RT-DETR r50 demo

samples/README.md

@@ -140,3 +140,9 @@ Sample location: [kafka_redis_adapter](./kafka_redis_adapter)
 A sample demonstrating the use of pass-through mode in Savant.
 
 Sample location: [pass_through_processing](./pass_through_processing)
+
+### RT-DETR R50 Demo
+
+A sample demonstrating the use of RT-DETR model in Savant.
+
+Sample location: [rtdetr](./rtdetr/)

samples/rtdetr/README.md

@@ -0,0 +1,55 @@
+# RT-DETR R50 Demo
+
+The sample shows how RT-DETR model can be used in a Savant module.
+
+The detector model was prepared in the ONNX format using instructions from [DeepStream-Yolo repo](https://github.com/marcoslucianops/DeepStream-Yolo/blob/master/docs/RTDETR.md).
+
+Weights used: `v0.1/rtdetr_r50vd_6x_coco_from_paddle.pth`  from the [RT-DETR releases](https://github.com/lyuwenyu/storage/releases).
+
+Tested on platforms:
+
+- Nvidia Turing.
+
+Demonstrated operational modes:
+
+- real-time processing: RTSP streams.
+
+Demonstrated adapters:
+
+- RTSP source adapter;
+- Always-ON RTSP sink adapter.
+
+## Prerequisites
+
+```bash
+git clone https://github.com/insight-platform/Savant.git
+cd Savant
+git lfs pull
+./utils/check-environment-compatible
+```
+
+**Note**: Ubuntu 22.04 runtime configuration [guide](https://insight-platform.github.io/Savant/develop/getting_started/0_configure_prod_env.html) helps to configure the runtime to run Savant pipelines.
+
+## Build Engines
+
+The demo uses models that are compiled into TensorRT engines the first time the demo is run. This takes time. Optionally, you can prepare the engines before running the demo by using the command:
+
+```bash
+# you are expected to be in Savant/ directory
+
+./samples/rtdetr/build_engines.sh
+```
+
+## Run Demo
+
+```bash
+# you are expected to be in Savant/ directory
+
+# if x86
+docker compose -f samples/rtdetr/docker-compose.x86.yml up
+
+# open 'rtsp://127.0.0.1:554/stream' in your player
+# or visit 'http://127.0.0.1:888/stream/' (LL-HLS)
+
+# Ctrl+C to stop running the compose bundle
+```

samples/rtdetr/build_engines.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+# you are expected to be in Savant/ directory
+
+MODULE_CONFIG=samples/rtdetr/module.yml
+
+if [ "$(uname -m)" = "aarch64" ]; then
+  echo "aarch64 not supported for this demo."
+else
+  docker compose -f samples/rtdetr/docker-compose.x86.yml build module
+fi
+
+./scripts/run_module.py -i rtdetr-module --build-engines $MODULE_CONFIG

samples/rtdetr/docker-compose.x86.yml

@@ -0,0 +1,68 @@
+version: "3.3"
+services:
+
+  video-loop-source:
+    image: ghcr.io/insight-platform/savant-adapters-gstreamer:latest
+    restart: unless-stopped
+    volumes:
+      - zmq_sockets:/tmp/zmq-sockets
+      - /tmp/video-loop-source-downloads:/tmp/video-loop-source-downloads
+    environment:
+      - LOCATION=https://eu-central-1.linodeobjects.com/savant-data/demo/leeds_1080p.mp4
+      - DOWNLOAD_PATH=/tmp/video-loop-source-downloads
+      - ZMQ_ENDPOINT=dealer+connect:ipc:///tmp/zmq-sockets/input-video.ipc
+      - SOURCE_ID=leeds
+      - SYNC_OUTPUT=True
+    entrypoint: /opt/savant/adapters/gst/sources/video_loop.sh
+    depends_on:
+      module:
+        condition: service_healthy
+
+  module:
+    build:
+      context: .
+      dockerfile: docker/Dockerfile.x86
+    volumes:
+      - zmq_sockets:/tmp/zmq-sockets
+      - ../../models/rtdetr:/models
+      - ../../downloads/rtdetr:/downloads
+      - .:/opt/savant/samples/rtdetr
+    command: samples/rtdetr/module.yml
+    environment:
+      - ZMQ_SRC_ENDPOINT=router+bind:ipc:///tmp/zmq-sockets/input-video.ipc
+      - ZMQ_SINK_ENDPOINT=pub+bind:ipc:///tmp/zmq-sockets/output-video.ipc
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+  always-on-sink:
+    image: ghcr.io/insight-platform/savant-adapters-deepstream:latest
+    restart: unless-stopped
+    ports:
+      - "554:554"    # RTSP
+      - "1935:1935"  # RTMP
+      - "888:888"    # HLS
+      - "8889:8889"  # WebRTC
+    volumes:
+      - zmq_sockets:/tmp/zmq-sockets
+      - ../assets/stub_imgs:/stub_imgs
+    environment:
+      - ZMQ_ENDPOINT=sub+connect:ipc:///tmp/zmq-sockets/output-video.ipc
+      - SOURCE_ID=leeds
+      - STUB_FILE_LOCATION=/stub_imgs/smpte100_1920x1080.jpeg
+      - DEV_MODE=True
+    command: python -m adapters.ds.sinks.always_on_rtsp
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+volumes:
+  zmq_sockets:

samples/rtdetr/docker/Dockerfile.x86

@@ -0,0 +1,27 @@
+# build nvinfer custom library for yolo models (create engine and parse bbox functions)
+# https://github.com/marcoslucianops/DeepStream-Yolo
+FROM nvcr.io/nvidia/deepstream:6.3-triton-multiarch as builder
+
+ENV CUDA_VER=12.1
+ARG DS_YOLO_VER=5af9da189d91fa8808695c488a417f9f1c920b77
+ARG DS_YOLO_PATH=/opt/yolo
+ARG NVDSINFER_PATH=/opt/nvidia/deepstream/deepstream/sources/libs/nvdsinfer
+
+RUN git clone https://github.com/marcoslucianops/DeepStream-Yolo.git $DS_YOLO_PATH \
+    && cd $DS_YOLO_PATH \
+    && git checkout $DS_YOLO_VER \
+    && make -C nvdsinfer_custom_impl_Yolo
+
+# patch nvdsinfer_model_builder.cpp: use engine path to place created engine
+COPY nvdsinfer_model_builder.patch $NVDSINFER_PATH/
+RUN cd $NVDSINFER_PATH && \
+    patch nvdsinfer_model_builder.cpp < nvdsinfer_model_builder.patch && \
+    make
+
+FROM ghcr.io/insight-platform/savant-deepstream:latest
+
+ARG DS_YOLO_PATH=/opt/yolo
+ARG NVDSINFER_PATH=/opt/nvidia/deepstream/deepstream/sources/libs/nvdsinfer
+
+COPY --from=builder $DS_YOLO_PATH/nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so /opt/savant/lib/
+COPY --from=builder $NVDSINFER_PATH/libnvds_infer.so /opt/nvidia/deepstream/deepstream/lib/

samples/rtdetr/module.yml

@@ -0,0 +1,42 @@
+name: rtdetr_r50_demo
+
+parameters:
+  frame:
+    width: 1920
+    height: 1080
+  output_frame:
+    codec: ${oc.env:CODEC, 'h264'}
+  draw_func: {}
+  batch_size: 1
+
+  model_name: rtdetr_r50
+  model_ver: 5af9da1
+
+  model: ${parameters.model_name}_${parameters.model_ver}
+
+pipeline:
+
+  elements:
+    - element: nvinfer@detector
+      name: ${parameters.model_name}
+      model:
+        remote:
+          url: s3://savant-data/models/${parameters.model}/${parameters.model}.zip
+          checksum_url: s3://savant-data/models/${parameters.model}/${parameters.model}.md5
+          parameters:
+            endpoint: https://eu-central-1.linodeobjects.com
+        format: onnx
+
+        workspace_size: 6144
+        model_file: ${parameters.model_name}.onnx
+        label_file: labels.txt
+        custom_lib_path: /opt/savant/lib/libnvdsinfer_custom_impl_Yolo.so
+        parse_bbox_func_name: NvDsInferParseYolo
+        engine_create_func_name: NvDsInferYoloCudaEngineGet
+
+        input:
+          scale_factor: 0.0039215697906911373
+          maintain_aspect_ratio: False
+
+        output:
+          num_detected_classes: 80

samples/rtdetr/nvdsinfer_model_builder.patch

@@ -0,0 +1,14 @@
+--- nvdsinfer_model_builder.cpp	2023-04-20 13:36:23.753901493 +0700
++++ nvdsinfer_model_builder_new.cpp	2023-04-20 13:44:18.230221914 +0700
+@@ -830,6 +830,11 @@
+     suggestedPathName =
+         modelPath + "_b" + std::to_string(initParams.maxBatchSize) + "_" +
+         devId + "_" + networkMode2Str(networkMode) + ".engine";
++    /* Workaround for predictable engine file path. */
++    if (!string_empty(initParams.modelEngineFilePath))
++    {
++        suggestedPathName = initParams.modelEngineFilePath;
++    }
+     return engine;
+ }
+