Data Reader is a function for reading input data. You can use 2 ways to set data_reader for dataset:
type:for setting reader name. This approach gives opportunity to set additional parameters for adapter if it is required.
In case, when you have model with several inputs which should use data stored in different format (e. g. images and json) you can use
combine_reader allows specify reading scheme depends on file names. It use parameter
scheme for describing reading approaches as dictionary where keys are regular expressions for file names, values are reader_name.
AccuracyChecker supports following list of data readers:
opencv_imread- read images using OpenCV library. Default color space is BGR.
reading_flag- (Optional) flag which specifies the way image should be read:
color- default, loads color image,
gray- loads image in grayscale mode,
unchanged- loads image as such including alpha channel.
pillow_imread- read images using Pillow library. Default color space is RGB.
scipy_imread- read images using similar approach as in
tf_imread- read images using TensorFlow. Default color space is RGB. Requires TensorFlow installation.
opencv_capture- read frames from video using OpenCV.
json_reader- read value from json file.
key- key for reading from stored in json dictionary.
annotation_features_extractor- read features from annotation.
features- list of features. All features should be fields of annotation representation.
numpy_reader- read numpy dumped files
nifti_reader- read NifTI data format
channels_first- allows read nifti files and transpose in order where channels first (Optional, default False)
wav_reader- read WAV file into NumPy array. Also gets the samplerate.
dicom_reader- read images stored in DICOM format.