Vitis AI is Xilinx’s development stack for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards. - Xilinx/Vitis-AI

<< endl; return; } float mean [3] = {104, 107, 123}; auto input_tensor_buffers = runner->get_inputs (); auto output_tensor_buffers = runner->get_outputs (); CHECK_EQ (input_tensor_buffers.size (), 1u) …

"""Benchmark DPU FPS performance over Vitis AI APIs execute_async() and wait() """ """Uncomment the following code snippet to include softmax calculation for models end-to-end FPS evaluation """

Accuracy: 0.973339 Sensitivity/Recall: 0.163494 Specificity: 0.989558 FAR/FPR: 0.0104421 MDR/FNR: 0.836506 Total frames inferred: 11140 Total timetaken: 63.566 seconds.. Throughput (fps): 175.25 …

If users provide a huge dataset, e.g. 50000 images in the directory, they can use the variable to control the test time, and no need to run the whole dataset. """ cnt = 360 """run with batch """ time_start = …

% (n_images)) r_n = 20 t = 0.0 for i in tqdm (range (r_n)): t_ = run (wego_mod, all_images, args.threads) t += t_ print ("===================== Perf Result =====================") print (" [Total …

echo -e " [ERROR] Check Usage with: ./app_test.sh -h " echo -e "" exit 1 fi CPP_EXE="./app.exe" if [ "$performance_diff" -eq 0 ]; then exec_args="$config_file $xmodel_file $img_dir $sw_pre_proc …

time_end = time.time () timetotal = time_end - time_start total_frames = cnt * int (threadnum) fps = float (total_frames / timetotal) print ( "FPS=%.2f, total frames = %.2f , time=%.6f seconds" % (fps, …

external_yolov3_tutorial.ipynb run_external_yolov3.py run_mxnet_resnet_18.py run_mxnet_resnet_18_zynq_fps.py setup_custom_yolov3.sh setup_custom_yolov3_zynq.sh …

The vai_benchmark is a utility tool provided by Vitis AI. It allows users to perform comprehensive performance testing, both end-to-end and DPU-only, by utilizing supported sample programs in Vitis …