Optimize your training process by adjusting parameters, using efficient models, and leveraging hardware acceleration.
Optimize your training process by adjusting parameters, using efficient models, and leveraging hardware acceleration.
How to Enhance OpenCV Learning Speed? Using multiple threads on the CPU like Xeon e5 2699v4 (22 cores, 44 threads, 2.3 GHz) can help. Single-threaded CPUs such as i9-10900k (10 cores, 20 threads, 5.3 GHz) may not always improve performance. GPU acceleration can also significantly boost speed.
Your project supports CUDA, making GPU the optimal choice. How much RAM are your models requiring? What is your financial plan?
Both of these options seem quite outdated, so it's best to avoid them. Do you have a budget in mind? What size models are you working with? I'm aiming for something around the 3080.
Available GPUs depend on your setup. If you own the hardware, try testing them yourself!
The model should handle around 1,000 to 15,000 images at high definition. It needs 15,000 pictures of people wearing masks and 15,000 without masks for training the face recognition system in the attendance setup. Employees who don’t wear a mask could face penalties of about 1,000 rubles. The budget stays under $900, but approval from your company is required next year. You’ll use your own funds first, then redeem them later.