I'm refererring http://abhishek4273.wordpress.com/2014/02/10/opencv-haar-training/ to create the Haar Classifier in OpenCV, I have got the error in,
$ perl createtrainsamples.pl positives.txt negatives.txt samples 200 "opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1 -maxyangle 1.1 maxzangle 0.5 -maxidev 40 -w 20 -h 20"
opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1 -maxyangle 1.1 maxzangle 0.5 -maxidev 40 -w 20 -h 20 -img ./pos/5.jpg -bg tmp -vec samples/5.jpg.vec -num 40
Info file name: (NULL)
Img file name: ./pos/5.jpg
Vec file name: samples/5.jpg.vec
BG file name: tmp
Num: 40
BG color: 0
BG threshold: 0
Invert: FALSE
Max intensity deviation: 40
Max x angle: 1.1
Max y angle: 1.1
Max z angle: 0.5
Show samples: FALSE
Width: 20
Height: 20
Create training samples from single image applying distortions...
OpenCV Error: Bad argument (Quadrangle is nonconvex or degenerated.) in cvWarpPerspective, file /home/project/OpenCV/opencv-2.4.9/apps/haartraining/cvsamples.cpp, line 217
terminate called after throwing an instance of 'cv::Exception'
what(): /home/project/OpenCV/opencv-2.4.9/apps/haartraining/cvsamples.cpp:217: error: (-5) Quadrangle is nonconvex or degenerated. in function cvWarpPerspective
Above error generated for all the samples in positive folder.
Eventhough it generates error, it has created 8 samples.jpg.vec files in the samples folder.
Actually i have passed 200 as my samples, but it is creating only 8 of those in samples folder and throwing above error, and if try to merge using,
$./mergevec samples.txt samples.vec
It shows following error,
OpenCV Error: Assertion failed (elements_read == 1) in icvGetHaarTraininDataFromVecCallback, file cvhaartraining.cpp, line 1859
terminate called after throwing an instance of 'cv::Exception'
what(): cvhaartraining.cpp:1859: error: (-215) elements_read == 1 in function icvGetHaarTraininDataFromVecCallback
Aborted (core dumped)
If any one knows the answer for the following please do post it.
Related
I have a solution for solving an MIP problem of graph which works fine and gives the following output when I run it for smaller graphs. I'm using Gurobi solver with Pyomo.
Problem:
- Name: x73
Lower bound: 192.0
Upper bound: 192.0
Number of objectives: 1
Number of constraints: 10
Number of variables: 37
Number of binary variables: 36
Number of integer variables: 36
Number of continuous variables: 1
Number of nonzeros: 37
Sense: minimize
Solver:
- Status: ok
Return code: 0
Message: Model was solved to optimality (subject to tolerances), and an optimal solution is available.
Termination condition: optimal
Termination message: Model was solved to optimality (subject to tolerances), and an optimal solution is available.
Wall time: 0.03206682205200195
Error rc: 0
Time: 0.09361410140991211
Solution:
- number of solutions: 0
number of solutions displayed: 0
But I am getting the following error while running the code with larger graphs.
ERROR: Solver (gurobi) returned non-zero return code (137)
ERROR: Solver log: Using license file /opt/shared/gurobi/gurobi.lic Set
parameter TokenServer to value gurobi.lm.udel.edu Set parameter TSPort to
value 40100 Read LP format model from file /tmp/tmpaud9ogrn.pyomo.lp
Reading time = 0.01 seconds x1101: 56 rows, 551 columns, 551 nonzeros
Changed value of parameter TimeLimit to 600.0
Prev: inf Min: 0.0 Max: inf Default: inf
Gurobi Optimizer version 9.0.1 build v9.0.1rc0 (linux64) Optimize a model
with 56 rows, 551 columns and 551 nonzeros Model fingerprint: 0xafe0319a
Model has 15400 quadratic objective terms Variable types: 1 continuous,
550 integer (550 binary) Coefficient statistics:
Matrix range [1e+00, 1e+00] Objective range [0e+00, 0e+00]
QObjective range [4e+00, 8e+01] Bounds range [1e+00, 1e+00] RHS
range [1e+00, 1e+00]
Found heuristic solution: objective 22880.000000 Presolve removed 1 rows
and 1 columns Presolve time: 0.01s Presolved: 55 rows, 550 columns, 550
nonzeros Presolved model has 15400 quadratic objective terms Variable
types: 0 continuous, 550 integer (550 binary)
Root simplex log...
Iteration Objective Primal Inf. Dual Inf. Time
130920 9.8490000e+02 1.610955e+03 0.000000e+00 5s 263917
1.0999000e+03 1.710649e+03 0.000000e+00 10s 397157
1.0999000e+03 2.243077e+03 0.000000e+00 15s 529512
1.0999000e+03 1.910603e+03 0.000000e+00 20s 662404
1.0999000e+03 1.584650e+03 0.000000e+00 25s 791296
1.0999000e+03 1.812443e+03 0.000000e+00 30s 906473
1.3475000e+03 0.000000e+00 0.000000e+00 34s
Root relaxation: objective 1.347500e+03, 906473 iterations, 34.32 seconds
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node
Time
H 0 0 1730.0000000 0.00000 100% - 52s
H 0 0 1654.0000000 0.00000 100% - 52s
H 0 0 1578.0000000 0.00000 100% - 52s
0 0 1347.50000 0 137 1578.00000 1347.50000 14.6% - 52s
0 0 1347.50000 0 137 1578.00000 1347.50000 14.6% - 53s
H 0 0 1540.0000000 1347.50000 12.5% - 53s
0 2 1347.50000 0 145 1540.00000 1347.50000 12.5% - 55s
101 118 1396.92351 10 140 1540.00000 1347.50000 12.5% 157 61s
490 591 1416.40484 18 128 1540.00000 1347.50000 12.5% 63.6 65s
2136 2347 1440.09938 42 100 1540.00000 1347.50000 12.5% 42.9 70s
3847 3402 1461.55736 81 80 1540.00000 1347.50000 12.5% 37.0 82s
/opt/shared/gurobi/9.0.1/bin/gurobi.sh: line 17: 23890 Killed
$PYTHONHOME/bin/python3.7 "$#"
Traceback (most recent call last):
File "/home/2925/EdgeColoring/main.py", line 91, in <module>
qubo_coloring, qubo_time = qubo(G, colors, edge_list, solver)
File "/home/2925/EdgeColoring/qubo.py", line 59, in qubo
result = solver.solve(model)
File "/home/2925/.conda/envs/qubo/lib/python3.9/site-packages/pyomo/opt/base/solvers.py", line 596, in solve
raise ApplicationError(
pyomo.common.errors.ApplicationError: Solver (gurobi) did not exit normally
Using TimeLimit upto 2 minutes breaks the model early without any error but doesn't always give any optimal solution for larger graphs. Memory or processing power is not an issue here. I need to run the code without any interruption for at least 10 minutes if not for hours.
i need your help :) today i trained possitive image and negative image for HAAR detection. I followed this command below :
opencv_traincascade -data classifier -vec samples.vec -bg negatives.txt\ -numStages 20 -minHitRate 0.999 -maxFalseAlarmRate 0.5 -numPos 1000\ -numNeg 600 -w 80 -h 40 -mode ALL -precalcValBufSize 1024\ -precalcIdxBufSize 1024
(from CodingRobin) on my terminal, it seems "Done".
But there's no .vec files in samples directory. Can anyone help me ??
opencv_traincascade.exe USES the vec file. You must call the opencv_createsamples.exe instead.
The command line should look like:
opencv_createsamples.exe -info positives.txt -vec samples.vec -w 24 -h 24 -num 4455
for your number of samples and width/height
positives.txt should look like (each line):
#path #numberOfObjects #xObj1 #yObj1 #widthObj1 #heightObj1 #xObj2 #...
for example:
image1.png 1 0 0 84 84
image2.jpg 1 100 130 128 128
image3.png 2 10 30 50 50 300 100 101 101
etc.
After that you can train by calling opencv_traincascade with your parameter list and you'll get a .xml file as result.
I'm trying to train object detector based on train_object_detector.cpp example using dlib library.
time ./train_object_detector -tv -u 0 --threads 4 --flip data/training.xml
Loading image dataset from metadata file data/training.xml
Number of images loaded: 78
objective: 45.1205
objective gap: 45.1167
risk: 45.1167
risk gap: 45.1167
num planes: 3
iter: 1
...
objective: 3.44535
objective gap: 0.00889926
risk: 2.99319
risk gap: 0.00889926
num planes: 60
iter: 157
Saving trained detector to object_detector.svm
Testing detector on training data...
Test detector (precision,recall,AP): 1 0 0
Parameters used:
threads: 4
C: 1
eps: 0.01
target-size: 6400
detection window width: 80
detection window height: 80
upsample this many times : 0
trained using left/right flips.
real 3m17.072s
user 9m54.928s
sys 0m4.328s
Test detector (precision,recall,AP): 1 0 0 means that true positives = 0 and false positives = 0?
And also when apply detector to any image from training set it can't detect any objects Number of detections: 0.
How to fix this?
I am trying to train a haar cascade using opencv_traincascade executable in opencv 3.1.0.
For the moment I want to do this using only one positive even though the result is inconsistent, in order to be sure that I am passing the right parameters to opencv_createsamples and opencv_traincascade.
bg.txt content:
negatives/img_04436_c1.pgm
negatives/img_04437_c1.pgm
Negatives resolution: width: 1176 height: 640
Positives resolution: width: 40 height: 70
I am using the following command parameters:
For opencv_createsamples:
./opencv_createsamples -img img_04569_c1.pgm -vec samples -bg bg.txt -maxxangle 0.1 -maxyangle 0.1 -maxzangle 0.1 -w 40 -h 70 -num 30
Info file name: (NULL)
Img file name: img_04569_c1.pgm
Vec file name: samples.vec
BG file name: bg.txt
Num: 30
BG color: 0
BG threshold: 80
Invert: FALSE
Max intensity deviation: 40
Max x angle: 0.1
Max y angle: 0.1
Max z angle: 0.1
Show samples: FALSE
Width: 40
Height: 70
Create training samples from single image applying distortions...
Open background image: negatives/img_04436_c1.pgm
Done
For opencv_traincascade:
./opencv_traincascade -data cascade -vec samples -bg bg.txt -w 40 -h 70 -numPos 30 -numStages 1 -numNeg 2
PARAMETERS:
cascadeDirName: cascade
vecFileName: samples.vec
bgFileName: bg.txt
numPos: 30
numNeg: 2
numStages: 2
precalcValBufSize[Mb] : 1024
precalcIdxBufSize[Mb] : 1024
acceptanceRatioBreakValue : -1
stageType: BOOST
featureType: HAAR
sampleWidth: 40
sampleHeight: 70
boostType: GAB
minHitRate: 0.995
maxFalseAlarmRate: 0.5
weightTrimRate: 0.95
maxDepth: 1
maxWeakCount: 100
mode: BASIC
===== TRAINING 0-stage =====
<BEGIN
POS count : consumed 28 : 28
*** Error in `./opencv_traincascade': double free or corruption (out): 0x00000000016749b0 ***
Aborted (core dumped)
My problem is the following:
I am able to create the sample.vec file.
When I run opencv_traincascade I get the following error:
*** Error in `./opencv_traincascade': double free or corruption (out): 0x0000000001e0e9b0 ***
Sometimes I also get a Segmentation Fault error.
I tried to resize the negatives to a lower resolution and I am able to generate the xml file but when I am trying to use it nothing happens. (the classifier is stucked and runs continuously without returning any rectangles)
I want to use my original negatives size.
Can anybody help me to solve this problem ?
If more details are required please leave a comment and I will update my question.
I'm trying to train my own cascade, but get the following error:
Unspecified error (No element name has been given) in cv::operator
<<, file C:\builds\2_4_PackSlave-win64-vc11-shared\opencv\modules\core\include\
opencv2/core/operations.hpp, line 2910
I made these steps:
I cut 20 photos of the object so that they remained only the desired object
Resize to 30x18
Make objectSamples.dat file like this :
object(1).jpg 1 0 0 30 18
object(10).jpg 1 0 0 30 18
object(11).jpg 1 0 0 30 18
And negatives.dat like :
negatives\1.jpeg
negatives\10.jpg
negatives\11.jpg
size of pic ~ 500x500
4.Make vec file:
opencv_createsamples -info objectSamples.dat -vec objectSamples.vec -w 30 -h 18 -num 20
5.Show samples ( my pictures are shown entirely) : opencv_createsamples -vec objectSamples.vec -w 30 -h 18
6.Try to train : opencv_traincascade -data Cascade -vec objectSamples.vec -bg negatives.dat -numPos 10 -numNeg 10 -numStages 2 -featureType HAAR -w 30 -h 18
But get an error:
What am I doing wrong?
I read these articles and the answer, but I didn't understand, in what a problem:
trouble-when-use-opencv_traincascadeexe
haartraining tutorial
docs.opencv traincascade
Increased the number of images to 1000 positive and 2000 negatives
opencv_traincascade -data Cascade -vec boobsSamples.vec -bg negativesBig/negatives.txt -numPos 400 -numNeg 1000 -numStages 2 -featureType HAAR -w 30 -h 18 -mode ALL
Geting the same error.
Problem solved!
I copied the opencv_traincascade.exe to a folder of images. When I ordered the full path to the opencv_traincascade.exe in the library, the problem disappeared.
F:\OpenCV\opencv\build\x64\vc11\bin\opencv_traincascade -data Cascade -vec positives.vec -bg negativesBig/negatives.txt -numPos 400 -numNeg 1000 -numStages 2 -featureType HAAR -w 30 -h 18 -mode ALL