halcon: 训练 OCR

* "bottle.hdev"
* 第1步: 分割
dev_update_window ('off')
read_image (Bottle, 'bottle2')
get_image_size (Bottle, Width, Height)
dev_close_window ()
dev_open_window (0, 0, 2 * Width, 2 * Height, 'black', WindowID)
set_display_font (WindowID, 27, 'mono', 'true', 'false')

* 二值化后通过多次形态学处理，再连通域分析，再筛选区域后字符排序
threshold (Bottle, RawSegmentation, 0, 95) 
fill_up_shape (RawSegmentation, RemovedNoise, 'area', 1, 5)
opening_circle (RemovedNoise, ThickStructures, 2.5)
fill_up (ThickStructures, Solid)
opening_rectangle1 (Solid, Cut, 1, 7)
connection (Cut, ConnectedPatterns)
intersection (ConnectedPatterns, ThickStructures, NumberCandidates)
select_shape (NumberCandidates, Numbers, 'area', 'and', 300, 9999)
sort_region (Numbers, FinalNumbers, 'first_point', 'true', 'column')
dev_display (Bottle)
dev_set_color ('green')
dev_set_line_width (2)
dev_set_shape ('rectangle1')
dev_set_draw ('margin')
dev_display (FinalNumbers)
* 第2步: 生成训练文件
TrainingNames := ['0','1','0','8','9','4']
TrainingFileName := FontName + '.trf'
sort_region (FinalNumbers, SortedRegions, 'first_point', 'true', 'column')
shape_trans (SortedRegions, RegionTrans, 'rectangle1') 转换成矩形区域
area_center (RegionTrans, Area, Row, Column)
MeanRow := mean(Row) 行平均值
dev_set_check ('~give_error')
delete_file (TrainingFileName)
dev_set_check ('give_error')
for I := 0 to |TrainingNames| - 1 by 1
select_obj (SortedRegions, CharaterRegions, I + 1) 依次选取字符区域
append_ocr_trainf (CharaterRegions, Bottle, TrainingNames[I], TrainingFileName) 将区域、图片、字符Class加入训练文件开始训练
disp_message (WindowID, TrainingNames[I], 'image', MeanRow - 40, Column[I] - 6, 'yellow', 'false')
endfor
*
* 第3步: 训练
CharNames := uniq(sort(TrainingNames)) 取不重复的字符
create_ocr_class_mlp (8, 10, 'constant', 'default', CharNames, 10, 'none', 10, 42, OCRHandle) 创建多层感知器OCR模型，8和10是字符的像素宽和高
trainf_ocr_class_mlp (OCRHandle, TrainingFileName, 200, 1, 0.01, Error, ErrorLog) 训练，200轮
write_ocr_class_mlp (OCRHandle, FontName) 保存训练结果