Tests the given test_classifier on the given samples. error_mode indicates what counts as an error. report_levels: 0 = no output. 1 = bottom-line error rate. 2 = bottom-line error rate + time. 3 = font-level error rate + time. 4 = list of all errors + short classifier debug output on 16 errors. 5 = list of all errors + short classifier debug output on 25 errors. If replicate_samples is true, then
| 796 | // If report_string is non-NULL, a summary of the results for each font |
| 797 | // is appended to the report_string. |
| 798 | double MasterTrainer::TestClassifier(CountTypes error_mode, |
| 799 | int report_level, |
| 800 | bool replicate_samples, |
| 801 | TrainingSampleSet* samples, |
| 802 | ShapeClassifier* test_classifier, |
| 803 | STRING* report_string) { |
| 804 | SampleIterator sample_it; |
| 805 | sample_it.Init(NULL, NULL, replicate_samples, samples); |
| 806 | if (report_level > 0) { |
| 807 | int num_samples = 0; |
| 808 | for (sample_it.Begin(); !sample_it.AtEnd(); sample_it.Next()) |
| 809 | ++num_samples; |
| 810 | tprintf("Iterator has charset size of %d/%d, %d shapes, %d samples\n", |
| 811 | sample_it.SparseCharsetSize(), sample_it.CompactCharsetSize(), |
| 812 | test_classifier->GetShapeTable()->NumShapes(), num_samples); |
| 813 | tprintf("Testing %sREPLICATED:\n", replicate_samples ? "" : "NON-"); |
| 814 | } |
| 815 | double unichar_error = 0.0; |
| 816 | ErrorCounter::ComputeErrorRate(test_classifier, report_level, |
| 817 | error_mode, fontinfo_table_, |
| 818 | page_images_, &sample_it, &unichar_error, |
| 819 | NULL, report_string); |
| 820 | return unichar_error; |
| 821 | } |
| 822 | |
| 823 | // Returns the average (in some sense) distance between the two given |
| 824 | // shapes, which may contain multiple fonts and/or unichars. |
nothing calls this directly
no test coverage detected