C++缓存设计建议

也许您可以使用Boost.MultiIndex容器做点什么？ 它将允许您创建一个存储图像数据的类型，以及如何操作它的详细信息，然后根据您想要的任何键组合查找值。 如果您以前没有使用过它，它可能看起来有点令人生畏，但我在下面附上了一个示例。

显然，我的示例只处理缓存机制的存储/检索部分，如果您将其粘在一起，如果查找失败，可以生成图像，它应该做您想要的一切。 扩展它也很容易...需要查找额外的参数？您只需要将另一个索引添加到 ImageCache typedef。

#include <boost/multi_index_container.hpp>
#include <boost/multi_index/composite_key.hpp>
#include <boost/multi_index/member.hpp>
#include <boost/multi_index/ordered_index.hpp>
#include <boost/multi_index/hashed_index.hpp>
#include <boost/multi_index/tag.hpp>
#include <boost/shared_array.hpp>
#include <algorithm>
#include <iostream>
#include <utility>
// A cache item, stores the image data, and any values we need to 
// index on.
struct ImageCacheItem
{
    enum RgbMode { RGB_MODE_COLOUR, RGB_MODE_GREYSCALE };
    // Im not sure how much copying goes on in the container,
    // so using a smart pointer to prevent copying large amounts
    // of data.
    boost::shared_array<char> imageBuffer;
    double  rotation;
    double  scale;
    RgbMode rgbMode;
    ImageCacheItem(double r, double s)
    : rotation(r), scale(s)
    {
    }
};
// These are "tag" structures, they are used as part of the 
// multi_index_container as a way to distinguish between indicies.
struct ByRotation {};
struct ByScale {};
struct ByRgb {};
struct ByRotationScale {};
// Typedef of the container itself.
typedef boost::multi_index_container<
    ImageCacheItem, // The data type for the container.  
                    // Note there is no "key" type, as the key values 
                    // are extracted from the data items theselves.
    boost::multi_index::indexed_by<
        // Define an index for the rotation value
        boost::multi_index::ordered_non_unique<
            boost::multi_index::tag<ByRotation>,
            BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, rotation)
        >,
        // Define an index for the scale value
        boost::multi_index::ordered_non_unique<
            boost::multi_index::tag<ByScale>,
            BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, scale)
        >,
        // Define an index for the rgb value
        boost::multi_index::hashed_non_unique<
            boost::multi_index::tag<ByRgb>,
            BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, ImageCacheItem::RgbMode, rgbMode)
        >,
        // Define an index by rotation + scale
        boost::multi_index::hashed_unique<
            boost::multi_index::tag<ByRotationScale>,
            boost::multi_index::composite_key<
                ImageCacheItem,
                BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, rotation),
                BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, scale)
            >
        >
    >
> ImageCache;
// Utility typedefs, you'll want these to shorten the iterator
// data types when you're looking things up (see main).
typedef ImageCache::index<ByRotation>::type      ImageCacheByRotation;
typedef ImageCache::index<ByScale>::type         ImageCacheByScale;
typedef ImageCache::index<ByRgb>::type           ImageCacheByRgb;
typedef ImageCache::index<ByRotationScale>::type ImageCacheByRotationScale;
int main()
{
    // Create the cache and add time "images" to it.
    ImageCache cache;
    cache.insert(ImageCacheItem(10, 10));
    cache.insert(ImageCacheItem(10, 20));
    cache.insert(ImageCacheItem(20, 20));
    // look up the images with scale of 20.
    typedef ImageCacheByScale::iterator ScaleIter;
    std::pair<ScaleIter, ScaleIter> scaleResult = cache.get<ByScale>().equal_range(20);
    std::cout << "Found " << std::distance(scaleResult.first, scaleResult.second) << " Results" << std::endl;
    // look up the image with rotation = 10 && scale = 20.
    ImageCacheByRotationScale::iterator rsResult = cache.get<ByRotationScale>().find(boost::make_tuple(10, 20));
    std::cout << "Found " << (rsResult != cache.get<ByRotationScale>().end() ? 1 : 0) << " Results" << std::endl;
    return 0;
}

编辑：这是一个很大的...

我已经尝试扩展上述示例以在缓存中找到最接近您搜索的图像，但有偏差，因此，如果您想要旋转 45 和 10 的比例，如果没有找到完全匹配，它将有利于具有相同属性之一的结果， 另一个为 0(即 10 的比例，但旋转为 0，所以您需要做的就是旋转(。

注释代码以解释它的作用，但基本上，它使用模板递归按顺序搜索索引，一旦索引找到一些匹配项，它就会尝试按相关性顺序对它们进行排序，并返回最佳匹配项。 若要添加其他属性，需要执行以下操作：

1. 将属性添加到ImageCacheItem
2. 将属性的比较添加到ImageCacheSimilarity
3. (可选(将与其匹配的另一个索引添加到 ImageCache typedef

这可能不是最佳解决方案，但我认为它涵盖了您在评论中提到的用例。

#include <boost/multi_index_container.hpp>
#include <boost/multi_index/composite_key.hpp>
#include <boost/multi_index/member.hpp>
#include <boost/multi_index/ordered_index.hpp>
#include <boost/multi_index/hashed_index.hpp>
#include <boost/multi_index/tag.hpp>
#include <boost/mpl/list.hpp>
#include <boost/optional.hpp>
#include <boost/ref.hpp>
#include <boost/shared_array.hpp>
#include <algorithm>
#include <cmath>
#include <iostream>
#include <utility>
#include <vector>
#include <typeinfo>
// A cache item, stores the image data, and any values we need to 
// index on.
struct ImageCacheItem
{
    enum RgbMode { RGB_MODE_COLOUR, RGB_MODE_GREYSCALE };
    // Im not sure how much copying goes on in the container,
    // so using a smart pointer to prevent copying large amounts
    // of data.
    boost::shared_array<char> imageBuffer;
    double  rotation;
    double  scale;
    RgbMode rgbMode;
    ImageCacheItem(double r, double s)
    : rotation(r), scale(s)
    {
    }
};
// Calculates the similarity between two ImageCacheItem objects.
int ImageCacheSimilarity(const ImageCacheItem& item, const ImageCacheItem& target)
{
    const double EPSILON = 0.0000001;
    int score = 0;
    // 2 points for an exact match
    // 1 point if the value is 0 (e.g. not rotated, so can be used as a starting point)
    // -1 point otherwise
    score += (std::fabs(item.rotation - target.rotation) < EPSILON) 
        ? 2 
        : ((std::fabs(item.rotation) < EPSILON) ? 1 : -1);
    score += (std::fabs(item.scale - target.scale) < EPSILON) 
        ? 2 
        : ((std::fabs(item.scale) < EPSILON) ? 1 : -1);
    score += (item.rgbMode == target.rgbMode) ? 2 : 0;
    return score;
}
// Orders ImageCacheItem objects based on their similarity to a target value.
struct ImageCacheCmp
{
    const ImageCacheItem& target;
    ImageCacheCmp(const ImageCacheItem& t)
    : target(t)
    {
    }
    bool operator()(const ImageCacheItem& a, const ImageCacheItem& b)
    {
        return (ImageCacheSimilarity(a, target) > ImageCacheSimilarity(b, target));
    }
};
// These are "tag" structures, they are used as part of the 
// multi_index_container as a way to distinguish between indicies.
struct ByRotation {};
struct ByScale {};
struct ByRgb {};
struct ByRotationScale {};
// Typedef of the container itself.
typedef boost::multi_index_container<
    ImageCacheItem, // The data type for the container.  
                    // Note there is no "key" type, as the key values 
                    // are extracted from the data items theselves.
    boost::multi_index::indexed_by<
        // The order of indicies here will affect performance, put the 
        // ones that match against the most fields first.  Its not required
        // to make it work, but it will reduce the number of matches to 
        // compare against later on.
        // Define an index by rotation + scale
        boost::multi_index::hashed_unique<
            boost::multi_index::tag<ByRotationScale>,
            boost::multi_index::composite_key<
                ImageCacheItem,
                BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, rotation),
                BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, scale)
            >
        >,
        // Define an index for the rotation value
        boost::multi_index::ordered_non_unique<
            boost::multi_index::tag<ByRotation>,
            BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, rotation)
        >,
        // Define an index for the scale value
        boost::multi_index::ordered_non_unique<
            boost::multi_index::tag<ByScale>,
            BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, double, scale)
        >,
        // Define an index for the rgb value
        boost::multi_index::hashed_non_unique<
            boost::multi_index::tag<ByRgb>,
            BOOST_MULTI_INDEX_MEMBER(ImageCacheItem, ImageCacheItem::RgbMode, rgbMode)
        >
    >
> ImageCache;
// Type of the vector used when collecting index results.  It stores
// references to the values in the cache to minimise copying.
typedef std::vector<boost::reference_wrapper<const ImageCacheItem> > ImageCacheResults;
// Utility class for overload resolution
template <int I>
struct Int2Type
{
    enum { value = I };
};
void FindMatches(
    const ImageCacheItem& item, 
    const ImageCache& cache, 
    ImageCacheResults& results,
    const Int2Type<boost::mpl::size<ImageCache::index_type_list>::type::value>&)
{
    // End of template recursion
}
template <int I>
void FindMatches(
    const ImageCacheItem& item, 
    const ImageCache& cache, 
    ImageCacheResults& results,
    const Int2Type<I>&)
{
    // Get the index being searched
    typedef typename ImageCache::nth_index<I>::type Index;
    // This type knows how to extract the relevant bits of ImageCacheItem
    // for this particular index.
    typename Index::key_from_value keyExtractor;
    // Look for matches in the index.
    std::pair<typename Index::const_iterator, typename Index::const_iterator> iter = 
        cache.get<I>().equal_range(keyExtractor(item));
    // If we found any results, add them to 'results', otherwise
    // continue to the next index.
    if (iter.first != iter.second)
    {
        results.reserve(std::distance(iter.first, iter.second));
        for ( ; iter.first != iter.second; ++iter.first)
        {
            results.push_back(boost::cref(*iter.first));
        }
    }
    else
    {
        FindMatches(item, cache, results, Int2Type<I + 1>());
    }
}
boost::optional<ImageCacheItem> FindClosestImage(const ImageCacheItem& item, const ImageCache& cache)
{
    // Find exact/partial matches according to the indicies.
    ImageCacheResults results;
    FindMatches(item, cache, results, Int2Type<0>());
    // If no matches were found, return an empty value
    if (results.empty())
    {
        return boost::optional<ImageCacheItem>();
    }
    // We got this far, so we must have some candiates, the problem is
    // we dont know which is the best match, so here we sort the results
    // based on proximity to the "item".  However, we are only interested
    // in the best match, so do a partial_sort.
    std::partial_sort(results.begin(), results.begin() + 1, results.end(), ImageCacheCmp(item));
    return results.front().get();
}
int main()
{
    // Create the cache and add some "images" to it.
    ImageCache cache;
    cache.insert(ImageCacheItem(10, 20));
    cache.insert(ImageCacheItem(10, 10));
    cache.insert(ImageCacheItem(10, 2));
    cache.insert(ImageCacheItem(20, 20));
    cache.insert(ImageCacheItem(30, 20));
    cache.insert(ImageCacheItem(30, 0));
    // Look for an image similar to rotation = 30 && scale = 2.
    boost::optional<ImageCacheItem> result = FindClosestImage(ImageCacheItem(30, 2), cache);
    // Have to check if result is value before usage, it would be empty 
    // if not match is found.
    if (result)
    {
        std::cout << "Found (" << result->rotation 
                  << ", " << result->scale << ")" 
                  << std::endl;
    }
    else
    {
        std::cout << "No Results" << std::endl;
    }
    return 0;
}

您是否考虑过使用瘦访问器对彩色图像进行灰色和旋转？Adobe的通用图像库(现在是boost的一部分(以这种方式使用了一些聪明的迭代器。

您是否考虑过使用 STL 容器？使用地图或集来存储对图像的引用。具有快速查找以查看您是否已经创建了映像。