Comments (1)
map@100是用在测试集的,与训练集无关,只要某个Query(查询图片)有至少1张GT都能算。
例如某Query其GT为M和P,Query在Index(底库,假设有N张图片)中搜索,会获得所有N张Index图片与Query图片的相似度,按相似度从大到小排序即Q: ABCDM...(省略95个,这中间没有P)qaP(这个P排103位)
则map@all = 0.5 * (1/5 + 2/103)
map@100 = 0.5 * (1/5)
在图片检索领域,一些人把map@100错误地算成map@100 = (1/5),认为P不在前100可以不记做分母,参考谷歌的论文和delg代码,谷歌是按正确方法计算的。评价方式更多讨论,可以见https://stackoverflow.com/questions/54966320/mapk-computation
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