此面部分析高级API允许您通过面部图像高精度评估皮肤状况。当您上传照片时,系统应用计算机视觉和人工智能算法来识别瑕疵、皱纹、污点、痤疮、毛孔粗大、水分水平以及其他与护肤相关的指标。
该API生成结构化结果,以清晰且易于集成的格式呈现,包括热图、严重程度指数和受影响面部区域的百分比。这使得对皮肤状况有了详细的理解,并进行定期跟进以评估治疗的进展或效果。
它提供客观的自动化分析,消除了主观差异,并提供可量化的皮肤健康数据。
此外,该API还包括面部分割选项,以识别特定区域(额头、脸颊、鼻子、下巴),提供局部诊断。它还支持参数定制,以适应不同的肤质和光照环境。
简而言之,此API将简单照片转变为详细的皮肤病学分析,帮助提供有根据的建议,改善用户关系,并通过准确的皮肤数据创造附加价值。
皮肤分析 - 端点功能
| 对象 | 描述 |
|---|---|
请求体 |
[必需] Json |
{"log_id":"1776444169,7f33f409-61d2-4af7-a38b-a5a81a30a1f7","request_id":"1776444169,0f55ec05-37f1-43c6-a510-ef24dd51df0c","timestamp":"2026-04-17T16:42:49.350404","analysis_type":"comprehensive","focus_areas":["acne","wrinkles","pores"],"image_url":"https://a.files.bbci.co.uk/worldservice/live/assets/images/2016/04/21/160421151857_acne_624x351_thinkstock_nocredit.jpg","image_info":{"original_size":{"width":512,"height":288},"processed_size":{"width":512,"height":288},"bbox_format":"x1,y1,x2,y2","coordinate_system":"pixels"},"quality":{"blur_score":0.824,"exposure_score":0.16,"contrast_score":0.294,"overall_quality":"poor","quality_score":0.333,"warnings":["High blur detected - texture-dependent analysis may be unreliable","Consider retaking photo with better focus","Underexposed image - may affect lesion detection"],"scales":{"blur_score":"0=sharp, 1=blurry","exposure_score":"0=dark, 1=overexposed","contrast_score":"0=low, 1=high","quality_score":"0=poor, 1=excellent"}},"face_regions":{"left_cheek":[115,86,201,173],"right_cheek":[288,86,375,173],"chin":[180,173,310,260],"forehead":[180,0,310,86]},"lesions":{"count":0,"severity":"none","severity_percentage":0.0,"confidence":0.95,"detection_status":"not_present"},"pores":{"left_cheek":{"count":1,"density":1.34,"density_units":"pores/10k_pixels","severity":"low","confidence":0.600133654103181,"filtering_applied":"morphological + circularity"},"right_cheek":{"count":7,"density":9.25,"density_units":"pores/10k_pixels","severity":"low","confidence":0.6009248249438499,"filtering_applied":"morphological + circularity"},"chin":{"count":2,"density":1.77,"density_units":"pores/10k_pixels","severity":"low","confidence":0.6001768346595933,"filtering_applied":"morphological + circularity"},"forehead":{"count":1,"density":0.89,"density_units":"pores/10k_pixels","severity":"low","confidence":0.6000894454382826,"filtering_applied":"morphological + circularity"}},"wrinkles":{"left_cheek":{"wrinkle_score":0.546,"severity":"moderate","confidence":0.8638320685224598},"right_cheek":{"wrinkle_score":0.37,"severity":"moderate","confidence":0.8111346385265074},"chin":{"wrinkle_score":0.444,"severity":"moderate","confidence":0.8332612127886169},"forehead":{"wrinkle_score":0.585,"severity":"moderate","confidence":0.8756066997274834}},"pigmentation":{"left_cheek":{"spot_count":1,"density":1.34,"density_units":"spots/10k_pixels","severity":"none","confidence":0.600133654103181,"filtering_applied":"morphological + circularity","detection_type":"defined_spots_only"},"right_cheek":{"spot_count":1,"density":1.32,"density_units":"spots/10k_pixels","severity":"none","confidence":0.6001321178491213,"filtering_applied":"morphological + circularity","detection_type":"defined_spots_only"},"chin":{"spot_count":0,"density":0.0,"density_units":"spots/10k_pixels","severity":"none","confidence":0.6,"filtering_applied":"morphological + circularity","detection_type":"defined_spots_only"},"forehead":{"spot_count":1,"density":0.89,"density_units":"spots/10k_pixels","severity":"none","confidence":0.6000894454382826,"filtering_applied":"morphological + circularity","detection_type":"defined_spots_only"}},"skin_type":{"label":"mixed","confidence":0.8,"texture_score":17442.5879},"severity":{"overall":"mild","confidence":0.703,"component_scores":{"inflammatory_acne":0,"pores":0.2,"wrinkles":0.7,"pigmentation":0.0},"total_weighted_score":0.9,"weighting_system":"mature_skin_optimized","explanation":"Wrinkles and pigmentation weighted higher for mature skin analysis","criteria":{"inflammatory_acne":">5 lesions or >2% area","pores":">300 pores/10k_pixels in any region","wrinkles":">0.6 wrinkle_score in any region","pigmentation":">500 spots/10k_pixels in any region","thresholds":{"mild":"0-2 lesions, <100 pores/10k_pixels, <0.3 wrinkle_score","moderate":"3-5 lesions, 100-300 pores/10k_pixels, 0.3-0.6 wrinkle_score","severe":">5 lesions, >300 pores/10k_pixels, >0.6 wrinkle_score"}}}}
curl --location --request POST 'https://zylalabs.com/api/9341/face+analyzer+advanced/16879/skin+analysis' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"analysis_type": "comprehensive",
"image_url": "https://a.files.bbci.co.uk/worldservice/live/assets/images/2016/04/21/160421151857_acne_624x351_thinkstock_nocredit.jpg",
"focus_areas": ["acne", "wrinkles", "pores"]
}'
| 标头 | 描述 |
|---|---|
授权
|
[必需] 应为 Bearer access_key. 订阅后,请查看上方的"您的 API 访问密钥"。 |
无长期承诺。随时升级、降级或取消。 免费试用包括最多 50 个请求。
皮肤分析端点返回有关皮肤状况的详细指标,包括瑕疵、皱纹、斑点、痤疮、毛孔粗大、水分水平和严重程度指数。它还提供受影响区域的热图和百分比,能够全面了解皮肤健康
响应数据中的关键字段包括“瑕疵”“皱纹”“ blemishes”“水合水平”“严重程度指数”和“热图”每个字段提供了对特定皮肤状况的可量化见解,使得能够进行有针对性的分析
响应数据采用JSON格式结构化,按每个皮肤状况指标分为不同部分。每个部分包含相关值和视觉表现,如热图,便于解释和集成到应用程序中
用户可以通过指定参数,如“肤质”、“光照条件”和“感兴趣区域”(例如额头、面颊)来定制他们的请求。这允许基于个人的皮肤特征和环境进行量身定制的分析
数据准确性通过先进的计算机视觉和人工智能算法得以保持,这些算法分析面部图像。对多样化数据集的持续更新和训练确保系统适应各种肤色和状况,从而提高可靠性
典型的使用案例包括个性化护肤建议 跟踪治疗进展 以及增强护肤应用中的用户参与 详细的分析帮助皮肤科医生和用户做出明智的护肤决策
用户可以通过将返回的数据整合到护肤应用程序中来获得个性化的推荐 可视化热力图以进行针对性治疗 并随着时间的推移监测变化以评估护肤产品或护肤程序的效果
标准数据模式包括针对不同皮肤状况的不同严重程度指数,较高的数值表示更严重的问题 用户可以期待相似皮肤类型之间的一致度量,帮助进行比较分析和治疗计划
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