Okay, so today I’m gonna talk about this little project I was messing around with. I called it “1fps” because… well, you’ll see why.
It all started when I was trying to do some basic video processing. Nothing fancy, just wanted to see if I could take a video file, grab a frame, do some simple stuff to it, and then save it back out. Seemed easy enough, right?
First thing I did was grab OpenCV. Everyone uses OpenCV for this kind of thing, so I figured, why not? Installed it, got the basic import working in my Python script. So far so good.
Then came the video loading part. Used to open the video. That worked fine. Got the frame rate, width, height – all the usual stuff. I thought, “Sweet, this is gonna be a breeze.”
Next, I wanted to actually read a frame. Used . This is where things started to go sideways. It worked, technically. I got an image. But it was SLOW. Like, glacial slow.
I’m talking, it took almost a full second just to read one frame. I was like, “There’s gotta be something wrong here.”
So, I started debugging. I tried different video files, different codecs, different resolutions. Nothing seemed to make a difference. The frame rate I was getting in reality was nowhere near what *(*_PROP_FPS) was telling me.
I then dove into the OpenCV documentation, looked at all the different video capture properties, and tried tweaking those. Tried different backends too. Nada.
I started suspecting it might be something with my system, or maybe a weird interaction between OpenCV and my graphics card. Updated drivers, checked for conflicts. Still no luck.
Then, I started suspecting the video file itself might be the problem. Used ffmpeg to re-encode the video into a simpler format. That actually helped a little, but it was still nowhere near real-time.
Finally, after hours of struggling, I realized I was being dumb. The problem wasn’t the reading of the frame. The problem was what I was doing after reading the frame.
See, I was doing some image processing stuff – blurring, edge detection, that kind of jazz. And I was doing it in a really inefficient way, just looping through the pixels one by one.
So I rewrote that part of the code to use NumPy’s vectorized operations. Suddenly, everything was much faster. I could actually process frames in real-time, no problem.
I was so focused on the video loading part that I completely overlooked the obvious bottleneck in my own code. Facepalm moment for sure.
So yeah, that’s the story of my “1fps” project. It taught me a valuable lesson about profiling your code and not jumping to conclusions too quickly. And also, that NumPy is your friend when it comes to image processing.
The final code looks something like this (simplified, of course):
- OpenCV to load video.
- NumPy for image manipulation.
- Optimized code!
Learned a lot. Next time, profile first, optimize later!
