Problem with Haar cascade

edit

Hi

I am trying to detect mosquitoes on images using Haar Cascade and it doesn't work.

I use ~200 images of walls (to use as negative images) and ~20 images of mosquitoes.

I did this :

1) I run the script below to resize the negative images (100x100 ) :

[karim@10-83-102-17 haar]$ more resize.py

import cv2
import os

pic_num=0
for img in os.listdir('/home/karim/perso/moustiques/haar/downloads/wall'):
    print img
    timg = cv2.imread('/home/karim/perso/moustiques/haar/downloads/wall/'+img,cv2.IMREAD_GRAYSCALE)
    resized_image = cv2.resize(timg, (100, 100))
    cv2.imwrite("negatif/"+str(pic_num)+".jpg",resized_image)
    pic_num=pic_num+1

[karim@10-83-102-17 haar]$ ls negatif/* > negatif.txt

2) I run the script below to generate positive images :

[karim@10-83-102-17 haar]$ more samplepos.sh

#!/bin/bash

mkdir -p info 

# create the samples
for file in downloads/9*.jpg; do
    echo "File=" $file
    opencv_createsamples -img "$file" -bg negatif.txt -info "info/info_$file.da"t -pngoutput info -maxxangle 0.5 -maxyangle -0.5 -maxzangle 0.5 -num 125
done

mv info/info_downloads/* info

# generate the sample file
touch temp
for file in info/*.dat; do
    echo "File="$file
    cat temp "$file" >> ./info/info.dat
done

# generate the sample vector
opencv_createsamples -info info/info.dat -vec positif.vec -w 25 -h 18 -num 2000

3) Then, I train the classifier

[karim@10-83-102-17 haar]$ more train.sh

#!/bin/bash

mkdir -p data

# train the classifier using haar cascade features
opencv_traincascade -data data -vec positif.vec -bg negatif.txt -numStages 10 -numPos 1800 -numNeg 900 -w 25 -h 18 -mode ALL -precalcValBuffSize 1024 -precalcIdxBuffSize 1024

mv ./data/cascade.xml .

It runs a couple of hours.

4) If I run the classifier on a mosquito image, I have the attached image

[karim@10-83-102-17 haar]$ more verif.py

import cv2

from matplotlib import pyplot as plt

img=cv2.imread('img_mous.jpg')
imggris = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgrgb = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)

FiltreMoustique=cv2.CascadeClassifier("/home/karim/perso/moustiques/haar/cascade.xml")

moustique=FiltreMoustique.detectMultiScale(imggris,scaleFactor=1.1,minNeighbors=4,minSize=(20,20))

n=len(moustique)

if n!=0:
    for (x,y,w,h) in moustique:
        cv2.rectangle(imgrgb,(x,y),(x+h,y+w),(0,255,0),5)

plt.subplot(1,1,1)
plt.imshow(imgrgb)
plt.show()

I got scripts from internet and I modified them for my use. I am probably doing something wrong ... Thanks for any advice.

Karim