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support for python3 #80

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10 changes: 5 additions & 5 deletions detect.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,7 @@ def detect(im, param_vals):
y_vals = []
for scaled_im in scaled_ims:
feed_dict = {x: numpy.stack([scaled_im])}
feed_dict.update(dict(zip(params, param_vals)))
feed_dict.update(dict(list(zip(params, param_vals))))
y_vals.append(sess.run(y, feed_dict=feed_dict))

# Interpret the results in terms of bounding boxes in the input image.
Expand Down Expand Up @@ -141,7 +141,7 @@ def _group_overlapping_rectangles(matches):
num_groups += 1

groups = collections.defaultdict(list)
for idx, group in match_to_group.items():
for idx, group in list(match_to_group.items()):
groups[group].append(matches[idx])

return groups
Expand All @@ -159,7 +159,7 @@ def post_process(matches):
"""
groups = _group_overlapping_rectangles(matches)

for group_matches in groups.values():
for group_matches in list(groups.values()):
mins = numpy.stack(numpy.array(m[0]) for m in group_matches)
maxs = numpy.stack(numpy.array(m[1]) for m in group_matches)
present_probs = numpy.array([m[2] for m in group_matches])
Expand All @@ -184,8 +184,8 @@ def letter_probs_to_code(letter_probs):

for pt1, pt2, present_prob, letter_probs in post_process(
detect(im_gray, param_vals)):
pt1 = tuple(reversed(map(int, pt1)))
pt2 = tuple(reversed(map(int, pt2)))
pt1 = tuple(reversed(list(map(int, pt1))))
pt2 = tuple(reversed(list(map(int, pt2))))

code = letter_probs_to_code(letter_probs)

Expand Down
6 changes: 3 additions & 3 deletions extractbgs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,10 +62,10 @@ def extract_backgrounds(archive_name):
t = tarfile.open(name=archive_name)

def members():
m = t.next()
m = next(t)
while m:
yield m
m = t.next()
m = next(t)
index = 0
for m in members():
if not m.name.endswith(".jpg"):
Expand All @@ -85,7 +85,7 @@ def members():
if im.shape[0] > 256:
im = cv2.resize(im, (256, 256))
fname = "bgs/{:08}.jpg".format(index)
print fname
print(fname)
rc = cv2.imwrite(fname, im)
if not rc:
raise Exception("Failed to write file {}".format(fname))
Expand Down
2 changes: 1 addition & 1 deletion gen.py
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Original file line number Diff line number Diff line change
Expand Up @@ -287,6 +287,6 @@ def generate_ims():
for img_idx, (im, c, p) in enumerate(im_gen):
fname = "test/{:08d}_{}_{}.png".format(img_idx, c,
"1" if p else "0")
print fname
print(fname)
cv2.imwrite(fname, im * 255.)

14 changes: 7 additions & 7 deletions train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,7 +69,7 @@ def read_data(img_glob):


def unzip(b):
xs, ys = zip(*b)
xs, ys = list(zip(*b))
xs = numpy.array(xs)
ys = numpy.array(ys)
return xs, ys
Expand Down Expand Up @@ -202,11 +202,11 @@ def do_report():
r[3] < 0.5)))
r_short = (r[0][:190], r[1][:190], r[2][:190], r[3][:190])
for b, c, pb, pc in zip(*r_short):
print "{} {} <-> {} {}".format(vec_to_plate(c), pc,
vec_to_plate(b), float(pb))
print("{} {} <-> {} {}".format(vec_to_plate(c), pc,
vec_to_plate(b), float(pb)))
num_p_correct = numpy.sum(r[2] == r[3])

print ("B{:3d} {:2.02f}% {:02.02f}% loss: {} "
print(("B{:3d} {:2.02f}% {:02.02f}% loss: {} "
"(digits: {}, presence: {}) |{}|").format(
batch_idx,
100. * num_correct / (len(r[0])),
Expand All @@ -215,7 +215,7 @@ def do_report():
r[4],
r[5],
"".join("X "[numpy.array_equal(b, c) or (not pb and not pc)]
for b, c, pb, pc in zip(*r_short)))
for b, c, pb, pc in zip(*r_short))))

def do_batch():
sess.run(train_step,
Expand All @@ -240,9 +240,9 @@ def do_batch():
if batch_idx % report_steps == 0:
batch_time = time.time()
if last_batch_idx != batch_idx:
print "time for 60 batches {}".format(
print("time for 60 batches {}".format(
60 * (last_batch_time - batch_time) /
(last_batch_idx - batch_idx))
(last_batch_idx - batch_idx)))
last_batch_idx = batch_idx
last_batch_time = batch_time

Expand Down