mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-17 06:00:59 +08:00
02eab973ce
* 第一次提交 * 补充一处漏翻译 * deleted: docs/en/quantize.md * Update one translation * Update en version * Update one translation in code * Standardize one writing * Standardize one writing * Update some en version * Fix a grammer problem * Update en version for api/vision result * Merge branch 'develop' of https://github.com/charl-u/FastDeploy into develop * Checkout the link in README in vision_results/ to the en documents * Modify a title * Add link to serving/docs/ * Finish translation of demo.md
1.7 KiB
1.7 KiB
English | 中文
Image Classification Result
The ClassifyResult code is defined in fastdeploy/vision/common/result.h, and is used to indicate the classification result and confidence level of the image.
C++ Definition
fastdeploy::vision::ClassifyResult
struct ClassifyResult {
std::vector<int32_t> label_ids;
std::vector<float> scores;
void Clear();
std::string Str();
};
- label_ids: Member variable which indicates the classification results of a single image. Its number is determined by the topk passed in when using the classification model, e.g. it can return the top 5 classification results.
- scores: Member variable which indicates the confidence level of a single image on the corresponding classification result. Its number is determined by the topk passed in when using the classification model, e.g. it can return the top 5 classification confidence level.
- Clear(): Member function used to clear the results stored in the structure.
- Str(): Member function used to output the information in the structure as string (for Debug).
Python Definition
fastdeploy.vision.ClassifyResult
- label_ids(list of int): Member variable which indicates the classification results of a single image. Its number is determined by the topk passed in when using the classification model, e.g. it can return the top 5 classification results.
- scores(list of float): Member variable which indicates the confidence level of a single image on the corresponding classification result. Its number is determined by the topk passed in when using the classification model, e.g. it can return the top 5 classification confidence level.