There are various use cases available, click one each hyperlink to find out more details:
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to build run:
make build-gst
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run one gst dlstreamer pipeline and use the default object detection only (yolov5s.sh)
make run-gst
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run three gst dlstreamer pipelines and use the default object detection only (yolov5s.sh)
PIPELINE_COUNT=3 make run-gst
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run two gst dlstreamer pipelines and use the object detection with classification (yolov5s_effnetb0.sh)
PIPELINE_SCRIPT=yolov5s_effnetb0.sh PIPELINE_COUNT=2 make run-gst
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shutdown Docker containers
make down-gst
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clean up the output results
make clean-results
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to build run:
make build-grpc_python
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run one grpc_python pipeline and use the default model (instance-segmentation-security-1040)
make run-grpc_python
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show the supported MODEL_NAME for grpc_python
make list-grpc-python-model-names
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run three grpc_python pipelines and use yolov5s model
PIPELINE_COUNT=3 MODEL_NAME=yolov5s make run-grpc_python
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shutdown Docker containers
make down-grpc_python
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clean up the output results
make clean-results
There are three different pipelines for gst_capi use cases: capi_yolov5, capi_yolov5_ensemble, and capi_face_detection.
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to build all capis run:
make build-all-capis
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to build one at a time run:
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for capi_yolov5
make build-capi_yolov5
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for capi_yolov5_ensemble
make build-capi_yolov5_ensemble
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for capi_face_detection
make build-capi_face_detection
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run one capi_yolov5 pipeline
make run-capi_yolov5
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shutdown capi_yolov5
make down-capi_yolov5
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run one capi_yolov5_ensemble pipeline
make run-capi_yolov5_ensemble
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shutdown capi_yolov5_ensemble
make down-capi_yolov5_ensemble
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run one capi_face_detection pipeline
make run-capi_face_detection
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shutdown capi_face_detection
make down-capi_face_detection
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run two capi_yolov5_ensemble pipelines
PIPELINE_COUNT=2 make run-capi_yolov5_ensemble
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shutdown Docker containers
make down-capi_yolov5 make down-capi_yolov5_ensemble make down-capi_face_detection
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clean up the output results
make clean-results
There are three different pipelines for demos use case: classification, instance_segmentation, and object_detection.
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to build run:
make build-demos
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run one classification pipeline
make run-demo-classification
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run one instance segmentation pipeline
make run-demo-instance-segmentation
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run two object detection pipelines
PIPELINE_COUNT=2 make run-demo-object-detection
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shutdown classification pipeline Docker container
make down-demo-classification
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shutdown all Docker containers
make down-demos-all
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clean up the output results
make clean-results
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to build run:
make build-grpc-go
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run one grpc_go pipeline
make run-grpc-go
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run two grpc_go pipelines
PIPELINE_COUNT=2 make run-grpc-go
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shutdown Docker containers
make down-grpc-go
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clean up the output results
make clean-results
Run the following commands by changing directory to ./retail-use-cases/use-cases/demos
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build pytorch pipeline
make build_pytorch
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run one pytorch pipeline
make run_pytorch_object_detection
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run two pytorch pipelines
PIPELINE_COUNT=2 make run_pytorch_object_detection
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shutdown Docker containers
make down_pytorch_object_detection
Run the following command by changing directory to ./retail-use-cases
-
clean up the output results
make clean-results
Run the following commands by changing directory to ./retail-use-cases/use-cases/demos
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build tensorflow keras pipeline
make build_tensorflow_keras
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run one tensorflow keras pipeline
make run_tensorflow_keras_classification
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run two tensorflow keras pipelines
PIPELINE_COUNT=2 make run_tensorflow_keras_classification
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shutdown Docker containers
make down_tensorflow_keras_classification
Run the following command by changing directory to ./retail-use-cases
-
clean up the output results
make clean-results
GStreamer is an open source framework licensed under LGPL. See https://gstreamer.freedesktop.org/documentation/frequently-asked-questions/licensing.html?gi-language=c. You are solely responsible for determining if your use of Gstreamer requires any additional licenses. Intel is not responsible for obtaining any such licenses, nor liable for any licensing fees due, in connection with your use of Gstreamer.
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