION_MODEL_NAME" \
 --label object_detection/python/labels/"$DETECTION_LABEL_FILE" -i "$INPUTSRC" \
 --adapter ovms -t "$DETECTION_THRESHOLD" -at "$DETECTION_ARCHITECTURE_TYPE" --output_resolution "$DETECTION_OUTPUT_RESOLUTION" \
-$mqttArgs 2>&1  | tee >/tmp/results/r$cid_count.jsonl >(stdbuf -oL sed -n -e 's/^.*fps: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid_count.log)
+$mqttArgs 2>&1  | tee >/tmp/results/r$cid"_object_detection".jsonl >(stdbuf -oL sed -n -e 's/^.*fps: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid"_object_detection".log)

configs/opencv-ovms/gst/framework-pipelines/yolov5_pipeline/yolov5s.sh

@@ -16,9 +16,13 @@ else
     OUTPUT="${OUTPUT:="! fpsdisplaysink video-sink=fakesink sync=true --verbose"}"
 fi
 
+# generate unique container id based on the date with the precision upto nano-seconds
+cid=$(date +%Y%m%d%H%M%S%N)
+echo "cid: $cid"
+
 echo "Run yolov5s pipeline"
 
-gstLaunchCmd="GST_DEBUG=\"GST_TRACER:7\" GST_TRACERS=\"latency_tracer(flags=pipeline,interval=100)\" gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect model-instance-id=odmodel name=detection model=models/yolov5s/FP16-INT8/1/yolov5s.xml model-proc=models/yolov5s/FP16-INT8/1/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS ! $AGGREGATE gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid_count.jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst-launch_$cid_count.log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid_count.log)"
+gstLaunchCmd="GST_DEBUG=\"GST_TRACER:7\" GST_TRACERS=\"latency_tracer(flags=pipeline,interval=100)\" gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect model-instance-id=odmodel name=detection model=models/yolov5s/FP16-INT8/1/yolov5s.xml model-proc=models/yolov5s/FP16-INT8/1/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS ! $AGGREGATE gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid\"_gst\".jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst-launch_$cid\"_gst\".log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid\"_gst\".log)"
 
 echo "$gstLaunchCmd"
 

configs/opencv-ovms/gst/framework-pipelines/yolov5_pipeline/yolov5s_effnetb0.sh

@@ -23,9 +23,13 @@ else
     OUTPUT="${OUTPUT:="! fpsdisplaysink video-sink=fakesink sync=true --verbose"}"
 fi
 
+# generate unique container id based on the date with the precision upto nano-seconds
+cid=$(date +%Y%m%d%H%M%S%N)
+echo "cid: $cid"
+
 echo "Run run yolov5s with efficientnet classification pipeline"
-gstLaunchCmd="gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect model-instance-id=odmodel name=detection model=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.xml model-proc=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS $DETECTION_OPTIONS ! gvatrack name=tracking tracking-type=zero-term-imageless ! queue max-size-bytes=0 max-size-buffers=0 max-size-time=0 ! gvaclassify model-instance-id=clasifier labels=/home/pipeline-server/models/efficientnet-b0/1/imagenet_2012.txt model=/home/pipeline-server/models/efficientnet-b0/FP32-INT8/1/efficientnet-b0.xml model-proc=/home/pipeline-server/models/efficientnet-b0/efficientnet-b0.json device=$DEVICE inference-region=roi-list name=classification $PRE_PROCESS $CLASSIFICATION_OPTIONS ! gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid_count.jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst_launch$cid_count.log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid_count.log)"
+gstLaunchCmd="gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect model-instance-id=odmodel name=detection model=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.xml model-proc=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS $DETECTION_OPTIONS ! gvatrack name=tracking tracking-type=zero-term-imageless ! queue max-size-bytes=0 max-size-buffers=0 max-size-time=0 ! gvaclassify model-instance-id=clasifier labels=/home/pipeline-server/models/efficientnet-b0/1/imagenet_2012.txt model=/home/pipeline-server/models/efficientnet-b0/FP32-INT8/1/efficientnet-b0.xml model-proc=/home/pipeline-server/models/efficientnet-b0/efficientnet-b0.json device=$DEVICE inference-region=roi-list name=classification $PRE_PROCESS $CLASSIFICATION_OPTIONS ! gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid\"_gst\".jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst_launch$cid\"_gst\".log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid\"_gst\".log)"
 
 echo "$gstLaunchCmd"
 
-eval $gstLaunchCmd
+eval $gstLaunchCmd

configs/opencv-ovms/gst/framework-pipelines/yolov5_pipeline/yolov5s_full.sh

@@ -23,8 +23,12 @@ else
     OUTPUT="${OUTPUT:="! fpsdisplaysink video-sink=fakesink sync=true --verbose"}"
 fi
 
+# generate unique container id based on the date with the precision upto nano-seconds
+cid=$(date +%Y%m%d%H%M%S%N)
+echo "cid: $cid"
+
 echo "Run yolov5s with efficientnet classification, horizontal text detection, and barcode detection pipeline"
-gstLaunchCmd="gst-launch-1.0 $inputsrc ! $DECODE $VA_SURFACE ! gvadetect model-instance-id=odmodel name=detection model=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.xml model-proc=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS $DETECTION_OPTIONS  gpu-throughput-streams=4 nireq=4 batch-size=1 ! gvatrack name=tracking tracking-type=zero-term-imageless $PARALLEL_PIPELINE ! gvaclassify model-instance-id=clasifier labels=/home/pipeline-server/models/efficientnet-b0/1/imagenet_2012.txt model=/home/pipeline-server/models/efficientnet-b0/FP32-INT8/1/efficientnet-b0.xml model-proc=/home/pipeline-server/models/efficientnet-b0/efficientnet-b0.json reclassify-interval=1  device=$DEVICE inference-region=roi-list name=classification $PRE_PROCESS reclassify_interval=$OCR_RECLASSIFY_INTERVAL batch-size=8 nireq=4 gpu-throughput-streams=1 $PARALLEL_AGGRAGATE ! gvapython class=ObjectFilter module=/home/pipeline-server/extensions/tracked_object_filter.py kwarg=\"{\\\"reclassify_interval\\\": $OCR_RECLASSIFY_INTERVAL}\" name=tracked_object_filter ! gvadetect model-instance-id=ocr threshold=.2 model=/home/pipeline-server/models/horizontal-text-detection-0002/FP16-INT8/1/horizontal-text-detection-0002.xml model-proc=/home/pipeline-server/models/horizontal-text-detection-0002/FP16-INT8/1/horizontal-text-detection-0002.json name=text_detection device=$DEVICE inference-region=roi-list $PRE_PROCESS ! gvainference model-instance-id=ocr2 nireq=4 gpu-throughput-streams=2 batch-size=32 device=$DEVICE model=/home/pipeline-server/models/text-recognition-0012-mod/FP16-INT8/1/text-recognition-0012-mod.xml model-proc=/home/pipeline-server/models/text-recognition-0012-mod/FP16-INT8/1/text-recognition-0012-mod.json inference-region=roi-list name=text_recognition object-class=text ! gvapython class=OCR module=/home/pipeline-server/extensions/OCR_post_processing_0012.py name=ocr_postprocess $AGGREGATE ! gvapython name=barcode class=BarcodeDetection module=/home/pipeline-server/extensions/barcode_nv12_to_gray.py kwarg=\"{\\\"reclassify_interval\\\": $BARCODE_RECLASSIFY_INTERVAL}\" !  gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid_count.jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst-launch_$cid_count.log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid_count.log)"
+gstLaunchCmd="gst-launch-1.0 $inputsrc ! $DECODE $VA_SURFACE ! gvadetect model-instance-id=odmodel name=detection model=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.xml model-proc=/home/pipeline-server/models/yolov5s/FP16-INT8/1/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS $DETECTION_OPTIONS  gpu-throughput-streams=4 nireq=4 batch-size=1 ! gvatrack name=tracking tracking-type=zero-term-imageless $PARALLEL_PIPELINE ! gvaclassify model-instance-id=clasifier labels=/home/pipeline-server/models/efficientnet-b0/1/imagenet_2012.txt model=/home/pipeline-server/models/efficientnet-b0/FP32-INT8/1/efficientnet-b0.xml model-proc=/home/pipeline-server/models/efficientnet-b0/efficientnet-b0.json reclassify-interval=1  device=$DEVICE inference-region=roi-list name=classification $PRE_PROCESS reclassify_interval=$OCR_RECLASSIFY_INTERVAL batch-size=8 nireq=4 gpu-throughput-streams=1 $PARALLEL_AGGRAGATE ! gvapython class=ObjectFilter module=/home/pipeline-server/extensions/tracked_object_filter.py kwarg=\"{\\\"reclassify_interval\\\": $OCR_RECLASSIFY_INTERVAL}\" name=tracked_object_filter ! gvadetect model-instance-id=ocr threshold=.2 model=/home/pipeline-server/models/horizontal-text-detection-0002/FP16-INT8/1/horizontal-text-detection-0002.xml model-proc=/home/pipeline-server/models/horizontal-text-detection-0002/FP16-INT8/1/horizontal-text-detection-0002.json name=text_detection device=$DEVICE inference-region=roi-list $PRE_PROCESS ! gvainference model-instance-id=ocr2 nireq=4 gpu-throughput-streams=2 batch-size=32 device=$DEVICE model=/home/pipeline-server/models/text-recognition-0012-mod/FP16-INT8/1/text-recognition-0012-mod.xml model-proc=/home/pipeline-server/models/text-recognition-0012-mod/FP16-INT8/1/text-recognition-0012-mod.json inference-region=roi-list name=text_recognition object-class=text ! gvapython class=OCR module=/home/pipeline-server/extensions/OCR_post_processing_0012.py name=ocr_postprocess $AGGREGATE ! gvapython name=barcode class=BarcodeDetection module=/home/pipeline-server/extensions/barcode_nv12_to_gray.py kwarg=\"{\\\"reclassify_interval\\\": $BARCODE_RECLASSIFY_INTERVAL}\" !  gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid\"_gst\".jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst-launch_$cid\"_gst\".log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid\"_gst\".log)"
 
 echo "$gstLaunchCmd"
 

configs/opencv-ovms/gst/run_gst.sh

@@ -0,0 +1,30 @@
+#!/bin/bash
+#
+# Copyright (C) 2024 Intel Corporation.
+#
+# SPDX-License-Identifier: Apache-2.0
+#
+
+cl_cache_dir="/home/pipeline-server/.cl-cache" \
+DISPLAY="$DISPLAY" \
+RESULT_DIR="/tmp/result" \
+DECODE="$DECODE" \
+DEVICE="$DEVICE" \
+PRE_PROCESS="$PRE_PROCESS" \
+AGGREGATE="$AGGREGATE" \
+OUTPUTFORMAT="$OUTPUTFORMAT" \
+BARCODE_RECLASSIFY_INTERVAL="$BARCODE_INTERVAL" \
+OCR_RECLASSIFY_INTERVAL="$OCR_INTERVAL" \
+OCR_DEVICE="$OCR_DEVICE" \
+LOG_LEVEL="$LOG_LEVEL" \
+GST_DEBUG="$GST_DEBUG" \
+LOW_POWER="$LOW_POWER" \
+cid_count="$cid_count" \
+inputsrc="$inputsrc" \
+RUN_MODE="$RUN_MODE" \
+CPU_ONLY="$CPU_ONLY" \
+OCR_RECLASSIFY_INTERVAL="$OCR_RECLASSIFY_INTERVAL" \
+BARCODE_RECLASSIFY_INTERVAL="$BARCODE_RECLASSIFY_INTERVAL" \
+AUTO_SCALE_FLEX_140="$AUTO_SCALE_FLEX_140" \
+PIPELINE_SCRIPT="$PIPELINE_SCRPT" \
+/opencv-ovms/scripts/run_gst.sh --pipeline_script_choice "$PIPELINE_SCRIPT"

configs/opencv-ovms/gst_capi/launch-pipeline.sh

@@ -21,5 +21,5 @@ BARCODE=$9
 # Obtaining codec_type (avc or hevc)
 is_avc=`gst-discoverer-1.0 "$INPUTSRC" | grep -i h.264 | wc -l`
 
-echo "./$PIPELINE_EXEC_PATH $INPUTSRC $USE_ONEVPL $RENDER_MODE $RENDER_PORTRAIT_MODE $is_avc $WINDOW_WIDTH $WINDOW_HEIGHT $DETECTION_THRESHOLD" "$BARCODE"
+echo "inside launch-pipeline.sh and the command is ./$PIPELINE_EXEC_PATH $INPUTSRC $USE_ONEVPL $RENDER_MODE $RENDER_PORTRAIT_MODE $is_avc $WINDOW_WIDTH $WINDOW_HEIGHT $DETECTION_THRESHOLD" "$BARCODE"
 ./"$PIPELINE_EXEC_PATH" "$INPUTSRC" "$USE_ONEVPL" "$RENDER_MODE" "$RENDER_PORTRAIT_MODE" "$is_avc" "$WINDOW_WIDTH" "$WINDOW_HEIGHT" "$DETECTION_THRESHOLD" "$BARCODE"

configs/opencv-ovms/gst_capi/pipelines/capi_yolov5/main.cpp

@@ -1,5 +1,5 @@
 //*****************************************************************************
-// Copyright 2023 Intel Corporation
+// Copyright 2024 Intel Corporation
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -28,6 +28,14 @@
 #include <mutex>
 #include <condition_variable>
 
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <unistd.h>
+#include <sys/types.h>
+#include <sys/socket.h>
+#include <netinet/in.h>
+
 #include <signal.h>
 #include <stdio.h>
 #include <sstream>
@@ -738,12 +746,13 @@ bool loadOVMS()
      OVMS_ServerSettingsSetLogLevel(_serverSettings, OVMS_LOG_ERROR);
 
      char * ovmsCofigJsonFilePath = std::getenv("OVMS_MODEL_CONFIG_JSON");
-     std::cout << "ovmsCofigJsonFilePath: "<<ovmsCofigJsonFilePath<<std::endl;
      if (ovmsCofigJsonFilePath == nullptr ) { 
          std::cout << "error: could not find env OVMS_MODEL_CONFIG_JSON, exiting"<<std::endl;
          return false;
      }
 
+     std::cout << "ovmsCofigJsonFilePath: "<<ovmsCofigJsonFilePath<<std::endl;
+
      OVMS_ModelsSettingsSetConfigPath(_modelsSettings, ovmsCofigJsonFilePath);
 
      if (!createModelServer()) {
@@ -1045,29 +1054,50 @@ void print_usage(const char* programName) {
         << "detection_threshold is confidence threshold value in floating point that needs to be between 0.0 to 1.0\n";
 }
 
-int get_running_servers() {
-    char buffer[128];
-    string cmd = "echo $cid_count";
-    std::string result = "";
-    FILE* pipe = popen(cmd.c_str(), "r");
-
-    if (!pipe) 
-        throw std::runtime_error("popen() failed!");
+int getFreePort(const int startingPort) {
+    struct sockaddr_in sin;
+    int gotSocket, gotPortNum = -1;
 
-    try 
-    {
-        while (fgets(buffer, sizeof buffer, pipe) != NULL) 
-        {
-            result += buffer;
+    gotSocket = socket(AF_INET, SOCK_STREAM, 0);
+    if(gotSocket == -1) {
+        std::cout << "ERROR: failed to get socket...." << std::endl;
+        return -1;
+    } else {
+        std::cout << "found socket handler: " << gotSocket << std::endl;
+    }
+
+    // use port 0 to let system chooses a random free port
+    sin.sin_port = htons(0);
+    sin.sin_addr.s_addr = 0;
+    sin.sin_addr.s_addr = INADDR_ANY;
+    sin.sin_family = AF_INET;
+
+    if (bind(gotSocket, (struct sockaddr *)&sin, sizeof(struct sockaddr_in)) == -1) {
+        std::cout << "ERROR: system unable to bind to find free port..." << std::endl;
+        return -1;
+    }
+
+    // retrieve the port number that system just bound
+    socklen_t len = sizeof(sin);
+    if (getsockname(gotSocket, (struct sockaddr *)&sin, &len) != -1) {
+        gotPortNum = ntohs(sin.sin_port);
+        if (gotPortNum >= startingPort) {
+            std::cout << "found a port number " << gotPortNum << " that is no less than the starting port number " << startingPort << std::endl;
+        } else {
+            // port number found still less than the starting port number: continue searching...
+            gotPortNum = getFreePort(startingPort);
         }
-    } 
-    catch (...) 
-    {
-        pclose(pipe);
-        throw;
+    } else {
+        std::cout << "ERROR: failed to get socket name for socket handle " << gotSocket << std::endl;
+        gotPortNum = -1;
+    }
+
+    if (gotPortNum != -1) {
+        // ready to be used, close it so it is not in use anymore
+        close(gotSocket);
     }
-    pclose(pipe);
-    return std::stoi(result.c_str());
+
+    return gotPortNum;
 }
 
 int main(int argc, char** argv) {
@@ -1077,9 +1107,21 @@ int main(int argc, char** argv) {
     _mediaService = new GStreamerMediaPipelineService();
 
     // get valid server port numbers
-    int running_servers = get_running_servers();
-    _server_grpc_port = 9178 + running_servers;
-    _server_http_port = 11338 + running_servers;
+    int grpcPort = getFreePort(9178);
+    if (grpcPort == -1) {
+        std::cout << "ERROR: failed to get free port number for GRPC port starting from 9178" << std::endl;
+        return 1;
+    }
+    std::cout << "got GRPC port number: " << grpcPort << std::endl;
+    _server_grpc_port = grpcPort;
+
+    int httpPort = getFreePort(11338);
+    if (httpPort == -1) {
+        std::cout << "ERROR: failed to get free port number for HTTP port starting from 11338" << std::endl;
+        return 1;
+    }
+    std::cout << "got HTTP port number: " << httpPort << std::endl;
+    _server_http_port = httpPort;
 
     _videoStreamPipeline = "people-detection.mp4";
 
@@ -1124,6 +1166,7 @@ int main(int argc, char** argv) {
     GstElement *appsink;
     ObjectDetectionInterface* objDet;
     getMAPipeline(_videoStreamPipeline, &pipeline,  &appsink, &objDet);
+
     running_streams.emplace_back(run_stream, _videoStreamPipeline, pipeline, appsink, objDet);
 
     if (!loadOVMS())