模型纹理检查
这个例子利用纹理检测模型检测纹理缺陷。
这个示例程序演示了如何进行微调
*纹理检测模型[文]。
*首先，创建和[章]训练纹理检测模[来]型
*使用一组无错[自]误的纹理图像。[网]
*接下来，对其[淘]中一个有缺陷的[巴]参数进行微调
*测试图像。
*在最后一步，[文]收集有缺陷的和[章]没有缺陷的
*图像被测试。[来]
*初始化
dev_update_off ()
dev_close_window ()
read_image (Image, 'carpet/carpet_01')
get_image_size (Image, Width, Height)
NumImages := 7
*定义训练图像[自]集。
Trainin[网]gImageI[淘]ndices := [1,2]
*训练图像指数
Texture[巴]ModelFi[文]lename := 'texture[章]_model_[来]carpet'
*纹理模型文件
* 初始可视化.
dev_open_window_fit_size (0, 0, Width, Height, -1, -1, WindowHandle1)
get_window_extents (WindowHandle1, Row, Column, WindowWidth, WindowHeight)
set_display_font (WindowHandle1, 16, 'mono', 'true', 'false')
dev_set_draw ('margin')
dev_set_line_width (2)
*
Message := '这个示例程序演示了如何微调'
Message[1] := '用于缺陷检测的纹理检测模型:'
Message[2] := ' '
Message[3] := '(1)创建并训练纹理检查模型
Message[4] := '使用无错误纹理的图像'
Message[5] := ' '
Message[6] := ''(2)对其中一个测试的参数进行了微调'
Message[7] := '图像。'
Message[8] := ' '
Message[9] := '(3)检测缺陷图像和非缺陷图像'
Message[10] := ' '
Message[11] := '要完全理解此程序，请阅读'
Message[12] := '源代码中的注释。'
dev_disp_text (Message, 'window', 12, 12, 'black', [], [])
dev_disp_text ('Press Run (F5) to continue', 'window', 'bottom', 'right', 'black', [], [])
stop ()
*首先我们尝试[自]读取纹理检测模[网]型
*(仅当示例之[淘]前运行过时有效[巴])
file_exists (TextureModelFilename + '.htim', FileExists)
if (FileEx[文]ists)
read_texture_inspection_model (TextureModelFilename, TextureInspectionModel)
get_texture_inspection_model_param (TextureInspectionModel, 'levels', Levels)
Message[章] := '读取之前训练的[来]纹理检测模型.[自]'
Message[网][1] := ' '
else
* 训练一个新的纹[淘]理检查模型.
* [巴]
* 创建内部数据结[文]构.
create_texture_inspection_model ('basic', TextureInspectionModel)
* [章]
* 阅读并添加样本[来]图像进行训练.[自]
for Index := 0 to |Traini[网]ngImage[淘]Indices[巴]| - 1 by 1
read_image (Image, 'carpet/carpet_' + TrainingImageIndices[Index]$'02')
dev_display (Image)
Message[文] := '添加图片 ' + (Index + 1) + ' of ' + |Traini[章]ngImage[来]Indices[自]| + '到训练集.'
dev_disp_text (Message, 'window', 12, 12, 'black', [], [])
* 使用整个图像作[网]为纹理样本
*在不同的应用[淘]程序中，你可能[巴]想先缩小图像域[文]。.
add_texture_inspection_model_image (Image, TextureInspectionModel, Indices)
dev_disp_text ('Press Run (F5) to continue', 'window', 'bottom', 'right', 'black', [], [])
stop ()
endfor
* [章]
* 训练可能需要一[来]段时间，特别是[自]当使用大图像时[网].
dev_display (Image)
Message[淘][0] := '训练纹理检测模[巴]型.'
Message[文][1] := ' '
Message[章][2] := '这可能需要一分[来]钟 (看'
Message[自][3] := '进度的状态栏)[网].'
dev_disp_text (Message, 'window', 12, 12, 'black', [], [])
* [淘]
* 定义训练参数.[巴]
* 将归一化设置为[文]“[章]weber&r[来]dquo;，以[自]允许处理不同亮[网]度的图像.
set_texture_inspection_model_param (TextureInspectionModel, 'patch_normalization', 'weber')
* [淘]
* 高分辨率的图像[巴]会导致较长的训[文]练和执行时间.[章]
* 在许多情况下，[来]在较低的分辨率[自]下可以检测到缺[网]陷
* (对应于更高的[淘]金字塔层次)，[巴]也.
Levels := [2,3,4][文]
set_texture_inspection_model_param (TextureInspectionModel, 'levels', Levels)
* [章]
* 开始训练.
train_texture_inspection_model (TextureInspectionModel)
* [来]
* 将纹理模型写入[自]磁盘
write_texture_inspection_model (TextureInspectionModel, TextureModelFilename)
* [网]
Message[淘] := '训练很成功.'
Message[巴][1] := ' '
endif
* [文]
Message[章][2] := '我们现在可以通[来]过评估测试图像[自]上的'
Message[网][3] := ' 新颖性检测结果[淘]来微调参数'
dev_disp_text (Message, 'window', 12, 12, 'black', [], [])
dev_disp_text ('Press Run (F5) to continue', 'window', 'bottom', 'right', 'black', [], [])
stop()
* [巴]
*我们得到了新[文]颖性阈值，以便[章]在测试阶段显示[来]它们.
* 新阈值定义了每[自]一个金字塔级别[网]，在这一点上区[淘]分有缺陷和无缺[巴]陷的纹理
* 较低的阈值会导[文]致更多的错误检[章]测，但也可能导[来]致更多的误报([自]无缺陷的纹理区[网]域作为缺陷返回[淘])
get_texture_inspection_model_param (TextureInspectionModel, 'novelty_threshold', NoveltyThreshold)
* [巴]
*调试产生的信[文]息在apply[章]_textur[来]e_inspe[自]ction_m[网]odel执行期[淘]间存储了。
* 注意，必须使用[巴]clear_t[文]exture_[章]inspect[来]ion_res[自]ult释放re[网]sult句柄。[淘]
set_texture_inspection_model_param (TextureInspectionModel, 'gen_result_handle', 'true')
* [巴]
WindowW[文]idth := 320
WindowH[章]eight := 280
dev_open_window (0, 0, WindowWidth, WindowHeight, 'black', WindowHandle1)
set_display_font (WindowHandle1, 16, 'mono', 'true', 'false')
dev_open_window (0, WindowWidth + 8, WindowWidth, WindowHeight, 'black', WindowHandle2)
set_display_font(WindowHandle2, 16, 'mono', 'true', 'false')
dev_open_window (0, 2 * WindowWidth + 16, WindowWidth, WindowHeight, 'black', WindowHandle3)
set_display_font(WindowHandle3, 16, 'mono', 'true', 'false')
dev_open_window (WindowHeight + 50, WindowWidth / 2 + 8, 2 * WindowWidth, 2 * WindowHeight, 'black', WindowHandle4)
set_display_font(WindowHandle4, 16, 'mono', 'true', 'false')
WindowH[来]andles := [Window[自]Handle1[网],Window[淘]Handle2[巴],Window[文]Handle3[章]]
* [来]
* 检测第一个训练[自]图像的纹理缺陷[网]，以微调参数.[淘]
for Index := 1 to 3 by 1
ImageIn[巴]dex := 5
read_image (TestImage, 'carpet/carpet_' + ImageIndex$'02')
* [文]
* 检查当前图像.[章]
apply_texture_inspection_model (TestImage, NoveltyRegion, TextureInspectionModel, TextureInspectionResultID)
* 检查调试信息.[来]
* 新颖性得分图像[自]可用于单独微调[网]新颖性阈值。.[淘]
get_texture_inspection_result_object (NovScoreImage, TextureInspectionResultID, 'novelty_score_image')
get_texture_inspection_result_object (NovRegion, TextureInspectionResultID, 'novelty_region')
* 清理结果句柄
clear_texture_inspection_result (TextureInspectionResultID)
* [巴]
* 显示单个尺度的[文]结果
count_o[章]bj (NovSco[来]reImage[自], Number)[网]
for Level := 1 to Number by 1
Current[淘]Window := WindowH[巴]andles[[文]Level - 1]
dev_set_window (CurrentWindow)
select_obj (NovScoreImage, NovScoreImageL, Level)
select_obj (NovRegion, NovRegionL, Level)
get_image_size (NovScoreImageL, Width, Height)
dev_set_part (0, 0, Height - 1, Width - 1)
dev_display (NovScoreImageL)
Legend := 'Novelty[章] region (level ' + Levels[[来]Level - 1] + ')'
dev_set_color ('red')
* [自]
dev_display (NovRegionL)
dev_disp_text (['Novelty score image (level ' + Levels[Level - 1] + ')','Novelty threshold: ' + NoveltyThreshold[Level - 1]$'.1f'], 'window', 12, 12, 'black', [], [])
dev_disp_text (Legend, 'window', WindowHeight - 30, 12, 'white', ['box_color','shadow'], ['black','false'])
* 注意，appl[网]y_textu[淘]re_insp[巴]ection_[文]model返回[章]的Novelt[来]yRegion[自]是通过组合各个[网]金字塔层的各个[淘]新奇区域而派生[巴]的.
endfor
* [文]
* 显示结果
dev_set_window (WindowHandle4)
dev_display (TestImage)
dev_set_color ('red')
dev_display (NoveltyRegion)
area_center (NoveltyRegion, Area, Row, Column)
if (Index < 3)
dev_disp_text ('Result', 'window', 12, 12, 'black', [], [])
else
dev_disp_text ('Final result', 'window', 12, 12, 'black', [], [])
endif
* [章]
* 对于第一个图像[来]，我们微调参数[自]，以确保最佳参[网]数设置
if (Index == 1)
Message[淘][0] := 'There are many small errors in the image.'
Message[巴][1] := 'It is possibl[文]e to adapt the sensiti[章]vity by alterin[来]g'
Message[自][2] := 'the novelty[网] thresho[淘]lds.'
Message[巴][3] := 'For example[文], this can be done by decreas[章]ing the'
Message[来][4] := 'value of the \'sensiti[自]vity\' paramet[网]er'
dev_disp_text (Message, 'window', 12, 12, 'black', [], [])
* 微调新颖性阈值[淘]。
* [巴]
* 设置阈值计算的[文]灵敏度。负值导[章]致更高的阈值，[来]因此检测到的缺[自]陷更少。
set_texture_inspection_model_param (TextureInspectionModel, 'sensitivity', -10)
get_texture_inspection_model_param (TextureInspectionModel, 'novelty_threshold', NoveltyThreshold)
endif
* [网]
if (Index == 2)
Message[淘] := 'It is also possibl[巴]e to adapt the sensiti[文]vity'
Message[章][1] := 'of the single levels individ[来]ually by manipul[自]ating'
Message[网][2] := 'the novelty[淘] boundar[巴]ies directl[文]y.'
dev_disp_text (Message, 'window', 12, 12, 'black', [], [])
* 微调新颖性阈值[章].
* [来]
* 从纹理检测模型[自]中获取(自动确[网]定的)新颖性阈[淘]值，并设置适当[巴]修改值作为新颖[文]性阈值。
* [章]
* 如果我们明确地[来]设定了新颖性的[自]界限，敏感性就[网]被忽略了。
* 为了避免混淆，[淘]我们把它设回0[巴]
set_texture_inspection_model_param (TextureInspectionModel, 'sensitivity', 0)
* [文]
Offset := [25,10,[章]30]
get_texture_inspection_model_param(TextureInspectionModel, 'novelty_threshold', NoveltyThreshold)
set_texture_inspection_model_param (TextureInspectionModel, 'novelty_threshold', Offset + NoveltyThreshold)
get_texture_inspection_model_param(TextureInspectionModel, 'novelty_threshold', NoveltyThreshold)
endif
* [来]
dev_disp_text ('Press Run (F5) to continue', 'window', 'bottom', 'right', 'black', [], [])
stop ()
endfor
* [自]
for Level := 1 to |Window[网]Handles[淘]| by 1
dev_set_window (WindowHandles[Level - 1])
endfor
dev_set_window (WindowHandle4)
Message[巴] := 'With the fine-tu[文]ned paramet[章]ers we can now'
Message[来][1] := 'detect defects[自] in all trainin[网]g and test images.[淘]..'
dev_disp_text (Message, 'window', 12, 12, 'black', [], [])
dev_disp_text ('Press Run (F5) to continue', 'window', 'bottom', 'right', 'black', [], [])
stop ()
* [巴]
* 在所有测试图像[文]上检测纹理缺陷[章]
for Index := 1 to NumImag[来]es by 1
read_image (TestImage, 'carpet/carpet_' + Index$'02')
* [自]
* 检查当前图像
apply_t[网]exture_[淘]inspect[巴]ion_mod[文]el (TestIm[章]age, Novelty[来]Region,[自] Texture[网]Inspect[淘]ionMode[巴]l, Texture[文]Inspect[章]ionResu[来]ltID)
* 检查调试信息
get_tex[自]ture_in[网]spectio[淘]n_resul[巴]t_objec[文]t (NovSco[章]reImage[来], Texture[自]Inspect[网]ionResu[淘]ltID, 'novelty[巴]_score_[文]image')
get_tex[章]ture_in[来]spectio[自]n_resul[网]t_objec[淘]t (NovReg[巴]ion, Texture[文]Inspect[章]ionResu[来]ltID, 'novelty[自]_region[网]')
* 清理结果句柄
clear_t[淘]exture_[巴]inspect[文]ion_res[章]ult (Textur[来]eInspec[自]tionRes[网]ultID)
* [淘]
* 显示单个尺度的[巴]结果
count_obj (NovScoreImage, Number)
for Level := 1 to Number by 1
Current[文]Window := WindowH[章]andles[[来]Level - 1]
dev_set_window (CurrentWindow)
select_obj (NovScoreImage, NovScoreImageL, Level)
select_obj (NovRegion, NovRegionL, Level)
get_image_size (NovScoreImageL, Width, Height)
dev_set_part (0, 0, Height - 1, Width - 1)
dev_display (NovScoreImageL)
Legend := 'Novelty[自] region (level ' + Levels[[网]Level - 1] + ')'
dev_set_color ('red')
* [淘]
dev_display (NovRegionL)
dev_disp_text (['Novelty score image (level ' + Levels[Level - 1] + ')','Novelty threshold: ' + NoveltyThreshold[Level - 1]$'.1f'], 'window', 12, 12, 'black', [], [])
dev_disp_text (Legend, 'window', WindowHeight - 50, 12, ['red','white'], ['box_color','shadow'], ['black','false'])
* 请注意，app[巴]ly_text[文]ure_ins[章]pection[来]_model返[自]回的Novel[网]tyRegio[淘]n是通过组合各[巴]个金字塔层次的[文]各个新奇区域派[章]生出来的。
endfor
* [来]
* 显示结果
dev_set_window (WindowHandle4)
dev_display (TestImage)
dev_set_color ('red')
dev_display (NoveltyRegion)
area_center (NoveltyRegion, Area, Row, Column)
if (Area > 100)
dev_disp_text ('Not OK', 'window', 12, 12, 'white', 'box_color', 'red')
else
dev_disp_text ('OK', 'window', 12, 12, 'white', 'box_color', 'forest green')
endif
* [自]
if (Index < NumImag[网]es)
dev_disp_text ('Press Run (F5) to continue', 'window', 'bottom', 'right', 'black', [], [])
stop()
endif
endfor
stop()
* [淘]
* 清理内存
clear_texture_inspection_model (TextureInspectionModel)
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