Getting started with TI Jacinto 7 Edge AI/Demos/Classification
Run the Classification app
/opt/edge_ai_apps/apps_cpp/bin/Release/app_image_classification \ -m /opt/edge_ai_apps/models/classification/TFL-CL-000-mobileNetV1-mlperf \ -i /opt/edge_ai_apps/data/images/%04d.jpg \ -o output/classification_%d.jpg
- The help will show you the flags options
[docker] root@j7-evm:/opt/edge_ai_apps/apps_cpp/build# /opt/edge_ai_apps/apps_cpp/bin/Release/app_image_classification --help # # /opt/edge_ai_apps/apps_cpp/bin/Release/app_image_classification PARAMETERS [OPTIONAL PARAMETERS] # OPTIONS: # --model |-m Path to the model directory. # [--input |-i Source to gst pipeline camera or file.] # [--output |-o Set gst pipeline output display or file.] # [--device |-d Device name for camera input.] # [--index |-u Start index for multiple file input output.] # [--frame |-f Framerate of gstreamer pipeline for image input.] # [--no-curses |-n Disable curses report.] # [--connector |-c Connector id to select output display.] # [--log-level |-l Logging level to enable. [0: DEBUG 1:INFO 2:WARN 3:ERROR]. Default is 2. # [--help |-h] # # # (c) Texas Instruments 2021 #