N 个object queries通过Decoder转换成一个output embedding,然后output embedding通过FFN独立解码出 N 个预测结果,包含box和class。对输入embedding同时使用Self-Attention和Encoder-Decoder Attention,模型可以利用目标的相互关系来进行全局推理。 和Transformer Decoder不同的是,DETR的每个Decoder并行输出 N 个对象,Transformer...
Object queries are often used to return conceptual model data as entity objects, but they may also return aDbDataRecordobject for nested results and anonymous projections, or they can return primitive CLR types for sets of single values.
An ObjectQuery<T> is frequently of an entity type, but it can also be of DbDataRecord type, for projections to an anonymous type, or of a primitive type, such as an integer or string. For more information, see Object Queries.Constructors Разширяваненатаблица ...
AnObjectQuery<T>is frequently of an entity type, but it can also be ofDbDataRecordtype, for projections to an anonymous type, or of a primitive type, such as an integer or string. For more information, seeObject Queries. Constructors ...
AnObjectQuery<T>is frequently of an entity type, but it can also be ofDbDataRecordtype, for projections to an anonymous type, or of a primitive type, such as an integer or string. For more information, seeObject Queries. Constructors ...
Creating Anchored Object Queries Executing Anchored Object Queries M init(type: HKSampleType, predicate: NSPredicate?, anchor: HKQueryAnchor?, limit: Int, resultsHandler: (HKAnchoredObjectQuery, [HKSample]?, [HKDeletedObject]?, HKQueryAnchor?, (any Error)?) -> Void) ...
public static void demoWhereClause(ApplicationModule appMod) { // Define basic query string. String sqlStr = "SELECT Emp.ename, Emp.mgr FROM EMP Emp "; ViewObject vo = appMod.createViewObjectFromQueryStmt("whereDemo", sqlStr); // Define and set WHERE clause. (See also ViewObject.setOr...
publicclassEmployeeRepository : IRepository<Employee> {publicIEnumerable<Employee> FindSalariedEmployee(SalariedFlag salariedFlag) {} } 可以看出只要我们有通过对象属性来查询对象,就要在相应的数据层增加对应的Findxxx方法,不过这只是单一的查询,如果存在组合条件的查询,Employee仓储中会充斥大量的检索方法。
DETR 通过一个全局的集合 Loss,强制模型针对一个物体只会对应有一个框,而不会生成过多的冗余框。此外,在 DETR 架构中,Transformer 的解码器的输入额外有一项 Learned Object Queries,类似于可学习的 Anchor。DETR 简单且有效(但在目标检测上和 SOTA 还是差了挺多)!
Decoder:遵循标准Transformer解码器,Q是objects queries,K是3D位置感知特征,在全局角度寻找关注区域。loss设置同DETR3D。 碎碎念 PETR通过全局注意力对3D相关性进行表示学习,DETR3D则感知采样的局部区域内的3D场景。 PETR巧妙地使用Query Generator,从3D空间编码query,无需在图像特征上采样。 4.PETRv2: A Unified Frame...