diff --git a/detect.py b/detect.py
index 7182fc6..6d9d1e1 100755
--- a/detect.py
+++ b/detect.py
@@ -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.
@@ -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
@@ -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])
@@ -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)
 
diff --git a/extractbgs.py b/extractbgs.py
index 6d1461b..e017da7 100755
--- a/extractbgs.py
+++ b/extractbgs.py
@@ -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"):
@@ -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))
diff --git a/gen.py b/gen.py
index 75660d0..c1c688c 100755
--- a/gen.py
+++ b/gen.py
@@ -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.)
 
diff --git a/train.py b/train.py
index 162a8bd..c4c8240 100755
--- a/train.py
+++ b/train.py
@@ -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
@@ -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])),
@@ -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,
@@ -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