Abstract: A face retrieval method is applied to a face retrieval system and performed by a computing device, the face retrieval system including a retrieval device cluster, the retrieval device cluster including at least one node. The method includes acquiring a face image, parsing the face image to obtain a first facial feature, and generating a first retrieval instruction according to the first facial feature, the first retrieval instruction carrying the first facial feature. The method further includes selecting a first node from the retrieval device cluster according to a load balancing rule, the first node including a first retrieval server. Finally, the method includes transmitting the first retrieval instruction to the first retrieval server, to trigger the first retrieval server to execute the first retrieval instruction to retrieve the first facial feature, to obtain a first retrieval result.

Abstract: A face retrieval method is applied to a face retrieval system and performed by a computing device, the face retrieval system including a retrieval device cluster, the retrieval device cluster including at least one node. The method includes acquiring a face image, parsing the face image to obtain a first facial feature, and generating a first retrieval instruction according to the first facial feature, the first retrieval instruction carrying the first facial feature. The method further includes selecting a first node from the retrieval device cluster according to a load balancing rule, the first node including a first retrieval server. Finally, the method includes transmitting the first retrieval instruction to the first retrieval server, to trigger the first retrieval server to execute the first retrieval instruction to retrieve the first facial feature, to obtain a first retrieval result.

Abstract: The present disclosure discloses method and apparatus for image compression. The method includes: acquiring a threshold of a similarity score of an image; acquiring a first quality factor of the image, a first similarity score corresponding to the first quality factor, a second quality factor of the image, and a second similarity score corresponding to the second quality factor; obtaining a functional relationship between quality factor and similarity score of the image by means of curve fitting using the first quality factor, the first similarity score, the second quality factor, and the second similarity score; determining an optimum quality factor of the image according to the functional relationship between the quality factor and the similarity score and the threshold of the similarity score; and compressing the image according to the determined optimum quality factor. With the present disclosure, iterations in image compression can be completed in a very short time.

Abstract: The present disclosure discloses method and apparatus for image compression. The method includes: acquiring a threshold of a similarity score of an image; acquiring a first quality factor of the image, a first similarity score corresponding to the first quality factor, a second quality factor of the image, and a second similarity score corresponding to the second quality factor; obtaining a functional relationship between quality factor and similarity score of the image by means of curve fitting using the first quality factor, the first similarity score, the second quality factor, and the second similarity score; determining an optimum quality factor of the image according to the functional relationship between the quality factor and the similarity score and the threshold of the similarity score; and compressing the image according to the determined optimum quality factor. With the present disclosure, iterations in image compression can be completed in a very short time.