Mask R CNNが実行できない

前提・実現したいこと

実現したいこと：Mask R CNNを実行したい

以下の記事を参考に再現しようと、記載されたものと同様の手順で記載されたコードの実行を行いました。
https://qiita.com/Yooooo/items/3798c3f87393217cc219

使用したライブラリのバージョンは補足情報の欄に記載の通りです。
Mask_RCNNのgithubのrequirementsに指定のあった
tensorflowとkerasのverのみダウングレードし、
h5pyは以下の記事と同様のエラーが出たためバージョンを下げてインストールし直しました。
https://qiita.com/Hiroki-Fujimoto/items/b078bfb680fb710c38c1

発生している問題・エラーメッセージ

実行すると下記のようなエラーが出ます。

Python
1InvalidArgumentError                      Traceback (most recent call last)
2~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\common_shapes.py in _call_cpp_shape_fn_impl(op, input_tensors_needed, input_tensors_as_shapes_needed, require_shape_fn)
3    653           graph_def_version, node_def_str, input_shapes, input_tensors,
4--> 654           input_tensors_as_shapes, status)
5    655   except errors.InvalidArgumentError as err:
6
7~\anaconda3\envs\mask_r_cnn_env\lib\contextlib.py in __exit__(self, type, value, traceback)
8     87             try:
9---> 88                 next(self.gen)
10     89             except StopIteration:
11
12~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()
13    465           compat.as_text(pywrap_tensorflow.TF_Message(status)),
14--> 466           pywrap_tensorflow.TF_GetCode(status))
15    467   finally:
16
17InvalidArgumentError: Dimension 1 in both shapes must be equal, but are 324 and 8 for 'Assign_682' (op: 'Assign') with input shapes: [1024,324], [1024,8].
18
19During handling of the above exception, another exception occurred:
20
21ValueError                                Traceback (most recent call last)
22<ipython-input-2-1b19d189f47c> in <module>
23     41 
24     42 #学習データの指定
25---> 43 model.load_weights("mask_rcnn_balloon.h5", by_name=True)
26     44 
27     45 #自分が表示したい画像を指定する
28
29~○○○\Mask_RCNN\mrcnn\model.py in load_weights(self, filepath, by_name, exclude)
30   2128 
31   2129         if by_name:
32-> 2130             saving.load_weights_from_hdf5_group_by_name(f, layers)
33   2131         else:
34   2132             saving.load_weights_from_hdf5_group(f, layers)
35
36~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\keras\engine\topology.py in load_weights_from_hdf5_group_by_name(f, layers)
37   3156                 weight_value_tuples.append((symbolic_weights[i],
38   3157                                             weight_values[i]))
39-> 3158     K.batch_set_value(weight_value_tuples)
40
41~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\keras\backend\tensorflow_backend.py in batch_set_value(tuples)
42   2186                 assign_placeholder = tf.placeholder(tf_dtype,
43   2187                                                     shape=value.shape)
44-> 2188                 assign_op = x.assign(assign_placeholder)
45   2189                 x._assign_placeholder = assign_placeholder
46   2190                 x._assign_op = assign_op
47
48~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\ops\variables.py in assign(self, value, use_locking)
49    525       the assignment has completed.
50    526     """
51--> 527     return state_ops.assign(self._variable, value, use_locking=use_locking)
52    528 
53    529   def assign_add(self, delta, use_locking=False):
54
55~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\ops\state_ops.py in assign(ref, value, validate_shape, use_locking, name)
56    272     return gen_state_ops.assign(
57    273         ref, value, use_locking=use_locking, name=name,
58--> 274         validate_shape=validate_shape)
59    275   return ref.assign(value)
60
61~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\ops\gen_state_ops.py in assign(ref, value, validate_shape, use_locking, name)
62     41   result = _op_def_lib.apply_op("Assign", ref=ref, value=value,
63     42                                 validate_shape=validate_shape,
64---> 43                                 use_locking=use_locking, name=name)
65     44   return result
66     45 
67
68~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\op_def_library.py in apply_op(self, op_type_name, name, **keywords)
69    765         op = g.create_op(op_type_name, inputs, output_types, name=scope,
70    766                          input_types=input_types, attrs=attr_protos,
71--> 767                          op_def=op_def)
72    768         if output_structure:
73    769           outputs = op.outputs
74
75~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\ops.py in create_op(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_shapes, compute_device)
76   2630                     original_op=self._default_original_op, op_def=op_def)
77   2631     if compute_shapes:
78-> 2632       set_shapes_for_outputs(ret)
79   2633     self._add_op(ret)
80   2634     self._record_op_seen_by_control_dependencies(ret)
81
82~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\ops.py in set_shapes_for_outputs(op)
83   1909       shape_func = _call_cpp_shape_fn_and_require_op
84   1910 
85-> 1911   shapes = shape_func(op)
86   1912   if shapes is None:
87   1913     raise RuntimeError(
88
89~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\ops.py in call_with_requiring(op)
90   1859 
91   1860   def call_with_requiring(op):
92-> 1861     return call_cpp_shape_fn(op, require_shape_fn=True)
93   1862 
94   1863   _call_cpp_shape_fn_and_require_op = call_with_requiring
95
96~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\common_shapes.py in call_cpp_shape_fn(op, require_shape_fn)
97    593     res = _call_cpp_shape_fn_impl(op, input_tensors_needed,
98    594                                   input_tensors_as_shapes_needed,
99--> 595                                   require_shape_fn)
100    596     if not isinstance(res, dict):
101    597       # Handles the case where _call_cpp_shape_fn_impl calls unknown_shape(op).
102
103~\anaconda3\envs\mask_r_cnn_env\lib\site-packages\tensorflow\python\framework\common_shapes.py in _call_cpp_shape_fn_impl(op, input_tensors_needed, input_tensors_as_shapes_needed, require_shape_fn)
104    657       missing_shape_fn = True
105    658     else:
106--> 659       raise ValueError(err.message)
107    660 
108    661   if missing_shape_fn:
109
110ValueError: Dimension 1 in both shapes must be equal, but are 324 and 8 for 'Assign_682' (op: 'Assign') with input shapes: [1024,324], [1024,8].