| /external/opencv/cv/src/ |
| cvmoments.cpp | 43 /* The function calculates center of gravity and central second order moments */
45 icvCompleteMomentState( CvMoments* moments )
50 assert( moments != 0 );
51 moments->inv_sqrt_m00 = 0;
53 if( fabs(moments->m00) > DBL_EPSILON )
55 double inv_m00 = 1. / moments->m00;
56 cx = moments->m10 * inv_m00;
57 cy = moments->m01 * inv_m00;
58 moments->inv_sqrt_m00 = sqrt( fabs(inv_m00) );
62 mu20 = moments->m20 - moments->m10 * cx
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| cvcamshift.cpp | 64 CvMoments moments; local
75 moments.m00 = moments.m10 = moments.m01 = 0;
101 CV_CALL( cvMoments( &cur_win, &moments ));
104 if( fabs(moments.m00) < DBL_EPSILON )
107 inv_m00 = moments.inv_sqrt_m00*moments.inv_sqrt_m00;
108 dx = cvRound( moments.m10 * inv_m00 - windowIn.width*0.5 );
109 dy = cvRound( moments.m01 * inv_m00 - windowIn.height*0.5 )
171 CvMoments moments; local
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| cvmatchcontours.cpp | 61 CvMoments moments; local
76 /* first moments calculation */
77 CV_CALL( cvMoments( contour1, &moments ));
79 /* Hu moments calculation */
80 CV_CALL( cvGetHuMoments( &moments, &huMoments ));
91 /* second moments calculation */
92 CV_CALL( cvMoments( contour2, &moments ));
94 /* Hu moments calculation */
95 CV_CALL( cvGetHuMoments( &moments, &huMoments ));
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| parameterized_truncated_normal_op_test.py | 54 """Calculates the truncated normal moments.
84 moments = [0.0] * (max_moment + 1)
87 for k in range(len(moments)):
88 moments[k] += value
90 for i in range(len(moments)):
91 moments[i] /= len(samples)
92 return moments
109 # Stop at moment 10 to avoid numerical errors in the theoretical moments.
123 moments = calculate_moments(samples, self.max_moment)
126 for i in range(1, len(moments))
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| /external/tensorflow/tensorflow/core/lib/random/ |
| random_distributions_test.cc | 62 // of all statistical moments are all below z_limit.
68 // max_moments: the largest moments of the uniform distribution to be tested;
79 std::vector<double> moments(max_moments + 1);
80 double* const moments_data = &moments[0];
91 // moments[i] store the i-th order measured moments.
100 // normalize the moments
102 moments[i] /= moments_sample_count[i];
126 fabs((moments[i] - moments_i_mean) / sqrt(total_variance));
132 << " measured moments: " << moments[i
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| /external/tensorflow/tensorflow/contrib/nn/python/ops/ |
| alpha_dropout_test.py | 39 t_mean, t_std = nn_impl.moments(t, axes=[0, 1])
40 output_mean, output_std = nn_impl.moments(output, axes=[0, 1])
|
| /external/tensorflow/tensorflow/python/kernel_tests/random/ |
| random_poisson_test.py | 37 """This is a large test due to the moments computation taking some time."""
57 tf_logging.warn("Cannot test moments: %s", e)
59 # The moments test is a z-value test. This is the largest z-value
69 moments = [0] * (max_moment + 1)
78 moments[i] += moment
82 moments[i] /= moments_sample_count[i]
102 (moments[i] - moments_i_mean) / np.sqrt(total_variance))
|
| random_gamma_test.py | 37 """This is a medium test due to the moments computation taking some time."""
66 tf_logging.warn("Cannot test moments: %s" % e)
71 # z-tests of all statistical moments are all below z_limit.
73 # max_moments: the largest moments of the distribution to be tested
79 # The moments test is a z-value test. This is the largest z-value
90 # Gamma moments only defined for values less than the scale param.
94 moments = [0] * (max_moment + 1)
103 moments[i] += moment
107 moments[i] /= moments_sample_count[i]
132 (moments[i] - moments_i_mean) / math.sqrt(total_variance)
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| normalization.py | 106 # the moments and the batch normalization.
152 # Calculate the moments (instance activations).
153 mean, variance = nn.moments(inputs, moments_axes, keep_dims=True)
|
| layers.py | 240 it would accumulate the statistics of the moments into `moving_mean` and
506 it would accumulate the statistics of the moments into `moving_mean` and
694 # the moments and the batch normalization.
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| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| virtual_batchnorm_test.py | 53 """Check that `_statistics` gives the same result as `nn.moments`."""
59 mom_mean, mom_var = nn.moments(tensors, axes)
70 """Check that `_virtual_statistics` gives same result as `nn.moments`."""
79 # Get `nn.moments` on the full batch.
82 mom_mean, mom_variance = nn.moments(full_batch, reduction_axes)
|
| /external/opencv/cv/include/ |
| cv.h | 347 /* Calculates all spatial and central moments up to the 3rd order */
348 CVAPI(void) cvMoments( const CvArr* arr, CvMoments* moments, int binary CV_DEFAULT(0));
350 /* Retrieve particular spatial, central or normalized central moments */
351 CVAPI(double) cvGetSpatialMoment( CvMoments* moments, int x_order, int y_order );
352 CVAPI(double) cvGetCentralMoment( CvMoments* moments, int x_order, int y_order );
353 CVAPI(double) cvGetNormalizedCentralMoment( CvMoments* moments,
356 /* Calculates 7 Hu's invariants from precalculated spatial and central moments */
357 CVAPI(void) cvGetHuMoments( CvMoments* moments, CvHuMoments* hu_moments );
757 /* Compares two contours by matching their moments */
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| cvcompat.h | 344 #define cvContourMoments( contour, moments ) \
345 cvMoments( contour, moments, 0 )
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| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| sliced_wasserstein_impl.py | 127 mean, variance = nn.moments(patches, [1, 2, 3], keep_dims=True)
|
| /external/ImageMagick/MagickCore/ |
| statistic.c | 1784 *moments; local
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| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| optimizers.py | 190 moments = [K.zeros(shape) for shape in shapes]
191 self.weights = [self.iterations] + moments
192 for p, g, m in zip(params, grads, moments):
|
| /external/tensorflow/tensorflow/python/ops/ |
| batch_norm_benchmark.py | 99 mean, variance = nn_impl.moments(tensor, axes, keep_dims=keep_dims)
|
| nn_fused_batchnorm_test.py | 100 mean, var = nn_impl.moments(
136 # This is for Bessel's correction. tf.nn.moments uses n, instead of n-1, as
|
| nn_impl.py | 631 name: Name used to scope the operations that compute the moments.
651 @tf_export("nn.moments")
652 def moments( function
666 When using these moments for batch normalization (see
678 name: Name used to scope the operations that compute the moments.
679 keep_dims: produce moments with the same dimensionality as the input.
684 with ops.name_scope(name, "moments", [x, axes]):
718 keep_dims: Produce moments with the same dimensionality as the input.
728 # Unlike moments(), this just uses a simpler two-pass method.
730 # See comment in moments() WRT precision; it applies here too
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| nn_batchnorm_test.py | 250 """Test for tf.nn.moments(..., keep_dims=True / False).
325 """Test for a variety of shapes and moments.
445 # Method to compute moments of `x` wrt `axes`.
452 return nn_impl.moments(x, axes, keep_dims=keep_dims)
475 # Check that the moments are correct.
506 # Check that the moments are correct.
569 print("Moments %s gradient err vs input %d = %g" % (from_y, i, err))
589 MomentsTest are executed, but with calls to tf.nn.moments()
|
| nn_test.py | [all...] |
| /external/ImageMagick/www/api/ |
| statistic.php | 270 <p>GetImageMoments() returns the normalized moments of one or more image channels.</p>
|
| /external/ImageMagick/Magick++/lib/Magick++/ |
| Image.h | [all...] |
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| math_utils.py | 477 Since Cauchy distributions do not have moments, entropy matching provides one
609 Moments = collections.namedtuple("Moments", ["mean", "variance"])
625 # InputStatisticsFromMiniBatch, these moments are
636 # InputStatisticsFromMiniBatch, these moments
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| /external/tensorflow/tensorflow/python/layers/ |
| normalization.py | 436 # initialized with this batch's moments.
563 mean, variance = nn.moments(inputs, reduction_axes, keep_dims=keep_dims)
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