Image configuration¶
enable_tensorflow_image¶
Enable Image Transformer for processing of image data (String)
Default value 'auto'
Whether to use pretrained deep learning models for processing of image data as part of the feature engineering pipeline. A column of URIs to images (jpg, png, etc.) will be converted to a numeric representation using ImageNet-pretrained deep learning models. If no GPUs are found, then must be set to ‘on’ to enable.
tensorflow_image_pretrained_models¶
Supported ImageNet pretrained architectures for Image Transformer (List)
Default value ['xception']
Supported ImageNet pretrained architectures for Image Transformer. Non-default ones will require internet access to download pretrained models from H2O S3 buckets (To get all models, download http://s3.amazonaws.com/artifacts.h2o.ai/releases/ai/h2o/pretrained/dai_image_models_1_10.zip and unzip inside tensorflow_image_pretrained_models_dir).
tensorflow_image_vectorization_output_dimension¶
Dimensionality of feature space created by Image Transformer (List)
Default value [100]
Dimensionality of feature (embedding) space created by Image Transformer. If more than one is selected, multiple transformers can be active at the same time.
tensorflow_image_fine_tune¶
Enable fine-tuning of pretrained models used for Image Transformer (Boolean)
Default value False
Enable fine-tuning of the ImageNet pretrained models used for the Image Transformer. Enabling this will slow down training, but should increase accuracy.
tensorflow_image_fine_tuning_num_epochs¶
Number of epochs for fine-tuning used for Image Transformer (Number)
Default value 2
Number of epochs for fine-tuning of ImageNet pretrained models used for the Image Transformer.
tensorflow_image_augmentations¶
List of augmentations for fine-tuning used for Image Transformer (List)
Default value ['HorizontalFlip']
The list of possible image augmentations to apply while fine-tuning the ImageNet pretrained models used for the Image Transformer. Details about individual augmentations could be found here: https://albumentations.ai/docs/.
tensorflow_image_batch_size¶
Batch size for Image Transformer. Automatic: -1 (Number)
Default value -1
Batch size for Image Transformer. Larger architectures and larger batch sizes will use more memory.
tensorflow_image_pretrained_models_dir¶
Path to pretrained Image models. It is used to load the pretrained models if there is no Internet access. (String)
Default value './pretrained/image/'
Path to pretrained Image models. To get all models, download http://s3.amazonaws.com/artifacts.h2o.ai/releases/ai/h2o/pretrained/dai_image_models_1_10.zip, then extract it in a directory on the instance where Driverless AI is installed.
image_download_timeout¶
Image download timeout in seconds (Number)
Default value 60
Max. number of seconds to wait for image download if images are provided by URL
string_col_as_image_max_missing_fraction¶
Max allowed fraction of missing values for image column (Float)
Default value 0.1
Maximum fraction of missing elements in a string column for it to be considered as possible image paths (URIs)
string_col_as_image_min_valid_types_fraction¶
Min. fraction of images that need to be of valid types for image column to be used (Float)
Default value 0.8
Fraction of (unique) image URIs that need to have valid endings (as defined by string_col_as_image_valid_types) for a string column to be considered as image data
tensorflow_image_use_gpu¶
Enable GPU(s) for faster transformations of Image Transformer. (Boolean)
Default value True
Whether to use GPU(s), if available, to transform images into embeddings with Image Transformer. Can lead to significant speedups.
max_image_auto_ddp_cores¶
Maximum number of cores to use for image auto model parallel data management (Number)
Default value 10
Control maximum number of cores to use for image auto model parallel data management. 0 will disable mp: https://pytorch-lightning.readthedocs.io/en/latest/guides/speed.html