feat: streamlining result log filename for preparation of benchmarkin…

…g different pipelines at the same time Signed-off-by: Jim Wang <yutsung.jim.wang@intel.com>
intel-retail · Nov 5, 2024 · 57f4305 · 57f4305
1 parent d14ed02
commit 57f4305
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diff --git a/Makefile b/Makefile
@@ -90,15 +90,15 @@ build-benchmark:
 	cd performance-tools && $(MAKE) build-benchmark-docker
 
 benchmark: build-benchmark download-models
-	cd performance-tools/benchmark-scripts && python benchmark.py --compose_file ../../src/docker-compose.yml \
+	cd performance-tools/benchmark-scripts && python benchmark.py --compose_file ../../src/$(DOCKER_COMPOSE) \
 	--pipeline $(PIPELINE_COUNT) --duration $(BENCHMARK_DURATION) --results_dir $(RESULTS_DIR)
 # consolidate to show the summary csv
 	@cd performance-tools/benchmark-scripts && ROOT_DIRECTORY=$(RESULTS_DIR) $(MAKE) --no-print-directory consolidate && \
 	echo "Loss Prevention benchmark results are saved in $(RESULTS_DIR)/summary.csv file" && \
 	echo "====== Loss prevention benchmark results summary: " && cat $(RESULTS_DIR)/summary.csv
 
 benchmark-stream-density: build-benchmark download-models
-	cd performance-tools/benchmark-scripts && python benchmark.py --compose_file ../../src/docker-compose.yml \
+	cd performance-tools/benchmark-scripts && python benchmark.py --compose_file ../../src/$(DOCKER_COMPOSE) \
 	--target_fps $(TARGET_FPS) --density_increment 1 --results_dir $(RESULTS_DIR)
 
 clean-benchmark-results:

diff --git a/src/docker-compose-2-clients.yml b/src/docker-compose-2-clients.yml
@@ -0,0 +1,113 @@
+#
+# Copyright (C) 2024 Intel Corporation.
+#
+# SPDX-License-Identifier: Apache-2.0
+#
+
+
+ ## Current Developer Toolbox doesn't support environment files, make sure to remove any files or environment variables starting with $
+version: '3.7'
+services:
+  camera-simulator:
+    container_name: camera-simulator
+    image: aler9/rtsp-simple-server
+    ports:
+      - "127.0.0.1:8554:8554"
+  camera-simulator0:
+    image: jrottenberg/ffmpeg:4.1-alpine
+    container_name: camera-simulator0
+    network_mode: "host"
+    entrypoint: ["/bin/sh","-c"]
+    command: 
+    - | 
+       if [ ! -f /home/pipeline-server/sample-media/coca-cola-4465029-1920-15-bench.mp4 ]; then
+          mkdir -p /home/pipeline-server/sample-media
+          wget -O /home/pipeline-server/sample-media/coca-cola-4465029-1920-15-bench.mp4 https://www.pexels.com/download/video/4465029
+       fi
+       ffmpeg -nostdin -re -stream_loop -1 -i /home/pipeline-server/sample-media/coca-cola-4465029-1920-15-bench.mp4 -c copy -f rtsp -rtsp_transport tcp rtsp://localhost:8554/camera_0
+    depends_on:
+      - camera-simulator
+    volumes:
+      - ${RETAIL_USE_CASE_ROOT:-..}/performance-tools/sample-media:/home/pipeline-server/sample-media
+
+  OvmsClientGst1:
+    image: dlstreamer:dev
+    deploy:
+      mode: replicated
+      replicas: ${PIPELINE_COUNT:-1}
+    network_mode: "host"
+    entrypoint: /script/entrypoint.sh --pipeline_script_choice ${PIPELINE_SCRIPT:-yolov5s.sh}
+    privileged: true
+    ipc: "host"
+    env_file:
+      - ./res/gst.env
+      - ${DEVICE_ENV:-res/all-cpu.env}
+    environment:
+      - CONTAINER_NAME=gst1
+      - INPUTSRC=${INPUTSRC:-rtsp://localhost:8554/camera_0}
+      - RENDER_MODE=${RENDER_MODE:-0} #RENDER_MODE=1 will work only after running xhost +local:docker
+      - DISPLAY=$DISPLAY
+      - HTTP_PROXY
+      - HTTPS_PROXY
+      - NO_PROXY
+    volumes:
+      - ${RESULTS_DIR:-../results}:/tmp/results
+      - ~/.Xauthority:/home/dlstreamer/.Xauthority
+      - /tmp/.X11-unix
+      - ~/.cl-cache:/home/pipeline-server/.cl-cache
+      - ./res/:/home/pipeline-server/envs
+      - ${RETAIL_USE_CASE_ROOT:-..}/models:/home/pipeline-server/models
+      - ./pipelines/:/home/pipeline-server/pipelines
+      - ./extensions/:/home/pipeline-server/extensions
+
+  OvmsClientGst2:
+    image: dlstreamer:dev
+    deploy:
+      mode: replicated
+      replicas: ${PIPELINE_COUNT:-1}
+    network_mode: "host"
+    entrypoint: /script/entrypoint.sh --pipeline_script_choice ${PIPELINE_SCRIPT:-yolov8s_roi.sh}
+    privileged: true
+    ipc: "host"
+    env_file:
+      - ./res/gst.env
+      - ${DEVICE_ENV:-res/all-cpu.env}
+    environment:
+      - CONTAINER_NAME=gst2
+      - INPUTSRC=${INPUTSRC:-rtsp://localhost:8554/camera_0}
+      - RENDER_MODE=${RENDER_MODE:-0} #RENDER_MODE=1 will work only after running xhost +local:docker
+      - DISPLAY=$DISPLAY
+      - HTTP_PROXY
+      - HTTPS_PROXY
+      - NO_PROXY
+    volumes:
+      - ${RESULTS_DIR:-../results}:/tmp/results
+      - ~/.Xauthority:/home/dlstreamer/.Xauthority
+      - /tmp/.X11-unix
+      - ~/.cl-cache:/home/pipeline-server/.cl-cache
+      - ./res/:/home/pipeline-server/envs
+      - ${RETAIL_USE_CASE_ROOT:-..}/models:/home/pipeline-server/models
+      - ./pipelines/:/home/pipeline-server/pipelines
+      - ./extensions/:/home/pipeline-server/extensions      
+
+  mosquitto:
+    image: eclipse-mosquitto:2.0
+    container_name: mosquitto
+    network_mode: "host"
+    ports:
+      - "127.0.0.1:1883:1883"
+    depends_on:
+      - OvmsClientGst1
+      - OvmsClientGst2    
+
+  mqtt_tracker:
+    image: loss-prevention:dev
+    network_mode: "host"
+    environment:
+      - MQTT_URL=127.0.0.1
+      - MQTT_PORT=1883
+      - MQTT_TOPIC=event/detection
+      - ROI_NAME=BASKET
+    restart: always
+    depends_on:
+      - mosquitto
diff --git a/src/entrypoint.sh b/src/entrypoint.sh
@@ -19,6 +19,7 @@ checkBatchSize() {
 }
 
 cid_count="${cid_count:=0}"
+CONTAINER_NAME="${CONTAINER_NAME:=gst}"
 cameras="${cameras:=}"
 stream_density_mount="${stream_density_mount:=}"
 stream_density_params="${stream_density_params:=}"
@@ -125,14 +126,15 @@ fi
 
 # generate unique container id based on the date with the precision upto nano-seconds
 cid=$(date +%Y%m%d%H%M%S%N)
+cid="${cid}"_${CONTAINER_NAME}
 echo "cid: $cid"
 
-touch /tmp/results/r"$cid"_gst.jsonl
-chown 1000:1000 /tmp/results/r"$cid"_gst.jsonl
-touch /tmp/results/gst-launch_"$cid"_gst.log
-chown 1000:1000 /tmp/results/gst-launch_"$cid"_gst.log
-touch /tmp/results/pipeline"$cid"_gst.log
-chown 1000:1000 /tmp/results/pipeline"$cid"_gst.log
+touch /tmp/results/r"$cid".jsonl
+chown 1000:1000 /tmp/results/r"$cid".jsonl
+touch /tmp/results/gst-launch_"$cid".log
+chown 1000:1000 /tmp/results/gst-launch_"$cid".log
+touch /tmp/results/pipeline"$cid".log
+chown 1000:1000 /tmp/results/pipeline"$cid".log
 
 cl_cache_dir="/home/pipeline-server/.cl-cache" \
 DISPLAY="$DISPLAY" \

diff --git a/src/pipelines/age_recognition.sh b/src/pipelines/age_recognition.sh
@@ -7,7 +7,7 @@
 
 PRE_PROCESS="${PRE_PROCESS:=""}" #""|pre-process-backend=vaapi-surface-sharing|pre-process-backend=vaapi-surface-sharing pre-process-config=VAAPI_FAST_SCALE_LOAD_FACTOR=1 
 AGGREGATE="${AGGREGATE:="gvametaaggregate name=aggregate !"}" # Aggregate function at the end of the pipeline ex. "" | gvametaaggregate name=aggregate
-PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid\"_gst\".jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
+PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid.jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
 
 CLASSIFICATION_OPTIONS="${CLASSIFICATION_OPTIONS:="reclassify-interval=1 $DETECTION_OPTIONS"}" # Extra Classification model parameters ex. "" | reclassify-interval=1 batch-size=1 nireq=4 gpu-throughput-streams=4
 
@@ -29,7 +29,7 @@ gstLaunchCmd="gst-launch-1.0 $inputsrc ! $DECODE ! \
 gvadetect batch-size=$BATCH_SIZE model-instance-id=odmodel name=detection model=$DETECT_MODEL_PATH threshold=.8 device=$DEVICE ! \
 gvaclassify batch-size=$BATCH_SIZE model-instance-id=classifier name=recognition model-proc=$CLASS_MODEL_PROC_PATH model=$CLASS_MODEL_PATH device=$DEVICE $CLASSIFICATION_OPTIONS ! \
 $AGGREGATE gvametaconvert name=metaconvert add-empty-results=true ! \
-gvametapublish name=destination file-format=2 file-path=/tmp/results/r$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$cid\"_gst\".log)"
+gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid.jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst-launch_$cid.log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid.log)"
 
 echo "$gstLaunchCmd"
 

diff --git a/src/pipelines/people_detection.sh b/src/pipelines/people_detection.sh
@@ -7,7 +7,7 @@
 
 PRE_PROCESS="${PRE_PROCESS:=""}" #""|pre-process-backend=vaapi-surface-sharing|pre-process-backend=vaapi-surface-sharing pre-process-config=VAAPI_FAST_SCALE_LOAD_FACTOR=1 
 AGGREGATE="${AGGREGATE:="gvametaaggregate name=aggregate !"}" # Aggregate function at the end of the pipeline ex. "" | gvametaaggregate name=aggregate
-PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid\"_gst\".jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
+PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid.jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
 
 ROI="${ROI:="0,0,400,400"}"
 
@@ -20,7 +20,7 @@ fi
 echo "decode type $DECODE"
 echo "Run person-detection pipeline on $DEVICE with batch size = $BATCH_SIZE"
 
-gstLaunchCmd="GST_DEBUG=\"GST_TRACER:7\" GST_TRACERS=\"latency_tracer(flags=pipeline,interval=100)\" gst-launch-1.0 $inputsrc ! $DECODE ! gvaattachroi roi=$ROI ! gvadetect batch-size=$BATCH_SIZE model-instance-id=odmodel name=detection model=models/object_detection/person-detection-0200/FP16-INT8/person-detection-0200.xml threshold=.5 device=$DEVICE $PRE_PROCESS inference-region=1 ! $AGGREGATE gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$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)"
+gstLaunchCmd="GST_DEBUG=\"GST_TRACER:7\" GST_TRACERS=\"latency_tracer(flags=pipeline,interval=100)\" gst-launch-1.0 $inputsrc ! $DECODE ! gvaattachroi roi=$ROI ! gvadetect batch-size=$BATCH_SIZE model-instance-id=odmodel name=detection model=models/object_detection/person-detection-0200/FP16-INT8/person-detection-0200.xml threshold=.5 device=$DEVICE $PRE_PROCESS inference-region=1 ! $AGGREGATE gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid.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.log)"
 
 echo "$gstLaunchCmd"
 

diff --git a/src/pipelines/yolov5s.sh b/src/pipelines/yolov5s.sh
@@ -7,7 +7,7 @@
 
 PRE_PROCESS="${PRE_PROCESS:=""}" #""|pre-process-backend=vaapi-surface-sharing|pre-process-backend=vaapi-surface-sharing pre-process-config=VAAPI_FAST_SCALE_LOAD_FACTOR=1 
 AGGREGATE="${AGGREGATE:="gvametaaggregate name=aggregate !"}" # Aggregate function at the end of the pipeline ex. "" | gvametaaggregate name=aggregate
-PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid\"_gst\".jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
+PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid.jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
 
 if [ "$RENDER_MODE" == "1" ]; then
     OUTPUT="${OUTPUT:="! videoconvert ! video/x-raw,format=I420 ! gvawatermark ! videoconvert ! fpsdisplaysink video-sink=ximagesink sync=true --verbose"}"
@@ -18,7 +18,7 @@ fi
 echo "decode type $DECODE"
 echo "Run yolov5s pipeline on $DEVICE with batch size = $BATCH_SIZE"
 
-gstLaunchCmd="GST_DEBUG=\"GST_TRACER:7\" GST_TRACERS=\"latency_tracer(flags=pipeline,interval=100)\" gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect batch-size=$BATCH_SIZE model-instance-id=odmodel name=detection model=models/object_detection/yolov5s/FP16-INT8/yolov5s.xml model-proc=models/object_detection/yolov5s/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)"
+gstLaunchCmd="GST_DEBUG=\"GST_TRACER:7\" GST_TRACERS=\"latency_tracer(flags=pipeline,interval=100)\" gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect batch-size=$BATCH_SIZE model-instance-id=odmodel name=detection model=models/object_detection/yolov5s/FP16-INT8/yolov5s.xml model-proc=models/object_detection/yolov5s/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.jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst-launch_$cid.log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid.log)"
 
 echo "$gstLaunchCmd"
 

diff --git a/src/pipelines/yolov5s_effnetb0.sh b/src/pipelines/yolov5s_effnetb0.sh
@@ -7,7 +7,7 @@
 
 if [ "$INPUTSRC_TYPE" == "REALSENSE" ]; then
 	# TODO: update with vaapipostproc when MJPEG codec is supported.
-	echo "Not supported until D436 with MJPEG." > /tmp/results/pipeline$cid_count.log
+	echo "Not supported until D436 with MJPEG." > /tmp/results/pipeline$cid.log
 	exit 2
 fi
 
@@ -17,7 +17,7 @@ DETECTION_OPTIONS="${DETECTION_OPTIONS:="gpu-throughput-streams=4 nireq=4 batch-
 
 CLASSIFICATION_OPTIONS="${CLASSIFICATION_OPTIONS:="reclassify-interval=1 $DETECTION_OPTIONS"}" # Extra Classification model parameters ex. "" | reclassify-interval=1 batch-size=1 nireq=4 gpu-throughput-streams=4
 
-PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid\"_gst\".jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
+PUBLISH="${PUBLISH:="name=destination file-format=2 file-path=/tmp/results/r$cid.jsonl"}" # address=localhost:1883 topic=inferenceEvent method=mqtt
 
 if [ "$RENDER_MODE" == "1" ]; then
     OUTPUT="${OUTPUT:="! videoconvert ! video/x-raw,format=I420 ! gvawatermark ! videoconvert ! fpsdisplaysink video-sink=ximagesink sync=true --verbose"}"
@@ -27,7 +27,7 @@ fi
 
 echo "Run run yolov5s with efficientnet classification pipeline on $DEVICE with batch size = $BATCH_SIZE"
 
-gstLaunchCmd="gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect batch-size=$BATCH_SIZE model-instance-id=odmodel name=detection model=/home/pipeline-server/models/object_detection/yolov5s/FP16-INT8/yolov5s.xml model-proc=/home/pipeline-server/models/object_detection/yolov5s/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS $DETECTION_OPTIONS ! gvatrack name=tracking tracking-type=zero-term-imageless ! queue max-size-bytes=0 max-size-buffers=0 max-size-time=0 ! gvaclassify model-instance-id=clasifier labels=/home/pipeline-server/models/object_classification/efficientnet-b0/imagenet_2012.txt model=/home/pipeline-server/models/object_classification/efficientnet-b0/FP32/efficientnet-b0.xml model-proc=/home/pipeline-server/models/object_classification/efficientnet-b0/efficientnet-b0.json device=$CLASSIFICATION_DEVICE inference-region=roi-list name=classification $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)"
+gstLaunchCmd="gst-launch-1.0 $inputsrc ! $DECODE ! gvadetect batch-size=$BATCH_SIZE model-instance-id=odmodel name=detection model=/home/pipeline-server/models/object_detection/yolov5s/FP16-INT8/yolov5s.xml model-proc=/home/pipeline-server/models/object_detection/yolov5s/yolov5s.json threshold=.5 device=$DEVICE $PRE_PROCESS $DETECTION_OPTIONS ! gvatrack name=tracking tracking-type=zero-term-imageless ! queue max-size-bytes=0 max-size-buffers=0 max-size-time=0 ! gvaclassify model-instance-id=clasifier labels=/home/pipeline-server/models/object_classification/efficientnet-b0/imagenet_2012.txt model=/home/pipeline-server/models/object_classification/efficientnet-b0/FP32/efficientnet-b0.xml model-proc=/home/pipeline-server/models/object_classification/efficientnet-b0/efficientnet-b0.json device=$CLASSIFICATION_DEVICE inference-region=roi-list name=classification $CLASSIFICATION_PRE_PROCESS $CLASSIFICATION_OPTIONS ! gvametaconvert name=metaconvert add-empty-results=true ! gvametapublish name=destination file-format=2 file-path=/tmp/results/r$cid.jsonl $OUTPUT 2>&1 | tee >/tmp/results/gst-launch_$cid.log >(stdbuf -oL sed -n -e 's/^.*current: //p' | stdbuf -oL cut -d , -f 1 > /tmp/results/pipeline$cid.log)"
 
 echo "$gstLaunchCmd"