outputDir = '/tmp'
edgeThreshold = 13
ft = FASTex(edgeThreshold=edgeThreshold, nlevels=-1, minCompSize=4)
imgName = '/datagrid/personal/TextSpotter/evaluation-sets/bornDigital/img_100.png'
if len(sys.argv) > 1:
if sys.argv[1].endswith(".png") or sys.argv[1].endswith(".jpg"):
imgName = sys.argv[1]
img = cv2.imread(imgName, 0)
imgc = cv2.imread(imgName)
#print(out)
segmentations = ft.getCharSegmentations(img, outputDir, 'base')
print segmentations
for i in range(segmentations.shape[0]):
rectn = segmentations[i, :]
rectn[2] += rectn[0]
rectn[3] += rectn[1]
lines = ft.findTextLines(outputDir, 'base')
for i in range(lines.shape[0]):
line = lines[i]
lineSegm = ft.getNormalizedLine(i)
cv2.imshow("textLine", lineSegm)
cv2.waitKey(0)
# Verify image
if not os.path.isfile(args.image):
sys.exit("Image not found")
if not args.image.endswith(".png") and not args.image.endswith(".jpg"):
sys.exit("Not valid image")
settings = settings("config.json")
output_dir = settings['debug_dir']
ft = FASTex(edgeThreshold=13, nlevels=-1, minCompSize=4)
# Read image as numpy array
img = cv2.imread(args.image, 0) # load image in grayscale, i.e. 1 channel
img_o = cv2.imread(args.image)
img3 = cv2.imread(args.image)
# Get boxes of characters
# Elem in rows:: [bbox.x, bbox.y, bbox.width, bbox.height, keyPoint.pt.x, keyPoint.pt.y, octave, ?, duplicate, quality, [keypointsIds]]
segmentations = ft.getCharSegmentations(img, output_dir, 'base')
viz_location(img3, ft, segmentations, cumulative=True, max_chars=2000)
# drawCharMasks(img3, ft, segmentations, 100)
# drawCharBoxes(img3, segmentations, 100)
# cv2.imwrite(output_dir + "/mask.jpg", img3)
# Get boxes of text lines, should be a lot less than characters
# Elem in rows [bbox.x, bbox.y, bbox.width, bbox.height, rotated rectangle points (pt1.x, pt1.y, ... pt3.y) ]
txt_lines = ft.findTextLines(output_dir, 'txt_lines')
pass
