| /external/webrtc/webrtc/modules/video_coding/ |
| qm_select.cc | 81 // Spatial measure: take average of 3 prediction errors.
176 down_action_history_[i].spatial = kNoChangeSpatial;
301 // 2) The possible down-sampling actions are: spatial by 1/2x1/2, 3/4x3/4;
303 // 3) The action for going back up is the reverse of last (spatial or temporal)
306 // 4) The total amount of down-sampling (spatial and/or temporal) from the
340 if (down_action_history_[0].spatial != kNoChangeSpatial ||
365 action_.spatial = kNoChangeSpatial;
398 // Use base layer frame rate for temporal layers: this will favor spatial.
428 float fac_width = kFactorWidthSpatial[down_action_history_[0].spatial];
429 float fac_height = kFactorHeightSpatial[down_action_history_[0].spatial];
[all...] |
| qm_select.h | 96 ResolutionAction() : spatial(kNoChangeSpatial), temporal(kNoChangeTemporal) {}
97 SpatialAction spatial; member in struct:webrtc::ResolutionAction
101 // Down-sampling factors for spatial (width and height), and temporal.
132 // Compute spatial texture magnitude and level.
133 // Spatial texture is a spatial prediction error measure.
137 // NFD is normalized frame difference (normalized by spatial variance).
213 // Output: the spatial and/or temporal scale change.
260 // Covert 2 stages of 3/4 (=9/16) spatial decimation to 1/2.
263 // Returns true if the new frame sizes, under the selected spatial action
[all...] |
| /external/tensorflow/tensorflow/stream_executor/ |
| dnn.cc | 284 string spatial; local
286 port::Appendf(&spatial, "%lld ", spatial_size()[i]);
289 "{count: %lld feature_map_count: %lld spatial: %s "
291 count(), feature_map_count(), spatial.c_str(), value_min_, value_max_,
302 string spatial = "s"; local
304 port::Appendf(&spatial, "%lld ", spatial_size()[i]);
317 return absl::StrCat(spatial, depth, batch, suffix);
319 return absl::StrCat(spatial, batch, depth, suffix);
321 return absl::StrCat(batch, spatial, depth, suffix);
323 return absl::StrCat(batch, depth, spatial, suffix)
417 string spatial = "s"; local
[all...] |
| /cts/apps/CameraITS/build/ |
| envsetup.sh | 34 for M in numpy PIL matplotlib scipy.stats scipy.spatial
|
| /external/tensorflow/tensorflow/core/util/ |
| tensor_format_test.cc | 50 int spatial(int spatial_index) const { return spatial_dim[spatial_index]; } function in struct:tensorflow::TensorDimMap
62 int spatial(int spatial_index) const { return spatial_dim[spatial_index]; } function in struct:tensorflow::FilterDimMap
76 // These arrays are indexed by the number of spatial dimensions in the format.
183 EXPECT_EQ(GetTensorSpatialDimIndex(num_dims, format, i), tdm.spatial(i));
185 tdm.spatial(i));
200 fdm.spatial(i));
202 fdm.spatial(i));
|
| tensor_format.h | 109 // Returns the number of spatial dims of a tensor of rank 'num_dims' and tensor
120 // Note: the VECT_W is not counted as an independent spatial dim here,
134 // Returns the rank of a tensor with 'num_spatial_dims' spatial dimensions and
150 // Returns the rank of a tensor with 'num_spatial_dims' spatial dimensions and
297 // 'C' (channels), 'H' (height), 'W' (width), or a numbered spatial dimension:
366 // numbered spatial dimension: '0', .. (NUM_SPATIAL_DIMS-1).
505 // FORMAT_NHWC: (N, spatial, C); rank = spatial.size() + 2
506 // FORMAT_NCHW: (N, C, spatial); rank = spatial.size() +
[all...] |
| /external/libmpeg2/common/arm/ |
| ideint_spatial_filter_a9.s | 24 @* This file contains definitions of routines for spatial filter
40 @* @brief Performs spatial filtering
43 @* This functions performs edge adaptive spatial filtering on a 8x8 block
|
| ideint_cac_a9.s | 24 @* This file contains definitions of routines for spatial filter
|
| /cts/apps/CameraITS/tests/sensor_fusion/ |
| test_sensor_fusion.py | 32 import scipy.spatial
182 dist = scipy.spatial.distance.correlation(cam_rots, gyro_rots)
209 dists.append(scipy.spatial.distance.correlation(cam_rots, gyro_rots))
|
| /external/libhevc/test/encoder/ |
| vid_enc_cfg.txt | 78 --cu_level_rc 1 /* CU QP Modulation 0-disable, 1-spatial qp modulation {1} */
|
| /external/tensorflow/tensorflow/core/framework/ |
| common_shape_fns.h | 40 // dimension. This is usually used to make sure that the spatial dimensions
71 // For 2D and 3D convolutions, the spatial dimensions are orthogonal, so the
72 // size and padding of each spatial dimension can be computed by calling
222 const std::vector<DimensionOrConstant>& spatial,
|
| common_shape_fns.cc | 329 const std::vector<DimensionOrConstant>& spatial,
332 const int num_dims = GetTensorDimsFromSpatialDims(spatial.size(), format);
344 for (int spatial_dim = 0; spatial_dim < spatial.size(); spatial_dim++) {
346 context->MakeDim(spatial[spatial_dim]);
360 // Spatial.
386 // Spatial.
[all...] |
| /external/libvpx/libvpx/ |
| configure | 48 ${toggle_spatial_resampling} spatial sampling (scaling) support
61 ${toggle_temporal_denoising} enable temporal denoising and disable the spatial denoiser
|
| /external/mesa3d/src/gallium/state_trackers/vdpau/ |
| vdpau_private.h | 371 bool supported, enabled, spatial; member in struct:__anon34070::__anon34072
|
| mixer.c | 480 vmixer->skip_chroma_deint, vmixer->deint.spatial);
[all...] |
| /external/tensorflow/tensorflow/go/op/ |
| wrappers.go | 665 // Rearranges blocks of spatial data, into depth. More specifically,
751 // block_size: The size of the spatial block.
775 // Zero-pads and then rearranges (permutes) blocks of spatial data into batch.
784 // the padding of the input with zeros across the spatial dimensions as follows:
788 // The effective spatial dimensions of the zero-padded input tensor will be:
887 // This operation divides "spatial" dimensions `[1, ..., M]` of the input into a
889 // "batch" dimension (0) such that in the output, the spatial dimensions
891 // dimension combines both the position within a spatial block and the original
892 // batch position. Prior to division into blocks, the spatial dimensions of the
[all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| layers.py | [all...] |
