def hashDct(img):
arr = PIL2array(img)
src = cv.CreateMat(32, 32, CV_32FC1)
dst = cv.CreateMat(32, 32, CV_32FC1)
cv.DCT(src, dst, CV_DXT_FORWARD)
imgarray = numpy.asarray(dst)
img2 = Image.fromarray(numpy.uint8(imgarray))
return img2
print "Average:\t%d"
def dct_hash(img):
img = float_version(img)
small_img = cv.CreateImage((32, 32), 32, 1)
cv.Resize(img[20:190, 20:205], small_img)
dct = cv.CreateMat(32, 32, cv.CV_32FC1)
cv.DCT(small_img, dct, cv.CV_DXT_FORWARD)
dct = dct[1:9, 1:9]
avg = cv.Avg(dct)[0]
dct_bit = cv.CreateImage((8, 8), 8, 1)
cv.CmpS(dct, avg, dct_bit, cv.CV_CMP_GT)
return [dct_bit[y, x] == 255.0 for y in xrange(8) for x in xrange(8)]
def main():
img = Image.open("p.jpg")
img = img.resize((32, 32))
img = img.convert("L")
arr = PIL2array(img)
#print arr
src = cv.CreateMat(32, 32, cv.CV_32FC1)
dst = cv.CreateMat(32, 32, cv.CV_32FC1)
cv.DCT(src, dst, cv.CV_DXT_FORWARD)
imgarray = numpy.asarray(dst)
#img2 = array2PIL(imgarray, img.size)
#img2 = array2PIL(arr, img.size)
img2 = Image.fromarray(numpy.uint8(imgarray))
img2.save('out.jpg')
def old_GeneratePerceptualHash(path):
# I think what I should be doing here is going cv2.imread( path, flags = cv2.CV_LOAD_IMAGE_GRAYSCALE )
# then efficiently resize
thumbnail = GeneratePILImage(path)
# convert to 32 x 32 greyscale
if thumbnail.mode == 'P':
thumbnail = thumbnail.convert(
'RGBA'
) # problem with some P images converting to L without RGBA step in between
if thumbnail.mode == 'RGBA':
# this is some code i picked up somewhere
# another great example of PIL failing; it turns all alpha to pure black on a RGBA->RGB
thumbnail.load()
canvas = PILImage.new('RGB', thumbnail.size, (255, 255, 255))
canvas.paste(thumbnail, mask=thumbnail.split()[3])
thumbnail = canvas
thumbnail = thumbnail.convert('L')
thumbnail = thumbnail.resize((32, 32), PILImage.ANTIALIAS)
# convert to mat
numpy_thumbnail_8 = cv.CreateMatHeader(32, 32, cv.CV_8UC1)
cv.SetData(numpy_thumbnail_8, thumbnail.tostring())
numpy_thumbnail_32 = cv.CreateMat(32, 32, cv.CV_32FC1)
cv.Convert(numpy_thumbnail_8, numpy_thumbnail_32)
# compute dct
dct = cv.CreateMat(32, 32, cv.CV_32FC1)
cv.DCT(numpy_thumbnail_32, dct, cv.CV_DXT_FORWARD)
# take top left 8x8 of dct
dct = cv.GetSubRect(dct, (0, 0, 8, 8))
# get mean of dct, excluding [0,0]
mask = cv.CreateMat(8, 8, cv.CV_8U)
cv.Set(mask, 1)
mask[0, 0] = 0
channel_averages = cv.Avg(dct, mask)
average = channel_averages[0]
# make a monochromatic, 64-bit hash of whether the entry is above or below the mean
bytes = []
for i in range(8):
byte = 0
for j in range(8):
byte <<= 1 # shift byte one left
value = dct[i, j]
if value > average: byte |= 1
bytes.append(byte)
answer = str(bytearray(bytes))
# we good
return answer