如何解读haartraining结果?

时间:2014-12-17 17:19:45

标签: opencv machine-learning classification haar-classifier

我的haartraining程序目前正在我的电脑上运行。 我正在使用1700个阳性样本,以及大约1300个阴性样本。我运行了以下命令行:

opencv_traincascade -data data -vec cars.vec -bg bg.txt -numStages 10 -nsplits 2 -minhitrate 0.999 -maxfalsealarm 0.5 -numPos 1600 -numNeg 1371 -w 48 -h 24

目前,该报告如下:

===== TRAINING 0-stage =====
<BEGIN
POS count : consumed   1600 : 1600
NEG count : acceptanceRatio    1371 : 1
Precalculation time: 16
+----+---------+---------+
|  N |    HR   |    FA   |
+----+---------+---------+
|   1|        1|        1|
+----+---------+---------+
|   2|        1|        1|
+----+---------+---------+
|   3|        1|        1|
+----+---------+---------+
|   4|  0.99875| 0.587163|
+----+---------+---------+
|   5|  0.99875| 0.587163|
+----+---------+---------+
|   6| 0.995625| 0.305616|
+----+---------+---------+
END>
Training until now has taken 0 days 0 hours 21 minutes 19 seconds.

===== TRAINING 1-stage =====
<BEGIN
POS count : consumed   1600 : 1607
NEG count : acceptanceRatio    1371 : 0.338853
Precalculation time: 18
+----+---------+---------+
|  N |    HR   |    FA   |
+----+---------+---------+
|   1|        1|        1|
+----+---------+---------+
|   2|        1|        1|
+----+---------+---------+
|   3|        1|        1|
+----+---------+---------+
|   4|        1|        1|
+----+---------+---------+
|   5| 0.998125| 0.786287|
+----+---------+---------+
|   6|   0.9975| 0.673961|
+----+---------+---------+
|   7| 0.995625| 0.560175|
+----+---------+---------+
|   8|   0.9975| 0.531729|
+----+---------+---------+
|   9| 0.995625| 0.406273|
+----+---------+---------+
END>
Training until now has taken 0 days 0 hours -19 minutes -57 seconds.

===== TRAINING 2-stage =====
<BEGIN
POS count : consumed   1600 : 1614
NEG count : acceptanceRatio    1371 : 0.136649
Precalculation time: 17
+----+---------+---------+
|  N |    HR   |    FA   |
+----+---------+---------+
|   1|        1|        1|
+----+---------+---------+
|   2|        1|        1|
+----+---------+---------+
|   3|        1|        1|
+----+---------+---------+
|   4| 0.998125| 0.856309|
+----+---------+---------+
|   5| 0.999375| 0.875274|
+----+---------+---------+
|   6| 0.996875| 0.633115|
+----+---------+---------+
|   7| 0.995625| 0.546317|
+----+---------+---------+
|   8| 0.995625| 0.501094|
+----+---------+---------+
|   9|  0.99625| 0.524435|
+----+---------+---------+
|  10| 0.995625| 0.404814|
+----+---------+---------+
END>
Training until now has taken 0 days 0 hours 14 minutes 52 seconds.

所以到第二阶段训练结束时,我仍然看到0.4假警报率。在一些教程之后,我一直在选择10阶段级联。我已经读过一个好的分类器应该在10 ^ -5 FA附近,所以我想在第2阶段结束时有0.404,在第10阶段结束时很难达到10 ^ -5的FA速率。 我对吗 ?我已经停止并改善我的阴性和阳性样本了吗?

[编辑]我认为我对每个阶段的FA率和一般接受率感到困惑......

另一个问题出现在我的脑海中:舞台数量的影响是什么?性能与速度?

0 个答案:

没有答案