tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [1,256,48,64] vs. [1,256,47,63]

[faheemullah]

Hello there!
I'm running the demo.ipynb from rt-mrcnn-master/samples.
https://github.com/noxouille/rt-mrcnn
I converted it to demo.py. I commented this statement #get_ipython().run_line_magic('matplotlib', 'inline').
When I run it ($python demo.py), it gives the following error.

tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [1,256,48,64] vs. [1,256,47,63]

Now I don't understand what to do. Any help please. For more details I paste the whole messages below.
Thanks

(test) *****@*-Server:~/Projects/rt-mrcnn-master/samples$ python demo.py
Using TensorFlow backend.

Configurations:
BACKBONE resnet101
BACKBONE_STRIDES [4, 8, 16, 32, 64]
BATCH_SIZE 1
BBOX_STD_DEV [0.1 0.1 0.2 0.2]
COMPUTE_BACKBONE_SHAPE None
DETECTION_MAX_INSTANCES 100
DETECTION_MIN_CONFIDENCE 0.7
DETECTION_NMS_THRESHOLD 0.3
FPN_CLASSIF_FC_LAYERS_SIZE 1024
GPU_COUNT 1
GRADIENT_CLIP_NORM 5.0
IMAGES_PER_GPU 1
IMAGE_CHANNEL_COUNT 3
IMAGE_MAX_DIM 1024
IMAGE_META_SIZE 93
IMAGE_MIN_DIM 800
IMAGE_MIN_SCALE 0
IMAGE_RESIZE_MODE none
IMAGE_SHAPE [1024 1024 3]
LEARNING_MOMENTUM 0.9
LEARNING_RATE 0.001
LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0}
MASK_POOL_SIZE 14
MASK_SHAPE [28, 28]
MAX_GT_INSTANCES 100
MEAN_PIXEL [123.7 116.8 103.9]
MINI_MASK_SHAPE (56, 56)
NAME coco
NUM_CLASSES 81
POOL_SIZE 7
POST_NMS_ROIS_INFERENCE 1000
POST_NMS_ROIS_TRAINING 2000
PRE_NMS_LIMIT 6000
ROI_POSITIVE_RATIO 0.33
RPN_ANCHOR_RATIOS [0.5, 1, 2]
RPN_ANCHOR_SCALES (32, 64, 128, 256, 512)
RPN_ANCHOR_STRIDE 1
RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2]
RPN_NMS_THRESHOLD 0.7
RPN_TRAIN_ANCHORS_PER_IMAGE 256
STEPS_PER_EPOCH 1000
TOP_DOWN_PYRAMID_SIZE 256
TRAIN_BN False
TRAIN_ROIS_PER_IMAGE 200
USE_MINI_MASK True
USE_RPN_ROIS True
VALIDATION_STEPS 50
WEIGHT_DECAY 0.0001

WARNING:tensorflow:From /home/faheem/.conda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING:tensorflow:From /home/faheem/.conda/envs/test/lib/python3.6/site-packages/mask_rcnn-2.1-py3.6.egg/mrcnn/model.py:772: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
2019-05-23 14:21:14.601297: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA
2019-05-23 14:21:14.623461: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3500000000 Hz
2019-05-23 14:21:14.624053: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x557c7f67bbb0 executing computations on platform Host. Devices:
2019-05-23 14:21:14.624102: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): ,
2019-05-23 14:21:15.355519: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x557c7f7613d0 executing computations on platform CUDA. Devices:
2019-05-23 14:21:15.355558: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): GeForce GTX 1080 Ti, Compute Capability 6.1
2019-05-23 14:21:15.355568: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (1): GeForce GTX 1080 Ti, Compute Capability 6.1
2019-05-23 14:21:15.355576: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (2): GeForce GTX 1080 Ti, Compute Capability 6.1
2019-05-23 14:21:15.355584: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (3): GeForce GTX 1080 Ti, Compute Capability 6.1
2019-05-23 14:21:15.356344: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:19:00.0
totalMemory: 10.92GiB freeMemory: 10.76GiB
2019-05-23 14:21:15.356526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 1 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:1a:00.0
totalMemory: 10.92GiB freeMemory: 10.76GiB
2019-05-23 14:21:15.356698: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 2 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:67:00.0
totalMemory: 10.92GiB freeMemory: 10.76GiB
2019-05-23 14:21:15.356865: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 3 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:68:00.0
totalMemory: 10.92GiB freeMemory: 10.70GiB
2019-05-23 14:21:15.364666: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0, 1, 2, 3
2019-05-23 14:21:15.368640: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-05-23 14:21:15.368659: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0 1 2 3
2019-05-23 14:21:15.368664: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N Y Y Y
2019-05-23 14:21:15.368668: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 1: Y N Y Y
2019-05-23 14:21:15.368672: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 2: Y Y N Y
2019-05-23 14:21:15.368675: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 3: Y Y Y N
2019-05-23 14:21:15.369197: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10468 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:19:00.0, compute capability: 6.1)
2019-05-23 14:21:15.369500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 10468 MB memory) -> physical GPU (device: 1, name: GeForce GTX 1080 Ti, pci bus id: 0000:1a:00.0, compute capability: 6.1)
2019-05-23 14:21:15.369730: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:2 with 10468 MB memory) -> physical GPU (device: 2, name: GeForce GTX 1080 Ti, pci bus id: 0000:67:00.0, compute capability: 6.1)
2019-05-23 14:21:15.370062: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:3 with 10407 MB memory) -> physical GPU (device: 3, name: GeForce GTX 1080 Ti, pci bus id: 0000:68:00.0, compute capability: 6.1)
Processing 1 images
image shape: (375, 500, 3) min: 0.00000 max: 255.00000 uint8
molded_images shape: (1, 375, 500, 3) min: -123.70000 max: 151.10000 float64
image_metas shape: (1, 93) min: 0.00000 max: 500.00000 int64
anchors shape: (1, 47157, 4) min: -0.96802 max: 1.82096 float32
2019-05-23 14:21:19.397662: I tensorflow/stream_executor/dso_loader.cc:152] successfully opened CUDA library libcublas.so.10.0 locally
Traceback (most recent call last):
File "demo.py", line 131, in
results = model.detect([image], verbose=1)
File "/home/faheem/.conda/envs/test/lib/python3.6/site-packages/mask_rcnn-2.1-py3.6.egg/mrcnn/model.py", line 2524, in detect
File "/home/faheem/.conda/envs/test/lib/python3.6/site-packages/keras/engine/training.py", line 1169, in predict
steps=steps)
File "/home/faheem/.conda/envs/test/lib/python3.6/site-packages/keras/engine/training_arrays.py", line 294, in predict_loop
batch_outs = f(ins_batch)
File "/home/faheem/.conda/envs/test/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 2715, in call
return self._call(inputs)
File "/home/faheem/.conda/envs/test/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 2675, in _call
fetched = self._callable_fn(*array_vals)
File "/home/faheem/.conda/envs/test/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1439, in call
run_metadata_ptr)
File "/home/faheem/.conda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 528, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [1,256,48,64] vs. [1,256,47,63]
[[{{node fpn_p3add/add}}]]
[[{{node mrcnn_detection/map/TensorArrayUnstack/range}}]]