| /OK3568_Linux_fs/external/rknpu2/examples/3rdparty/opencv/opencv-linux-aarch64/include/opencv2/flann/ |
| H A D | all_indices.h | 52 …static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const Inde… in create()
59 nnIndex = new LinearIndex<Distance>(dataset, params, distance); in create()
62 nnIndex = new KDTreeSingleIndex<Distance>(dataset, params, distance); in create()
65 nnIndex = new KDTreeIndex<Distance>(dataset, params, distance); in create()
68 nnIndex = new KMeansIndex<Distance>(dataset, params, distance); in create()
71 nnIndex = new CompositeIndex<Distance>(dataset, params, distance); in create()
74 nnIndex = new AutotunedIndex<Distance>(dataset, params, distance); in create()
77 nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); in create()
80 nnIndex = new LshIndex<Distance>(dataset, params, distance); in create()
93 …static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const Inde…
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| H A D | hierarchical_clustering_index.h | 127 … DistanceType sq = distance(dataset[centers[index]], dataset[centers[j]], dataset.cols); in chooseCentersRandom()
164 … DistanceType dist = distance(dataset[centers[0]],dataset[dsindices[j]],dataset.cols); in chooseCentersGonzales()
166 … DistanceType tmp_dist = distance(dataset[centers[i]],dataset[dsindices[j]],dataset.cols); in chooseCentersGonzales()
215 … closestDistSq[i] = distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols); in chooseCentersKMeanspp()
243 … DistanceType dist = distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols); in chooseCentersKMeanspp()
258 …DistanceType dist = distance(dataset[dsindices[i]], dataset[dsindices[bestNewIndex]], dataset.cols… in chooseCentersKMeanspp()
300 … closestDistSq[i] = distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols); in GroupWiseCenterChooser()
320 … newPot += std::min( distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols) in GroupWiseCenterChooser()
336 …closestDistSq[i] = std::min( distance(dataset[dsindices[i]], dataset[dsindices[bestNewIndex]], dat… in GroupWiseCenterChooser()
359 : dataset(inputData), params(index_params), root(NULL), indices(NULL), distance(d) in dataset() function
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| H A D | hdf5.h | 76 void save_to_file(const cvflann::Matrix<T>& dataset, const String& filename, const String& name) in save_to_file() argument
94 dimsf[0] = dataset.rows; in save_to_file()
95 dimsf[1] = dataset.cols; in save_to_file()
116 …status = H5Dwrite(dataset_id, get_hdf5_type<T>(), memspace_id, space_id, H5P_DEFAULT, dataset.data… in save_to_file()
128 void load_from_file(cvflann::Matrix<T>& dataset, const String& filename, const String& name) in load_from_file() argument
147 dataset = cvflann::Matrix<T>(new T[dims_out[0]*dims_out[1]], dims_out[0], dims_out[1]); in load_from_file()
149 status = H5Dread(dataset_id, get_hdf5_type<T>(), H5S_ALL, H5S_ALL, H5P_DEFAULT, dataset[0]); in load_from_file()
169 void load_from_file(cvflann::Matrix<T>& dataset, const String& filename, const String& name) in load_from_file() argument
212 dataset.rows = count[0]; in load_from_file()
213 dataset.cols = count[1]; in load_from_file()
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| H A D | ground_truth.h | 42 void find_nearest(const Matrix<typename Distance::ElementType>& dataset, typename Distance::Element…
51 dists[0] = distance(dataset[0], query, dataset.cols);
55 for (size_t i=1; i<dataset.rows; ++i) {
56 DistanceType tmp = distance(dataset[i], query, dataset.cols);
83 void compute_ground_truth(const Matrix<typename Distance::ElementType>& dataset, const Matrix<typen…
87 find_nearest<Distance>(dataset, testset[i], matches[i], (int)matches.cols, skip, d);
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| H A D | flann_base.hpp | 73 NNIndex<Distance>* load_saved_index(const Matrix<typename Distance::ElementType>& dataset, const cv… in load_saved_index() argument
86 if ((size_t(header.rows) != dataset.rows)||(size_t(header.cols) != dataset.cols)) { in load_saved_index()
93 NNIndex<Distance>* nnIndex = create_index_by_type<Distance>(dataset, params, distance); in load_saved_index()
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| H A D | lsh_table.h | 198 void add(Matrix<ElementType> dataset) in add() argument
201 buckets_space_.rehash((buckets_space_.size() + dataset.rows) * 1.2); in add()
204 for (unsigned int i = 0; i < dataset.rows; ++i) add(i, dataset[i]); in add()
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| /OK3568_Linux_fs/external/rknpu2/examples/3rdparty/opencv/opencv-linux-aarch64/include/opencv2/ |
| H A D | flann.hpp | 251 GenericIndex<Distance>::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Dist… in GenericIndex() argument
253 CV_Assert(dataset.type() == CvType<ElementType>::type()); in GenericIndex()
254 CV_Assert(dataset.isContinuous()); in GenericIndex()
255 …flann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, data… in GenericIndex()
347 CV_DEPRECATED Index_(const Mat& dataset, const ::cvflann::IndexParams& params) in Index_() argument
351 CV_Assert(dataset.type() == CvType<ElementType>::type()); in Index_()
352 CV_Assert(dataset.isContinuous()); in Index_()
353 …flann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, data… in Index_()
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| /OK3568_Linux_fs/docs/cn/Common/NPU/rknn-toolkit2/ |
| H A D | RKNNToolKit2_API_Difference_With_Toolkit1-1.4.0.md | 147 dataset='dataset.txt',
153 dataset='dataset.txt',
168 hybrid_quantization_step1(dataset=None)
171 hybrid_quantization_step1(dataset=None,
183 dataset, # abandoned
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| /OK3568_Linux_fs/external/rknn-toolkit2/doc/ |
| H A D | RKNNToolKit2_API_Difference_With_Toolkit1-1.5.0.md | 150 dataset='dataset.txt',
156 dataset='dataset.txt',
171 hybrid_quantization_step1(dataset=None)
174 hybrid_quantization_step1(dataset=None,
186 dataset, # abandoned
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| /OK3568_Linux_fs/docs/en/Common/NPU/rknn-toolkit2/ |
| H A D | RKNNToolKit2_API_Difference_With_Toolkit1-1.4.0.md | 147 dataset='dataset.txt',
153 dataset='dataset.txt',
168 hybrid_quantization_step1(dataset=None)
171 hybrid_quantization_step1(dataset=None,
183 dataset, # abandoned
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| /OK3568_Linux_fs/yocto/poky/bitbake/lib/toaster/toastergui/static/js/ |
| H A D | typeahead.jquery.js | 161 dataset: "tt-dataset", property
676 …this.$el = $(o.node).addClass(this.classes.dataset).addClass(this.classes.dataset + "-" + this.nam…
731 dataset: this.name property
739 dataset: this.name property
766 dataset: this.name property
773 dataset: this.name property
888 _onRendered: function onRendered(type, dataset, suggestions, async) {
890 this.trigger("datasetRendered", dataset, suggestions, async);
901 function isDatasetEmpty(dataset) { argument
902 return dataset.isEmpty();
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| /OK3568_Linux_fs/kernel/drivers/staging/media/atomisp/i2c/ |
| H A D | atomisp-libmsrlisthelper.c | 98 unsigned int dataset = 0; in parse_and_apply() local
111 dataset++; in parse_and_apply()
119 dataset, header->data_size); in parse_and_apply()
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/functions/hybrid_quant/ |
| H A D | step1.py | 28 ret = rknn.hybrid_quantization_step1(dataset='./dataset.txt', proposal=False)
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| /OK3568_Linux_fs/yocto/meta-openembedded/meta-python/recipes-devtools/python/ |
| H A D | python3-pycocotools_2.0.4.bb | 1 SUMMARY = "COCO is a large image dataset designed for object detection, segmentation, \
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| /OK3568_Linux_fs/external/rknpu2/examples/rknn_yolov5_demo/convert_rknn_demo/yolov5/ |
| H A D | onnx2rknn.py | 39 ret = rknn.build(do_quantization=True, dataset=DATASET)
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| /OK3568_Linux_fs/external/rknpu2/examples/RV1106_RV1103/rknn_yolov5_demo/convert_rknn_demo/yolov5/ |
| H A D | onnx2rknn.py | 36 ret = rknn.build(do_quantization=True, dataset=DATASET)
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/functions/multi_input_test/ |
| H A D | test.py | 29 ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
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| /OK3568_Linux_fs/buildroot/package/flann/ |
| H A D | Config.in | 11 dataset.
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/caffe/mobilenet_v2/ |
| H A D | test.py | 46 ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/functions/model_pruning/ |
| H A D | test.py | 46 ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/tflite/mobilenet_v1/ |
| H A D | test.py | 44 ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/functions/batch_size/ |
| H A D | test.py | 51 ret = rknn.build(do_quantization=True, dataset='./dataset.txt', rknn_batch_size=4)
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/functions/mmse/ |
| H A D | test.py | 48 ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/functions/board_test/ |
| H A D | test.py | 46 ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
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| /OK3568_Linux_fs/external/rknn-toolkit2/examples/pytorch/resnet18/ |
| H A D | test.py | 68 ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
|