/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
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/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));
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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
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ideint_cac_a9.s | 24 @* This file contains definitions of routines for spatial filter
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/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))
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/external/libhevc/test/encoder/ |
vid_enc_cfg.txt | 78 --cu_level_rc 1 /* CU QP Modulation 0-disable, 1-spatial qp modulation {1} */
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/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,
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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
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/external/mesa3d/src/gallium/state_trackers/vdpau/ |
vdpau_private.h | 371 bool supported, enabled, spatial; member in struct:__anon34070::__anon34072
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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...] |