o @Tj@s<dZddlZddlZddlmZeeZGdddZ dS)zJInsightFace buffalo_l wrapper for face detection and embedding extraction.N) FaceAnalysisc@s\eZdZdZddededefdd Zd ej d e ej fd d Z d ej d ej dBfddZ dS) FaceAnalyzerzKWraps insightface FaceAnalysis (buffalo_l) for detection + 512-d embedding. buffalo_l333333? model_namectx_id det_threshcCsVt|dgd|_|jj|ddt|jdr"t|jjdr"||jj_td||dS)NCPUExecutionProvider)name providers)r )rdet_size det_modelr z2FaceAnalyzer initialized (model=%s, det_thresh=%s))r_apppreparehasattrrr loggerinfo)selfrrr r7/home/ubuntu/htdocs/ootd-api/app/utils/face_analyzer.py__init__s  zFaceAnalyzer.__init__imagereturncCs>|j|}|s gSg}|D]}|j}||tjq|S)zDetect faces and return list of 512-d embedding vectors. Args: image: BGR numpy array (OpenCV format). Returns: List of normalized embedding vectors (one per detected face). )rgetnormed_embeddingappendastypenpfloat32)rrfaces embeddingsfaceembrrrget_embeddingss zFaceAnalyzer.get_embeddingsNcCs2|j|}|s dSt|ddd}|jtjS)zReturn embedding of the largest detected face (by bbox area). Args: image: BGR numpy array (OpenCV format). Returns: 512-d embedding vector, or None if no face detected. NcSs(|jd|jd|jd|jdS)Nr)bbox)frrr4s(z9FaceAnalyzer.get_largest_face_embedding..)key)rrmaxrrrr )rrr!largestrrrget_largest_face_embedding(s z'FaceAnalyzer.get_largest_face_embedding)rrr) __name__ __module__ __qualname____doc__strintfloatrrndarraylistr%r/rrrrr s r) r3loggingnumpyrinsightface.appr getLoggerr0rrrrrrs