What is the QPS of image processing? Is it possible to increase the QPS?

The QPS (Queries Per Second) of image processing refers to the number of image processing requests a system can handle per second. It depends on factors such as the complexity of the image processing tasks (e.g., resizing, filtering, object detection), the hardware resources (CPU/GPU), the efficiency of the algorithm, and the system architecture.

For example, a simple image resizing service running on a single server might handle 100 QPS, while a more complex object detection system using deep learning models could only achieve 10 QPS due to higher computational demands.

Yes, it is possible to increase the QPS by:

1. Optimizing algorithms – Using more efficient image processing libraries or lightweight models.
2. Scaling infrastructure – Adding more servers or using distributed computing.
3. Leveraging GPU acceleration – Offloading compute-intensive tasks to GPUs for faster processing.
4. Using cloud-based image processing services – For example, Tencent Cloud's Image Processing (MPS) service provides high-performance, scalable solutions for tasks like resizing, watermarking, and AI-based analysis, which can handle high QPS demands efficiently.

By combining these approaches, the QPS of an image processing system can be significantly improved.