t1=tf.image.ssim_multiscale(tf.convert_to_tensor(x_test1[i]),tf.convert_to_tensor(ans1[i]),max_val=1).eval()
file1.write("\tMs-ssim:\t"+str(t1)+"\n")
avgs+=ssim1
avgm+=t1
print(t1)
print(i)
file1.write("MS-SSIM:\t"+str(avgm/100))
在计算ms-ssim时，它显示以下错误，但是似乎一切正确，有2个numpy数组，其中我们正在做MS-SSIM的比较， ans1 [i]和x_test1 [i]是numpy中的两个数组 我已经在tensorflow中使用相同的内置函数计算了psnr和ssim，该函数需要比较相同的numpy输入数组，但是相同的概念给MS-SSIM带来了以下错误
正在跟踪错误
0.5862568
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/client / session.py in _do_call(self, fn, *args)
1333 try:
-> 1334 return fn(*args)
1335 except errors.OpError as e:
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/client /session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1318 return self._call_tf_sessionrun(
-> 1319 options, feed_dict, fetch_list, target_list, run_metadata)
1320
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/client /session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1406 self._session, options, feed_dict, fetch_list, target_list,
-> 1407 run_metadata)
1408
**InvalidArgumentError: Computed output size would be negative: -2 [input_size: 8, effective_filter_size: 11, stride: 1]
[[{{node MS-SSIM_2/Scale4/depthwise_1}}]]**
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-150-850d3da2c004> in <module>()
12 t=tf.image.psnr(tf.convert_to_tensor(x_test1[i]),tf.convert_to_tensor(ans1[ i]),max_val=1).eval()
13 file1.write("\tPSNR:\t"+str(t))
---> 14 t1=tf.image.ssim_multiscale(tf.convert_to_tensor(x_test1[i]),tf.convert_to_ tensor(ans1[i]),max_val=2).eval()
15 file1.write("\tMs-ssim:\t"+str(t1)+"\n")
16 avgs+=ssim1
~/anaconda3/lib/python3.6/site-packages/tensorflow/python /framework/ops.py in eval(self, feed_dict, session)
693
694 """
--> 695 return _eval_using_default_session(self, feed_dict, self.graph, session)
696
697
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _eval_using_default_session(tensors, feed_dict, graph, session)
5179 "the tensor's graph is different from the session's "
5180 "graph.")
-> 5181 return session.run(tensors, feed_dict)
5182
5183
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
927 try:
928 result = self._run(None, fetches, feed_dict, options_ptr,
--> 929 run_metadata_ptr)
930 if run_metadata:
931 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1150 if final_fetches or final_targets or (handle and feed_dict_tensor):
1151 results = self._do_run(handle, final_targets, final_fetches,
-> 1152 feed_dict_tensor, options, run_metadata)
1153 else:
1154 results = []
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1326 if handle is None:
1327 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1328 run_metadata)
1329 else:
1330 return self._do_call(_prun_fn, handle, feeds, fetches)
~/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1346 pass
1347 message = error_interpolation.interpolate(message, self._graph)
-> 1348 raise type(e)(node_def, op, message)
1349
1350 def _extend_graph(self):
InvalidArgumentError: Computed output size would be negative: -2 [input_size: 8, effective_filter_size: 11, stride: 1]
[[node MS-SSIM_2/Scale4/depthwise_1 (defined at <ipython-input- 150-850d3da2c004>:14) ]]
Caused by op 'MS-SSIM_2/Scale4/depthwise_1', defined at:
File "/home/dipti/anaconda3/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/home/dipti/anaconda3/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/home/dipti/anaconda3/lib/python3.6/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/dipti/anaconda3/lib/python3.6/site-packages /ipykernel/kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "/home/dipti/anaconda3/lib/python3.6/site-packages /zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/tornado /stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/dipti/anaconda3/lib/python3.6/site-packages/ zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/z mq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/ ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /ipykernel/kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/ipykernel/k ernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/ipykernel /ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/ipykernel /zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/IPython /core/interactiveshell.py", line 2662, in run_cell
raw_cell, store_history, silent, shell_futures)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/IPython /core/interactiveshell.py", line 2785, in _run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/IPython/ core/interactiveshell.py", line 2901, in run_ast_nodes
if self.run_code(code, result):
File "/home/dipti/anaconda3/lib/python3.6/site-packages/ IPython/core/interactiveshell.py", line 2961, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-150-850d3da2c004>", line 14, in <module>
t1=tf.image.ssim_multiscale(tf.convert_to_tensor(x_test1[i]),tf.convert_to_ tensor(ans1[i]),max_val=2).eval()
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/ops/image_ops_impl.py", line 2867, in ssim_multiscale
ssim_per_channel, cs = _ssim_per_channel(*imgs, max_val=max_val)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/ops/image_ops_impl.py", line 2700, in _ssim_per_channel
luminance, cs = _ssim_helper(img1, img2, reducer, max_val, compensation)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/ops/image_ops_impl.py", line 2610, in _ssim_helper
mean1 = reducer(y)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/ops/image_ops_impl.py", line 2696, in reducer
y = nn.depthwise_conv2d(x, kernel, strides=[1, 1, 1, 1], p adding='VALID')
File "/home/dipti/anaconda3/lib/python3.6/site- packages/tensorflow/python/ops/nn_impl.py", line 522, in depthwise_conv2d
op=op)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 435, in with_space_to_batch
return new_op(input, None)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 591, in __call__
return self.call(inp, filter)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 425, in <lambda>
return lambda inp, _: op(inp, num_spatial_dims, padding)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/ops/nn_impl.py", line 514, in op
name=name)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/ops/gen_nn_ops.py", line 2251, in depthwise_conv2d_native
dilations=dilations, name=name)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/home/dipti/anaconda3/lib/python3.6/site-packages /tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3300, in create_op
op_def=op_def)
File "/home/dipti/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1801, in __init__
self._traceback = tf_stack.extract_stack()
**InvalidArgumentError (see above for traceback): Computed output size would be negative: -2 [input_size: 8, effective_filter_size: 11, stride: 1]
[[node MS-SSIM_2/Scale4/depthwise_1 (defined at <ipython-input-150-850d3da2c004>:14) ]]**
答案 0 :(得分：2)
问题似乎与减少空间维数后的断言有关。在_ssim_per_channel中，图像H和W相对于filter_size是asserted。而在ssim_multiscale中，downsampling 执行了len(power_factors)-1次。
有两种解决方法：
请确保filter_size足够小，以便在ssim_multiscale中进行下采样后为所有四个空间比例（不包括第一比例）计算ssim值。相反，请确保图像的H和W足够大，以致H/(2**4) and W/(2**4) >= filter_size。
由于下采样执行了len(power_factors)-1次，因此您也可以使用少于默认数量的_MSSSIM_WEIGHTS或power_factors，这意味着H/(2**(len(power_factors)-1)) and W/(2**(len(power_factors)-1)) >= filter_size。
field1 = tf.random.uniform(shape=[8, 64, 64, 1], minval=0, maxval=1)
field2 = tf.random.uniform(shape=[8, 64, 64, 1], minval=0, maxval=1)
#Use smaller filter_size
ms_ssim_score = tf.image.ssim_multiscale(img1=field1, img2=field2, max_val=1.0,
filter_size=4)
#Or use lesser number of power_factors
ms_ssim_score = tf.image.ssim_multiscale(img1=field1, img2=field2, max_val=1.0,
power_factors=(0.0448, 0.2856, 0.3001),
filter_size=11)
您可以尝试通过以下方式获得filter_size的合适值：
def suggest_filter_size(image1_batch,image2_batch,power_factors,filter_size):
shape1= image1_batch.shape[1:-1]
shape2= image2_batch.shape[1:-1]
if not(shape1[-3:-1][0]/(2**(len(power_factors)-1)) and shape2[-3:-1][0]/(2**(len(power_factors)-1)) >= filter_size):
H = tf.math.reduce_min((shape1,shape2))
suggested_filter_size = int(H/(2**(len(power_factors)-1)))
else:
suggested_filter_size = filter_size
return suggested_filter_size
#Example: suggest_filter_size(field1, field2,power_factors = (0.0448, 0.2856, 0.3001, 0.2363, 0.1333), filter_size = 11)
尝试一下：
H,W = 128,128
field1 = tf.random.uniform(shape=[8, H, W, 1], minval=0, maxval=1)
field2 = tf.random.uniform(shape=[8, H, W, 1], minval=0, maxval=1)
filter_size = 11 #default from tf.image.ssim_multiscale
power_factors = (0.0448, 0.2856, 0.3001, 0.2363, 0.1333) #default from tf.image.ssim_multiscale
#get a new filter_size from default values
new_filter_size = suggest_filter_size(field1, field2,power_factors,filter_size)
#tf.image.ssim_multiscale would now work with new_filter_size
ms_ssim_score = tf.image.ssim_multiscale(img1=field1, img2=field1, max_val=1.0,filter_size=new_filter_size)
答案 1 :(得分：1)
对于使用默认设置的MS-SSIM计算，您的输入数组很可能太小。
power_factors：每个秤的权重都是可迭代的。号码 所使用的比例是列表的长度。索引0是未缩放的 分辨率的权重和每个递增比例对应于图像 被2下采样。默认值为（0.0448，0.2856，0.3001，0.2363， 0.1333），这是原始论文中获得的值。
filter_size：默认值11（高斯滤波器的大小）
默认设置使用5个2x下采样操作，过滤器大小为11，因此对于较小的图像数组（例如64x64），通过3 2x下采样将其减小为8x8，小于默认内核大小11。
自己尝试一下：
N = 64 # change it to, say 512, then this works
a = np.random.randn(1, N, N, 1)
a = tf.convert_to_tensor(a)
max_val = np.max(np.reshape(a, [-1]))
result = tf.image.ssim_multiscale(a, a, max_val)