The Skin Analysis API returns detailed information about skin features, including imperfections like acne, wrinkles, pores, and dark circles. The response includes a face token, location coordinates, and a confidence score for the detected features.

Key fields in the response include "face_num" (number of faces detected), "face_list" (details of each face), "location" (coordinates of the detected face), and "prob" (probability of detection), which indicates the confidence level of the analysis.

The response data is structured in a JSON format. It includes a top-level object with "error_code," "error_detail," and "result." The "result" contains "face_num" and "face_list," which details each detected face's attributes.

The Get Analysis endpoint accepts an image upload and an optional parameter for feature detection. Users can specify features like "color," "smooth," "acnespotmole," "wrinkle," "eyesattr," "blackheadpore," and "skinquality." Multiple features can be combined in a single request.

Users can customize their requests by selecting specific skin features to analyze through the optional parameter. For example, to analyze both blackheads and skin quality, users would input "blackheadpore,skinquality" in the parameter field.

The API provides information on various skin conditions, including color, smoothness, acne spots, wrinkles, pores, blackheads, dark circles, and eye bags. It also identifies specific details like blood vessel dark circles and acne marks.

Data accuracy is maintained through advanced image recognition technology that compares analyzed images against a comprehensive database of skin profiles and conditions. Continuous updates and quality checks ensure reliable results.

Typical use cases include personalized skincare recommendations, skin health tracking, dermatology diagnosis, skincare product development, and beauty consultations. These applications help users make informed decisions about their skincare needs.

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