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README.md
People count application With Deepstream SDK and Transfer Learning Toolkit
- Description
- Prerequisites
- Getting Started
- Build
- Run
- Output
- References
Description
This is a demo project for "People Count Application" using NVIDIA Deepstream SDK and Transfer Learning Toolkit (TLT).The application is based on deepstream-test5 application. It takes the input source data, uses PeopleNet model for inferencing and sends the people count data to cloud.
Prerequisites
Install Deepstream: [https://docs.nvidia.com/metropolis/deepstream/dev-guide/index.html#page/DeepStream_Development_Guide/deepstream_quick_start.html#]
Download PeopleNet model: [https://ngc.nvidia.com/catalog/models/nvidia:tlt_peoplenet]
This application is based on deepstream-test5 application. More about test5 application: [https://docs.nvidia.com/metropolis/deepstream/dev-guide/index.html#page/DeepStream_Development_Guide/deepstream_reference_app_test5.html]
Install Kafka: [https://kafka.apache.org/quickstart] and create the kafka topic:
tar -xzf kafka_2.13-2.6.0.tgz
cd kafka_2.13-2.6.0
bin/zookeeper-server-start.sh config/zookeeper.properties
bin/kafka-server-start.sh config/server.properties
bin/kafka-topics.sh --create --topic quickstart-events --bootstrap-server localhost:9092
Getting Started
- Preferably clone the repo in $DS_SDK_ROOT/sources/apps/sample_apps/
- Download peoplnet model:
cd demo/config && ./model.sh - For Jetson use: bin/jetson/libnvds_msgconv.so
- For x86 use: bin/x86/libnvds_msgconv.so
Build
cd demo && make
Run
./deepstream_test5 -c configs/test5_config_file_src_infer_tlt.txt
In another terminal run this command to see the kafka messages:
bin/kafka-console-consumer.sh --topic quickstart-events --from-beginning --bootstrap-server localhost:9092
Output
The output will look like this:
Where you can see the kafka messages for entry and exit count.
References
- CREATE INTELLIGENT PLACES USING NVIDIA PRE-TRAINED VISION MODELS AND DEEPSTREAM SDK: [https://info.nvidia.com/iva-occupancy-webinar-reg-page.html?ondemandrgt=yes]
- Deepstream SDK: [https://developer.nvidia.com/deepstream-sdk]
- Deepstream Quick Start Guide: [https://docs.nvidia.com/metropolis/deepstream/dev-guide/index.html#page/DeepStream_Development_Guide/deepstream_quick_start.html#]
- Transfer Learning Toolkit: [https://developer.nvidia.com/transfer-learning-toolkit]