14.6 Example
About1 Introduction2 Image Recognition3 TransApplet4 API5 Interface6 Input7 Image Display8 Preprocessing9 Processing10 Normalization11 Parameter Class12 Image Signatures13 Unsupervised Filters14 BioFilters15 NeuralFilters16 Dynamic Library17 NeuralNet Filter18 Parameters19 Input Options20 Database Input21 Video Input22 Live Video Input23 Counting & Tracking24 Counting 25 Batch Job26 ImageFinder for DOS27 ImageHunt 28 Support Packages
14.1 BioFilter Menu 
14.2 BioFilter API 
14.3 Training Design 
14.4 Implementation 
14.5 Parameters 
14.6 Example 
14.7 N:N Design 
14.8 N:N Implementation 
14.9 1:N Design 
14.10 1:N Implementation 
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14.6   Example: Label Recognition Training

We now revisit the Label Recognition example first introduced in the Unsupervised Filter.  We must prepare the match.txt file for training. This file is already prepared for you and we will simply open it and save it to match.txt. The steps are:

Match.txt

  •    Open the file, �.\data\match_ex_label.txt�. This file lists 152 matching pairs. Save it to match.txt (overwrite the existing file). Now the training file is prepared.

T1.txt:

  •    Click the �Source� button, go to �ex_label� directory and select any file in the folder. This will specify the input directory.
  •    Click  the Source �>� button a few times to see the images;
  •    Click menu item �Signature/N Signature (a1.txt)� to get signature file, a1.txt file;
  •    Click menu item �Signature/Copy a1.txt to t1.txt� to get the training file, t1.txt.

Note: Here t1.txt is for training and a1.txt is for 1:N Matching and N:N Matching.

Training

  •    Click �BioFilter\Training\Training� to train the BioFilter.

You should get this message at the end of the text window:

        Total Number of Matches = 152

        Number of Images that have No Match = 152

There are 304 images in 152 pairs. The match.txt listed 152 pairs.

  •    The first line, Total Number of Matches = 152, indicates the training used 152 pairs.
  •    The second line, Number of Images that have No Match = 152, indicates 152 out of 304 images does not have a match, which is correct. This is because in match.txt which has 152 pairs, (A, B), only A will match with B, but B will not match with A.

Now, the BioFilter is trained for the Label Recognition problem. We will continue this example in the next section, N:N Matching.

 

[Home][About][1 Introduction][2 Image Recognition][3 TransApplet][4 API][5 Interface][6 Input][7 Image Display][8 Preprocessing][9 Processing][10 Normalization][11 Parameter Class][12 Image Signatures][13 Unsupervised Filters][14 BioFilters][15 NeuralFilters][16 Dynamic Library][17 NeuralNet Filter][18 Parameters][19 Input Options][20 Database Input][21 Video Input][22 Live Video Input][23 Counting & Tracking][24 Counting ][25 Batch Job][26 ImageFinder for DOS][27 ImageHunt ][28 Support Packages]

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