Hi @Yujie Luo ,
The observation that your effective frame rate remains around 450 FPS despite adding functions is intriguing. Here are several factors that could explain this phenomenon:
Processing Overhead vs. Frame Capture Time: The frame capture time may be significantly less than the time taken by function1 and function2. If getdata(vid) is the bottleneck (i.e., it takes longer than the processing functions), then even if you add processing time, it won't affect the overall frame rate. Since you mentioned that both functions together take about 0.5 ms, if getdata(vid) is executing faster than this or if it is optimized in a way that compensates for additional processing, you may not see a drop in FPS.
Multithreading or Buffering: Some video processing libraries utilize multithreading or buffering techniques to handle frames efficiently. If your video input system has buffering capabilities, it may be capturing frames ahead of time while processing previous ones, thereby maintaining a high frame rate.
Measurement Timing: Ensure that you measure the total execution time accurately. If you are measuring just the time taken for function1 and function2, ensure that you're not inadvertently including other operations that might skew results.
To gain better insights into your performance metrics:
Use tic and toc for each function call: Wrap each function call with tic and toc to get precise measurements of their execution times.
tic; function1(frame); elapsedFunction1 = toc;
tic; function2(frame); elapsedFunction2 = toc;
Measure total loop execution time: You can also measure the total execution time for each iteration of your loop to see how it varies with different functions:
t_total_Frame = tic; % Your existing code... elapsedFrame = toc(t_total_Frame);
Regarding your concern about timestamps from getdata, it's important to note that:
- The timestamps returned by getdata should reflect the moment each frame was captured from the video stream.
- If you observe that timestamps remain constant even after introducing pauses or additional processing, consider Frame Buffering, timestamps might not update if frames are being buffered; check if your video object has such behavior. Also, if your timing mechanism lacks precision (e.g., milliseconds), subtle delays might not be captured.
Utilize MATLAB's built-in profiler (profile on; ...; profile viewer;) to analyze where time is being spent within your loop. This will help identify any unexpected performance. If feasible, explore asynchronous methods to process frames without blocking the main loop. This could allow capturing new frames while processing previous ones. Test with varying complexities in function1 and function2 to see how they impact performance, helping establish a clearer relationship between computational load and frame rate.
By following these suggestions and understanding potential underlying mechanisms in your video processing setup, you can better analyze and optimize your effective frame rates while ensuring accurate timestamp management.
Hope this helps.
Please let me know if you have any further questions.