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finalaverage.py
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finalaverage.py
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import os, numpy, PIL
from PIL import Image, ImageEnhance
import numpy as np
from PIL import Image
import sys
size=[[20,35],
[20,35],
[20,35],
[20,40],
[20,40],
[20,40],
[20,40],
[20,40],
[20,40],
[25,22],
[25,22],
[25,22]]
def HaarArr ():
from dataList import haar_sizes
haar_sizes = haar_sizes()
imgArr = []
for i in range(1,34):
if i == 4 :
# bugun data
allfiles = os.listdir('./bugun/' + str(i) + '/')
imList = ['./bugun/' + str(i) + '/' + filename for filename in allfiles]
images = np.array([np.array(Image.open(filename)) for filename in imList])
arr = np.array(np.mean(images, axis=(0)), dtype=np.uint8)
out = Image.fromarray(arr)
avg = PIL.ImageEnhance.Contrast(out).enhance(1000)
im = np.array(avg.convert('L').resize((size[0][0],size[0][1])))
sys.stdout = open('C:/Users/kyeb2/PycharmProjects/face-detectio/haar1-3.txt', 'w')
th1 = 30
im_bin_128_1 = (im > th1) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_1)).save('./avgImgs1/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_1)
# th2 = 70
# im_bin_128_2 = (im > th2) * 255
# #print(im_bin_128) # 0 까만, 255 흰색
# Image.fromarray(np.uint8(im_bin_128_2)).save('./avgImgs2/' + 'avg' + str(i) + '.bmp')
# imgArr.append(im_bin_128_2)
#
# th3 = 100
# im_bin_128_3 = (im > th3) * 255
# #print(im_bin_128) # 0 까만, 255 흰색
# Image.fromarray(np.uint8(im_bin_128_3)).save('./avgImgs3/' + 'avg' + str(i) + '.bmp')
# imgArr.append(im_bin_128_3)
if i == 11 :
# bugun data
allfiles = os.listdir('./bugun/' + str(i) + '/')
imList = ['./bugun/' + str(i) + '/' + filename for filename in allfiles]
images = np.array([np.array(Image.open(filename)) for filename in imList])
arr = np.array(np.mean(images, axis=(0)), dtype=np.uint8)
out = Image.fromarray(arr)
avg = PIL.ImageEnhance.Contrast(out).enhance(1000)
im = np.array(avg.convert('L').resize((size[3][0],size[3][1])))
th1 = 30
im_bin_128_1 = (im > th1) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_1)).save('./avgImgs1/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_1)
th2 = 70
im_bin_128_2 = (im > th2) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_2)).save('./avgImgs2/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_2)
th3 = 100
im_bin_128_3 = (im > th3) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_3)).save('./avgImgs3/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_3)
if i == 14 :
# bugun data
allfiles = os.listdir('./bugun/' + str(i) + '/')
imList = ['./bugun/' + str(i) + '/' + filename for filename in allfiles]
images = np.array([np.array(Image.open(filename)) for filename in imList])
arr = np.array(np.mean(images, axis=(0)), dtype=np.uint8)
out = Image.fromarray(arr)
avg = PIL.ImageEnhance.Contrast(out).enhance(1000)
im = np.array(avg.convert('L').resize((size[6][0],size[6][1])))
th1 = 30
im_bin_128_1 = (im > th1) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_1)).save('./avgImgs1/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_1)
th2 = 70
im_bin_128_2 = (im > th2) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_2)).save('./avgImgs2/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_2)
th3 = 100
im_bin_128_3 = (im > th3) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_3)).save('./avgImgs3/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_3)
if i == 24 :
# bugun data
allfiles = os.listdir('./bugun/' + str(i) + '/')
imList = ['./bugun/' + str(i) + '/' + filename for filename in allfiles]
images = np.array([np.array(Image.open(filename)) for filename in imList])
arr = np.array(np.mean(images, axis=(0)), dtype=np.uint8)
out = Image.fromarray(arr)
avg = PIL.ImageEnhance.Contrast(out).enhance(1000)
im = np.array(avg.convert('L').resize((size[9][0],size[9][1])))
th1 = 30
im_bin_128_1 = (im > th1) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_1)).save('./avgImgs1/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_1)
th2 = 70
im_bin_128_2 = (im > th2) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_2)).save('./avgImgs2/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_2)
th3 = 100
im_bin_128_3 = (im > th3) * 255
#print(im_bin_128) # 0 까만, 255 흰색
Image.fromarray(np.uint8(im_bin_128_3)).save('./avgImgs3/' + 'avg' + str(i) + '.bmp')
imgArr.append(im_bin_128_3)
return imgArr
# 실행
HaarArr = HaarArr ()
# print(HaarArr)
# print(len(HaarArr))
# print(len(size))
# 각 점의 좌표 찍어내기 (Haar)
for i in range(len(HaarArr)) :
pos = []
neg = []
for h1 in range(size[i][1]):
for w1 in range(size[i][0]):
if str(HaarArr[i][h1,w1])=='255':
print('neg' + str(w1) + str(h1) + '=' + 'self.getPixelValInIntegralMat(x+' + str(w1) + '*w' + ',y+' + str(h1) + '*h' + ', w, h, IntegralMat)')
neg.append('neg' + str(w1) + str(h1))
else :
print('pos' + str(w1) + str(h1) + '=' + 'self.getPixelValInIntegralMat(x+' + str(w1) + '*w' + ',y+' + str(h1) + '*h' + ', w, h, IntegralMat)')
pos.append('pos' + str(w1) + str(h1))
print('featureVal[feature_index] = ((\\')
for n in range(len(neg)):
if n == len(neg)-1 :
print(str(neg[n]),flush=True)
else :
print(str(neg[n]) + '+', end='', flush=True)
print(")-(")
for p in range(len(pos)):
if i == len(pos)-1 :
print(str(pos[p]), flush=True)
else :
print(str(pos[p]) + "+", end='', flush=True)
area = size[i][0] * size[i][1]
print(")/("+str(area)+"* w * h))")
print()
print("============================================="+str(i+1)+"번째 이미지 끝")
print("")
print("!! HAAR 종료 이제 Detector 시작 !!")
# 각 점의 좌표 찍어내기 (Detector)
for i in range(len(HaarArr)) :
pos = []
neg = []
for h1 in range(size[i][1]):
for w1 in range(size[i][0]):
if str(HaarArr[i][h1,w1])=='255':
print('neg' + str(w1) + str(h1) + '=' + 'self.haar.getPixelValInIntegralMat(x+' + str(w1) + '*w' + ',y+' + str(h1) + '*h' + ', w, h, subWindowImgIntegral)')
neg.append('neg' + str(w1) + str(h1))
else :
print('pos' + str(w1) + str(h1) + '=' + 'self.haar.getPixelValInIntegralMat(x+' + str(w1) + '*w' + ',y+' + str(h1) + '*h' + ', w, h, subWindowImgIntegral)')
pos.append('pos' + str(w1) + str(h1))
print(' scaledWindowsMat[window][dimension] = ((\\')
for n in range(len(neg)):
if n == len(neg)-1 :
print(str(neg[n]),flush=True)
else :
print(str(neg[n]) + '+', end='', flush=True)
print(")-(")
for p in range(len(pos)):
if i == len(pos)-1 :
print(str(pos[p]), flush=True)
else :
print(str(pos[p]) + "+", end='', flush=True)
area = size[i][0] * size[i][1]
print(")/("+str(area)+"* w * h))")
print()
print("============================================="+str(i+1)+"번째 이미지 끝")