OpenCV
This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests.
To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark opencv.
Project Site
opencv.orgSource Repository
github.comTest Created
22 September 2020Last Updated
18 March 2023Test Maintainer
Michael LarabelTest Type
SystemAverage Install Time
9 Minutes, 16 SecondsAverage Run Time
18 Minutes, 40 SecondsTest Dependencies
C/C++ Compiler Toolchain + JPEG Library + PNG Library + CMake + OpenCL + VulkanAccolades
30k+ DownloadsSupported Platforms
** Data based on those opting to upload their test results to OpenBenchmarking.org and users enabling the opt-in anonymous statistics reporting while running benchmarks from an Internet-connected platform.
*** Test profile page view reporting began March 2021.
Data updated weekly as of 13 April 2024.
Suites Using This Test
Performance Metrics
Analyze Test Configuration:OpenCV 4.4
Test: DNN - Deep Neural Network
OpenBenchmarking.org metrics for this test profile configuration based on 172 public results since 22 September 2020 with the latest data as of 4 August 2021.
Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. It is important to keep in mind particularly in the Linux/open-source space there can be vastly different OS configurations, with this overview intended to offer just general guidance as to the performance expectations.
Based on OpenBenchmarking.org data, the selected test / test configuration (OpenCV 4.4 - Test: DNN - Deep Neural Network) has an average run-time of 3 minutes. By default this test profile is set to run at least 3 times but may increase if the standard deviation exceeds pre-defined defaults or other calculations deem additional runs necessary for greater statistical accuracy of the result.
Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 8.9%.
Does It Scale Well With Increasing Cores?
No, based on the automated analysis of the collected public benchmark data, this test / test settings does not generally scale well with increasing CPU core counts. Data based on publicly available results for this test / test settings, separated by vendor, result divided by the reference CPU clock speed, grouped by matching physical CPU core count, and normalized against the smallest core count tested from each vendor for each CPU having a sufficient number of test samples and statistically significant data.
Tested CPU Architectures
This benchmark has been successfully tested on the below mentioned architectures. The CPU architectures listed is where successful OpenBenchmarking.org result uploads occurred, namely for helping to determine if a given test is compatible with various alternative CPU architectures.