train_variation_modelT_train_variation_modelTrainVariationModelTrainVariationModeltrain_variation_model (算子)

名称

train_variation_modelT_train_variation_modelTrainVariationModelTrainVariationModeltrain_variation_model — 训练变体模型。

签名

描述

train_variation_modeltrain_variation_modelTrainVariationModelTrainVariationModelTrainVariationModeltrain_variation_model trains the variation model that is passed in ModelIDModelIDModelIDModelIDmodelIDmodel_id with one or more images, which are passed in ImagesImagesImagesImagesimagesimages。

As described for create_variation_modelcreate_variation_modelCreateVariationModelCreateVariationModelCreateVariationModelcreate_variation_model, a variation model that has been created using the mode 'standard'"standard""standard""standard""standard""standard" can be trained iteratively, i.e., as soon as images of good objects become available, they can be trained with train_variation_modeltrain_variation_modelTrainVariationModelTrainVariationModelTrainVariationModeltrain_variation_model. The ideal image of the object is computed as the mean of all previous training images and the images that are passed in ImagesImagesImagesImagesimagesimages. The corresponding variation image is computed as the standard deviation of the training images and the images that are passed in ImagesImagesImagesImagesimagesimages。

If the variation model has been created using the mode 'robust'"robust""robust""robust""robust""robust", the model cannot be trained iteratively, i.e., all training images must be accumulated using concat_objconcat_objConcatObjConcatObjConcatObjconcat_obj and be trained with train_variation_modeltrain_variation_modelTrainVariationModelTrainVariationModelTrainVariationModeltrain_variation_model in a single call. If any images have been trained previously, the training information of the previous call is discarded. The image of the ideal object is computed as the median of all training images passed in ImagesImagesImagesImagesimagesimages. The corresponding variation image is computed as a suitably scaled median absolute deviation of the training images and the median image.

注意

At most 65535 training images can be trained.

执行信息

• 多线程类型：可重入（与非独占算子并行运行）。
• 多线程作用域：全局（可从任何线程调用）。
• 未采用并行化处理。

此算子修改后续输入参数的状态：

• ModelIDModelIDModelIDModelIDmodelIDmodel_id

在执行此算子时，若该参数值需在多个线程间使用，则必须对其访问进行同步。

参数

示例（HDevelop）

create_variation_model (Width, Height, Type, 'standard', ModelID)
for K := 1 to 10 by 1
    read_image (Image, 'pen-' + K$'02')
    find_generic_shape_model (Image, TemplateID, MatchResultID, \
                              NumMatchResult)
    get_generic_shape_model_result (MatchResultID, 'all', 'hom_mat_2d', \
                                    HomMat2D)
    if (NumMatchResult == 1)
        affine_trans_image (Image, ImageTrans, HomMat2D, 'constant', \
                            'false')
        train_variation_model (ImageTrans, ModelID)
    endif
endfor
prepare_variation_model (ModelID, 10, 4)

结果

train_variation_modeltrain_variation_modelTrainVariationModelTrainVariationModelTrainVariationModeltrain_variation_model 在所有参数正确时返回 2 ( H_MSG_TRUE )。

可能的前趋

create_variation_modelcreate_variation_modelCreateVariationModelCreateVariationModelCreateVariationModelcreate_variation_model, find_generic_shape_modelfind_generic_shape_modelFindGenericShapeModelFindGenericShapeModelFindGenericShapeModelfind_generic_shape_model, affine_trans_imageaffine_trans_imageAffineTransImageAffineTransImageAffineTransImageaffine_trans_image, concat_objconcat_objConcatObjConcatObjConcatObjconcat_obj

可能的后继

prepare_variation_modelprepare_variation_modelPrepareVariationModelPrepareVariationModelPrepareVariationModelprepare_variation_model

另见

prepare_variation_modelprepare_variation_modelPrepareVariationModelPrepareVariationModelPrepareVariationModelprepare_variation_model, compare_variation_modelcompare_variation_modelCompareVariationModelCompareVariationModelCompareVariationModelcompare_variation_model, compare_ext_variation_modelcompare_ext_variation_modelCompareExtVariationModelCompareExtVariationModelCompareExtVariationModelcompare_ext_variation_model, clear_variation_modelclear_variation_modelClearVariationModelClearVariationModelClearVariationModelclear_variation_model

模块

匹配