Searched refs:image_paths (Results 1 – 5 of 5) sorted by relevance
/external/tensorflow/tensorflow/python/keras/preprocessing/ |
D | image_dataset.py | 186 image_paths, labels, class_names = dataset_utils.index_directory( 200 image_paths, labels = dataset_utils.get_training_or_validation_split( 201 image_paths, labels, validation_split, subset) 202 if not image_paths: 206 image_paths=image_paths, 221 dataset.file_paths = image_paths 225 def paths_and_labels_to_dataset(image_paths, argument 235 path_ds = dataset_ops.Dataset.from_tensor_slices(image_paths)
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/external/tensorflow/tensorflow/lite/tools/evaluation/tasks/coco_object_detection/ |
D | run_eval.cc | 113 std::vector<std::string> image_paths; in RunImpl() local 115 &image_paths) != kTfLiteOk) { in RunImpl() 145 const int step = image_paths.size() / 100; in RunImpl() 146 for (int i = 0; i < image_paths.size(); ++i) { in RunImpl() 151 const std::string image_name = GetNameFromPath(image_paths[i]); in RunImpl() 152 eval.SetInputs(image_paths[i], ground_truth_map[image_name]); in RunImpl()
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/external/tensorflow/tensorflow/stream_executor/gpu/ |
D | asm_compiler.cc | 291 std::vector<std::string> image_paths; in BundleGpuAsm() local 302 image_paths.push_back(std::move(img_path)); in BundleGpuAsm() 304 auto image_files_cleaner = tensorflow::gtl::MakeCleanup([&image_paths] { in BundleGpuAsm() 305 for (const auto& path : image_paths) { in BundleGpuAsm() 327 assert(images.size() == image_paths.size()); in BundleGpuAsm() 330 "--image=profile=%s,file=%s", images[i].profile, image_paths[i])); in BundleGpuAsm() 386 std::vector<std::string> image_paths; in BundleGpuAsm() local 399 image_paths.push_back(std::move(img_path)); in BundleGpuAsm() 401 auto image_files_cleaner = tensorflow::gtl::MakeCleanup([&image_paths] { in BundleGpuAsm() 402 for (const auto& path : image_paths) { in BundleGpuAsm()
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/external/pdfium/testing/tools/ |
D | safetynet_image.py | 284 image_paths = glob.glob(image_path_matcher) 287 os.path.split(image_path)[1]: image_path for image_path in image_paths
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D | test_runner.py | 222 success, image_paths = result 224 if image_paths: 225 for img_path, md5_hash in image_paths:
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