HALCON示例程序classify_image_class_mlp.hdev如何使用MLP分類器分割RGB圖像

示例程序源碼（加注釋）

關(guān)于顯示相關(guān)顯示在其他帖子有介紹。
dev_update_off ()
dev_close_window ()
dev_open_window (0, 0, 735, 485, ‘black’, WindowHandle)
set_display_font (WindowHandle, 14, ‘mono’, ‘true’, ‘false’)
dev_set_draw (‘margin’)
dev_set_colored (6)
dev_set_line_width (3)
read_image (Image, ‘patras’)
dev_display (Image)
Color := [‘indian red’,‘cornflower blue’,‘white’,‘black’,‘yellow’]

• 創(chuàng)建分割不同類別的區(qū)域
  gen_rectangle1 (Sea, 10, 10, 120, 270)
  gen_rectangle2 (Deck, [170,400], [350,375], [-0.56,-0.75], [64,104], [26,11])
  union1 (Deck, Deck)
  gen_rectangle1 (Walls, 355, 623, 420, 702)
  gen_rectangle2 (Chimney, 286, 623, -0.56, 64, 33)
• concat_obj介紹
  concat_obj (Sea, Deck, Classes)
  concat_obj (Classes, Walls, Classes)
  concat_obj (Classes, Chimney, Classes)
• 顯示
  dev_set_color (Color[0])
  dev_display (Deck)
  dev_set_color (Color[1])
  dev_display (Sea)
  dev_set_color (Color[2])
  dev_display (Walls)
  dev_set_color (Color[3])
  dev_display (Chimney)
  Message := ‘Training regions for the color classifier’
  disp_message (WindowHandle, Message, ‘window’, 12, 12, ‘black’, ‘true’)
  disp_continue_message (WindowHandle, ‘black’, ‘true’)
• 程序停止運(yùn)行，便于觀察
  stop ()
• 創(chuàng)建MLP分類器，并添加分類樣本
• create_class_mlp( : : 輸入維度數(shù)量, 隱藏單位數(shù), 輸出類別數(shù), 輸出函數(shù)類型, 預(yù)處理類型, 預(yù)處理參數(shù), 迭代次數(shù) : MLP句柄)
  create_class_mlp (3, 3, 4, ‘softmax’, ‘principal_components’, 3, 42, MLPHandle)
• 為MLP添加訓(xùn)練樣本
• add_samples_image_class_mlp(圖像, 不同類的區(qū)域: : MLP句柄 : )
  add_samples_image_class_mlp (Image, Classes, MLPHandle)
  dev_display (Image)
  Message := ‘Training …’
  disp_message (WindowHandle, Message, ‘window’, 12, 12, ‘black’, ‘true’)
• 訓(xùn)練分類器
• train_class_mlp( : : MLP句柄, 最大迭代次數(shù), 權(quán)重差異閾值, 誤差差異閾值: 平均誤差, 平均誤差Log)
  train_class_mlp (MLPHandle, 200, 1, 0.01, Error, ErrorLog)
  Message := Message + ’ ready.’
  Message[1] := ‘Segment image using the classifier …’
  disp_message (WindowHandle, Message, ‘window’, 12, 12, ‘black’, ‘true’)
• 分割圖像
• classify_image_class_mlp(圖像 : 分割結(jié)果: MLP句柄, 拒絕分類區(qū)域閾值: )
  classify_image_class_mlp (Image, ClassRegions, MLPHandle, 0.5)
• 使用區(qū)域的平均灰度值填充圖像
  region_to_mean (ClassRegions, Image, ImageClass)
  dev_display (ImageClass)
  Message[1] := Message[1] + ’ ready.’
  disp_message (WindowHandle, Message, ‘window’, 12, 12, ‘black’, ‘true’)
• 清除句柄
  clear_class_mlp (MLPHandle)
  disp_continue_message (WindowHandle, ‘black’, ‘true’)
  stop ()
• 下邊分割了另幾種顏色和上文一樣
  gen_rectangle2 (Rejection, [193,66,261], [235,332,328], [-0.32,-1.45,-1.51], [33,34,60], [4,3,3])
  union1 (Rejection, Rejection)
  concat_obj (Classes, Rejection, Classes)
  dev_display (Image)
  dev_set_color (Color[0])
  dev_display (Deck)
  dev_set_color (Color[1])
  dev_display (Sea)
  dev_set_color (Color[2])
  dev_display (Walls)
  dev_set_color (Color[3])
  dev_display (Chimney)
  dev_set_color (Color[4])
  dev_display (Rejection)
  disp_message (WindowHandle, ‘Add a rejection class to improve the robustness of the classifier’, ‘window’, 12, 12, ‘black’, ‘true’)
  disp_continue_message (WindowHandle, ‘black’, ‘true’)
  stop ()
  dev_display (Image)
• Create the classifier and add the samples
  create_class_mlp (3, 4, 5, ‘softmax’, ‘principal_components’, 3, 42, MLPHandle)
  add_samples_image_class_mlp (Image, Classes, MLPHandle)
• Train the classifier
  Message := ‘Training the classifier with rejection class…’
  disp_message (WindowHandle, Message, ‘window’, 12, 12, ‘black’, ‘true’)
  train_class_mlp (MLPHandle, 200, 1, 0.01, Error, ErrorLog)
  Message := Message + ’ ready.’
  Message[1] := ‘Segment image using the classifier …’
  disp_message (WindowHandle, Message, ‘window’, 12, 12, ‘black’, ‘true’)
• Segment (classify) the image
  classify_image_class_mlp (Image, ClassRegionsNotRejected, MLPHandle, 0.5)
• Select every class except the rejection class.
  copy_obj (ClassRegionsNotRejected, ClassRegionsNotRejected, 1, 4)
• Note that the black areas in the mean image correspond to the rejected pixels
  region_to_mean (ClassRegionsNotRejected, Image, ImageClassNotRejected)
  dev_display (ImageClassNotRejected)
  Message[1] := Message[1] + ’ ready.’
  disp_message (WindowHandle, Message, ‘window’, 12, 12, ‘black’, ‘true’)
  clear_class_mlp (MLPHandle)

處理思路

這個(gè)例子介紹了使用MLP分類器對(duì)彩色圖片進(jìn)行分類的例子，選取多通道圖片的感興趣區(qū)域與背景可以對(duì)多通道圖片進(jìn)行快速分類。

后記

大家有什么問(wèn)題可以向我提問(wèn)哈，我看到了第一時(shí)間回復(fù)，希望在學(xué)習(xí)的路上多多結(jié)交良師益友。

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