A Simple Understanding of REST with a Face‑Recognition API Example

Before using REST, it is helpful to understand its basic concepts. Historically, web pages combined front‑end and back‑end code (e.g., PHP, JSP). With the rise of mobile clients, a need emerged for a clean separation, leading to the creation of REST.

REST has become the dominant web‑service design pattern. It is an architectural style rather than a strict standard, defining how applications interact over HTTP. Its resource‑oriented URLs use nouns instead of verbs, which improves data stability, obscures operation flow, and makes APIs easier to read and maintain.

The article then presents a common real‑world example: testing the recognition rate of a face‑recognition algorithm via a REST interface provided by developers. The workflow includes:

Collecting photos that meet various criteria and organizing them into directories.

Reviewing the API documentation to understand required parameters; in this case, the API expects a single base64‑encoded image.

Iterating over the image files, converting each to base64, and sending it to the REST endpoint (code omitted for brevity).

Repeating the request for all images and receiving JSON responses.

After receiving the responses, the JSON is parsed to extract fields such as code , msg , and isattsck . Based on the code values, results are written to different files for further analysis, allowing calculation of true‑positive and false‑negative rates to assess the algorithm’s suitability for production use (e.g., face‑check‑in systems).

The article also includes several illustrative images (flowcharts and screenshots) that depict the overall process.