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Yolov4 Demo

How to run yolov4

Model performant running with Trace+2CQ

For 320x320:

  • end-2-end perf is 80 FPS 
    pytest models/demos/yolov4/tests/perf/test_e2e_performant.py::test_e2e_performant[resolution0-True-1-act_dtype0-weight_dtype0-device_params0]

For 640x640:

  • end-2-end perf is 30 FPS 
    pytest models/demos/yolov4/tests/perf/test_e2e_performant.py::test_e2e_performant[resolution1-True-1-act_dtype0-weight_dtype0-device_params0]

Single Image Demo

  • Use the following command to run the yolov4 with a giraffe image:

For 320x320:

pytest models/demos/yolov4/demo.py::test_yolov4[device_params0-resolution0]

For 640x640:

pytest models/demos/yolov4/demo.py::test_yolov4[device_params0-resolution1]

  • The output file ttnn_yolov4_prediction_demo.jpg will be generated.

  • Use the following command to run the yolov4 with different input image:

    pytest  --disable-warnings --input-path=<PATH_TO_INPUT_IMAGE> models/demos/yolov4/demo.py

mAP Accuracy Test

  • To be added soon

Web Demo

  • You may try the interactive web demo (35 FPS end-2-end) for 320x320 following the instructions