class Scg(object):
def __init__(self, scg_id, scg_content, truth, request_at, response_at):
self.id = scg_id
self.content = scg_content
self.response = truth
self.request_at = request_at
self.response_at = response_at
self.truth_obj = Payload(truth)
self.dummySample = Sample('data/inkml/65_alfonso.inkml')
self.w_h_ratio = 1.0 # initialize here, updated in replace_traces()
self.replace_traces()
self.dummySample.re_calculate_IMG_MINMAX()
def get_latex(self):
return self.truth_obj.latex
def replace_traces(self):
'''
replace the traces in dummySample with the one generated from scg_content
:return:
'''
strokes = scginkparser.parse_scg_ink_file(self.content, self.id)
#for st in strokes:
#print st
traces = {}
trace_id_int = 0
for st in strokes:
coords = np.zeros((2, len(st)))
idx = 0
for x_y in st:
coords[:, idx] = [float(x_y[0]), float(x_y[1])]
idx += 1
traces[trace_id_int] = Stroke(trace_id_int, coords)
trace_id_int += 1
# //Compute bounding box of the input expression
x_min, y_min, x_max, y_max = get_bounding_box(
traces) # bounding box for the whole math expression
# Just in case there is only one point or a sequence of points perfectly aligned with the x or y axis
if x_max == x_min: x_max = x_min + 1
if y_max == y_min: y_max = y_min + 1
self.w_h_ratio = float(x_max - x_min) / (y_max - y_min)
# Renormalize to height [0,10000] keeping the aspect ratio
H = 10000.0
W = H * (x_max - x_min) / (y_max - y_min)
for trace_key, trace_v in traces.iteritems():
trace_v.calc_coords_h10000(H, W, x_min, y_min, x_max, y_max)
self.dummySample.traces = traces
def save_image(self, path):
img, W, H = self.dummySample.render()
print 'save image to: ', path
misc.imsave(path, img)
def __init__(self, scg_id, scg_content, truth):
self.id = scg_id
self.content = scg_content
self.truth_obj = Payload(truth)
self.dummySample = Sample('data/inkml/65_alfonso.inkml')
self.w_h_ratio = 1.0 # initialize here, updated in replace_traces()
self.replace_traces()
self.dummySample.re_calculate_IMG_MINMAX()
def process_list(self, pair_file_name, latex_out):
'''
:param pair_file_name, set name: for example, 'train', one train.flist, the other train.idlist
:param outfile: for example, data/batch/train.lst
:param latex_out: 'data/batch/latex_list.txt'
:return:
'''
print "No dir specified, using default dir"
base_dir = 'data/batch/' # self.list_out_dir
flist_base_dir = self.list_out_dir
prefix = 'im2latex_'
infile = flist_base_dir + pair_file_name + '.flist' # data/batch/pickle/train.flist
outfile = base_dir + prefix + pair_file_name + '.lst' # data/batch/im2latex_train.lst
scg_id_list_file = flist_base_dir + pair_file_name + '.idlist'
print 'input: ', infile
print 'output: ', outfile
with open(infile, 'rb') as fin:
flist = pickle.load(fin)
with open(scg_id_list_file, 'rb') as fin:
idlist = pickle.load(fin)
with codecs.open(outfile, 'w', 'utf-8') as f_out:
for file_path in flist:
print 'file: ', file_path
# process one file
sample = Sample(file_path)
latex = sample.latex
#output latex
latex_out.write(latex[1:-1] + '\n')
#get filename without extension
png_name = self.get_filename_noext(file_path)
line = str(self.latex_index) + ' ' + png_name + ' ' + 'basic\n'
f_out.write(line)
#output image
img, W, H = sample.render()
misc.imsave(png_dir + png_name + '.png', img)
self.latex_index += 1
for id in idlist:
print 'id: ', id
logging.info('processing %d scg record', id)
scg = self.scgs[id]
latex = scg.get_latex()
# output latex
latex_out.write(latex + '\n')
# get filename without extension
png_name = str(id)
line = str(self.latex_index) + ' ' + png_name + ' ' + 'basic\n'
f_out.write(line)
# output image (this task is done when dividing the list into 3 groups
#scg.save_image(png_dir + png_name + '.png')
self.latex_index += 1
def inkml2png(self):
'''
for all inkml files in data/batch/inkml folder, generate its png image and save it
to data/batch/formula_images/ folder
It is used if different resolution images need to be generated for mhr performance evaluation.
:return:
'''
files, files_nolatex = self.all_inkml_files()
for file_path in files:
print 'file: ', file_path
# process one file
sample = Sample(file_path)
# get filename without extension
png_name = self.get_filename_noext(file_path)
# output image
img, W, H = sample.render()
misc.imsave(png_dir + png_name + '.png', img)
def all_inkml_files(self):
'''
:return: files, files_nolatex
'''
files = []
files_nolatex = []
for root, dirnames, filenames in os.walk(self.inkml_file_path, followlinks=True):
for filename in fnmatch.filter(filenames, '*.inkml'):
tmp_path = os.path.join(root, filename)
print tmp_path
sample = Sample(tmp_path)
if hasattr(sample, 'latex') and self.check_latex_length(sample): #latex has been stripped
#print 'latex: ', tmp_path
files.append(tmp_path)
else:
files_nolatex.append(tmp_path)
return files, files_nolatex
coords[:, idx] = [float(x_y[0]), float(x_y[1])]
idx += 1
traces[trace_id_int] = Stroke(trace_id_int, coords)
trace_id_int += 1
# //Compute bounding box of the input expression
x_min, y_min, x_max, y_max = get_bounding_box(traces) # bounding box for the whole math expression
# Just in case there is only one point or a sequence of points perfectly aligned with the x or y axis
if x_max == x_min: x_max = x_min + 1;
if y_max == y_min: y_max = y_min + 1;
# Renormalize to height [0,10000] keeping the aspect ratio
H = 10000.0
W = H * (x_max - x_min) / (y_max - y_min)
for trace_key, trace_v in traces.iteritems():
trace_v.calc_coords_h10000(H, W, x_min, y_min, x_max, y_max)
for trace_key, trace_v in traces.iteritems():
print trace_key, trace_v
rx, ry, rs, rt = trace_v.get_bounding_box_h10000()
print rx, ry, rs, rt
dummy_sample = Sample('data/inkml/65_alfonso.inkml')
dummy_sample.traces = traces
img, W, H = dummy_sample.render()
print 'save image to temp/all.png: '
misc.imsave('temp/all.png', img)
def setUp(self):
idd = Sample('data/inkml/65_alfonso.inkml')
self.stroke0 = idd.traces[0]
self.stroke1 = idd.traces[1]
self.stroke2 = idd.traces[2]
self.stroke9 = idd.traces[9]
def test_loading_inkml(self):
iml = Sample('data/inkml/D_357_HMA095045.inkml')
print 'latex: ', iml.latex
def setUp(self):
self.idd = Sample('data/inkml/65_alfonso.inkml')
self.stroke0 = self.idd.traces[0]
self.stroke1 = self.idd.traces[1]
self.stroke2 = self.idd.traces[2]
prev = self.idd.traces[1]
class TestSample(TestCase):
def setUp(self):
self.idd = Sample('data/inkml/65_alfonso.inkml')
self.stroke0 = self.idd.traces[0]
self.stroke1 = self.idd.traces[1]
self.stroke2 = self.idd.traces[2]
prev = self.idd.traces[1]
def test_inkml_loading(self):
print 'loading inkml'
print 'latex: ', self.idd.latex
def test_loading_inkml(self):
iml = Sample('data/inkml/D_357_HMA095045.inkml')
print 'latex: ', iml.latex
def test_get_bounding_box_h1000(self):
self.assertEqual((0, 0, 69622, 10000),
(self.idd.ox, self.idd.oy, self.idd.os, self.idd.ot))
def test_getAVGstroke_size(self):
avgW, avgH = self.idd.getAVGstroke_size()
targetW = 6075.5
targetH = 4320.8999
self.assertTrue(abs(avgW - targetW) < 1.0 / 2)
self.assertTrue(abs(avgH - targetH) < 1.0 / 2)
print avgW, avgH
def test_nStrokes(self):
ns = self.idd.nStrokes()
self.assertEquals(10, ns)
def test_detRefSymbol(self):
'''
expect (5764, 5063)
:return:
'''
RX, RY = self.idd.detRefSymbol()
print RX, RY
self.assertEquals((5764, 5063), (RX, RY))
def test_stroke_aspect_area(self):
# expect 9623, 6794, 1.41639686, 65378662
i = 0
ancho, alto, aspectratio, area = self.idd.stroke_aspect_area(i)
print ancho, alto, aspectratio, area
self.assertEquals(9623, ancho)
self.assertEquals(6794, alto)
self.assertEquals(65378662, area)
self.assertAlmostEqual(1.41639686, aspectratio)
def test_median_vmedx(self):
vmedx = [9623, 6039, 7360, 7360, 6982, 4152, 3586, 3586, 6793, 5284]
print vmedx
vmedx.sort()
print vmedx
l = len(vmedx)
print vmedx[l / 2]
self.assertEquals(6793, vmedx[l / 2])
import numpy
medx = numpy.median(vmedx) # average of 6039 and 6793
self.assertEquals(6416.0, medx)
def test_stroke_distance1(self):
self.idd.render()
# distance between stroke 0 and stroke 2. the distance is before the normalization
dmin = self.idd.stroke_distance(0, 2)
self.assertEqual(7902.4310183639063, dmin)
print dmin
def test_stroke_distance2(self):
img, W, H = self.idd.render()
dmin = self.idd.stroke_distance(4, 7)
print dmin
def test_find_closest_pair(self):
dmin, p1, p2 = self.idd.find_closest_pair(0, 2)
print dmin
self.assertAlmostEqual(7902.43115, dmin, 3)
self.assertEqual((9433, 9056), p1)
self.assertEqual((16037, 4716), p2)
def test_render(self):
'''
testing rendering image from inkml file
save image at temp/all.png
:return:
'''
img, W, H = self.idd.render()
print 'save image to temp/all.png: '
misc.imsave('temp/all.png', img)
print img[15, 9]
print W, H
#self.assertEqual(255, img[15, 9])
#self.assertEqual((1792, 266), (W, H))
def test_linea(self):
W, H = 1792, 266
img = np.ones((H, W), dtype=int) * 255
self.idd.pix_stk = np.ones((H, W), dtype=int) * (-1)
pa = (19.4867649, 149.881516)
pb = (5, 145.043594)
self.idd.linea(img, pa, pb, 0)
print np.where(img == 0)
print img
self.assertEqual(0, img[145, 5])
self.assertEqual(0, img[150, 20])
def test_compute_strokes_distances(self):
RX = 5764
RY = 5063
img, W, H = self.idd.render()
stk_dis = self.idd.compute_strokes_distances(RX, RY)
print '(x, y): (1169, 119): ', img[119][1169], self.idd.pix_stk[119][
1169]
self.assertEqual(0, img[119][1169])
self.assertEqual(5, self.idd.pix_stk[119][1169])
print stk_dis
def test_get_close_strokes(self):
self.idd.detRefSymbol()
self.idd.render()
self.idd.compute_strokes_distances(self.idd.RX, self.idd.RY)
L = []
self.idd.get_close_strokes(7, L, 0.69474973)
self.assertEqual((6, 5), (L[0], L[1]))
print L
L = []
self.idd.get_close_strokes(6, L, 0.69474973)
self.assertEqual(5, L[0])
L = []
self.idd.get_close_strokes(8, L, 0.69474973)
self.assertEqual((7, 6), (L[0], L[1]))