def __call__(self, img):
img_temp = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
try:
debug_print('Writing temp file [{0}] for zxing'.format(img_temp.name))
cv2.imwrite(img_temp.name, img)
return self.decode_file(img_temp.name)
finally:
# TODO LH Logic here?
img_temp.close()
os.unlink(img_temp.name)
def __call__(self, img):
# Temporary files on Windows are pain
img_temp = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
try:
debug_print('Writing temp file [{0}] for Data Symbol'.format(img_temp.name))
cv2.imwrite(img_temp.name, img)
img_temp.close()
return self.decode_file(img_temp.name)
finally:
os.unlink(img_temp.name)
def __call__(self, img):
# Decode barcodes in img using zbar
# https://github.com/ZBar/ZBar/blob/master/python/README
# https://github.com/herbyme/zbar/blob/master/python/examples/scan_image.py
scanner = zbar.ImageScanner()
height,width = img.shape[:2]
if 'uint8'!=img.dtype or 2!=len(img.shape):
debug_print('Convert to greyscale for zbar')
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
image = zbar.Image(width, height, 'Y800', img.tostring())
scanner.scan(image)
return [Barcode(str(s.type), unicode(s.data, 'utf8')) for s in image]
def resize(img, engine):
# Entire image at different fractions of original size
# TODO LH try more sharpening, equalisation, other stuff?
for sharpening in (0,1,2):
if sharpening>0:
img = _unsharpmask(img)
for f in [round(x * 0.01, 2) for x in xrange(100, 0, -5)]:
msg = 'resize: scaling factor [{0}] sharpening [{1}]'
msg = msg.format(f, sharpening)
debug_print(msg)
if 1==f:
i = img
else:
# Resize from the original image
i = cv2.resize(img, (0,0), fx=f, fy=f)
barcodes = engine(i)
if barcodes:
return msg, barcodes
return None
def filter(self, rects):
debug_print('[{0}] rectangles'.format(len(rects)))
for index,r in enumerate(rects):
debug_print(index, r)
if self.min_area:
rects = [r for r in rects if r.area>=self.min_area]
if self.max_area:
rects = [r for r in rects if r.area<=self.max_area]
debug_print('[{0}] rectangles after filtering by area'.format(len(rects)))
for index,r in enumerate(rects):
debug_print(index, r)
return rects
def _compute_candidates(self):
""" Returns a tuple ({'image_name':image,},
[(x,y,width,height),],
)
"""
# Based on http://stackoverflow.com/questions/9013703/how-to-find-the-location-of-red-region-in-an-image-using-matlab/9014569#9014569
debug_print('Computing candidate barcode areas')
resized = self._img
if self.WIDTH!=resized.shape[1]:
factor = float(self.WIDTH)/resized.shape[1]
debug_print('Resize {0}, factor of {1:.2}'.format(self.WIDTH, factor))
resized = cv2.resize(resized, (0,0), fx=factor, fy=factor)
grey = resized
if 'uint8'!=grey.dtype or 2!=len(grey.shape):
debug_print('Convert grey')
grey = cv2.cvtColor(grey, cv2.COLOR_BGR2GRAY)
debug_print('Equalize')
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
equalized = clahe.apply(grey)
# http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_gradients/py_gradients.html
debug_print('High-pass filter')
sobelx = cv2.Sobel(equalized, cv2.CV_16S, 1, 0, 3)
sobelx = np.abs(sobelx)
sobely = cv2.Sobel(equalized, cv2.CV_16S, 0, 1, 3)
sobely = np.abs(sobely)
gradient = equalized.copy()
gradient = cv2.convertScaleAbs(sobely-sobelx, gradient)
debug_print('Low-pass filter')
if True:
gradient = cv2.GaussianBlur(gradient, (3,3), 0)
else:
# Better than gaussian blur at preserving edges but slower
gradient = cv2.bilateralFilter(gradient,9,75,75) # TODO Parameter values?
debug_print('Threshold')
# All scans should have good, consistent lighting so apply a very high threshold
retval,thresh = cv2.threshold(gradient, 0xd0, 0xff, cv2.THRESH_BINARY)
debug_print('Morphology')
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, self.structuring_kernel)
closing = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=2)
debug_print('Contours')
cont_img = closing.copy()
contours,hierarchy = cv2.findContours(cont_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
working_images = { 'resized':resized,
'grey':grey,
'equalized':equalized,
'gradient':gradient,
'thresh':thresh,
'closing':closing,
}
candidates = [cv2.boundingRect(c) for c in contours]
candidates = [Rect(x, y, width, height) for x, y, width, height in candidates]
return (working_images, candidates)
def __call__(self, img):
with tempfile.NamedTemporaryFile(suffix='.tiff') as img_temp:
debug_print('Writing temp file [{0}] for Softek'.format(img_temp.name))
cv2.imwrite(img_temp.name, img)
return self.decode_file(img_temp.name)
def __call__(self, img):
# Decode data matrix barcodes in img using dmtxread
with tempfile.NamedTemporaryFile(suffix='.png') as img_temp:
debug_print('Writing temp file [{0}] for dmtxread'.format(img_temp.name))
cv2.imwrite(img_temp.name, img)
return self.decode_file(img_temp.name)
