Function mindspore::dataset::Cityscapes
Defined in File datasets.h
Function Documentation
Function to create a CityscapesDataset.
Note
The generated dataset has two columns [“image”, “task”].
- Parameters
dataset_dir – [in] The dataset dir to be read.
usage – [in] The type of dataset. Acceptable usages include “train”, “test”, “val” or “all” if quality_mode is “fine” otherwise “train”, “train_extra”, “val” or “all”.
quality_mode – [in] The quality mode of processed image. Acceptable quality_modes include “fine” or “coarse”.
task – [in] The type of task which is used to select output data. Acceptable tasks include “instance”, “semantic”, “polygon” or “color”.
decode – [in] Decode the images after reading (default=false).
sampler – [in] Shared pointer to a sampler object used to choose samples from the dataset. If sampler is not given, a
RandomSampler
will be used to randomly iterate the entire dataset (default = RandomSampler()).cache – [in] Tensor cache to use. (default=nullptr which means no cache is used).
- Returns
Shared pointer to the current CityscapesDataset.
Example/* Define dataset path and MindData object */ std::string folder_path = "/path/to/cityscapes_dataset_directory"; std::shared_ptr<Dataset> ds = Cityscapes(dataset_path, "train", "fine", "color"); /* Create iterator to read dataset */ std::shared_ptr<Iterator> iter = ds->CreateIterator(); std::unordered_map<std::string, mindspore::MSTensor> row; iter->GetNextRow(&row); /* Note: In Cityscapes dataset, each data dictionary owns keys "image" and "task" */ auto task = row["task"];