fiftyone.utils.image

module documentation

(source)

Image utilities.

Function	`read`	Reads the image from the given path as a numpy array.
Function	`reencode_image`	Re-encodes the image to the format specified by the given output path.
Function	`reencode_images`	Re-encodes the images in the sample collection to the given format.
Function	`transform_image`	Transforms the image according to the provided parameters.
Function	`transform_images`	Transforms the images in the sample collection according to the provided parameters.
Function	`write`	Writes image to file.
Variable	`logger`	Undocumented
Function	`_do_transform`	Undocumented
Function	`_get_outpath`	Undocumented
Function	`_parse_ext`	Undocumented
Function	`_parse_parameters`	Undocumented
Function	`_transform_image`	Undocumented
Function	`_transform_images`	Undocumented
Function	`_transform_images_multi`	Undocumented
Function	`_transform_images_single`	Undocumented

def read(path_or_url, include_alpha=False, flag=None): (source) ¶

Reads the image from the given path as a numpy array.

Color images are returned as RGB arrays.

Parameters
path_or_url	Undocumented
include_alpha:`False`	whether to include the alpha channel of the image, if present, in the returned array
flag:`None`	an optional OpenCV image format flag to use. If provided, this flag takes precedence over `include_alpha`
path	the filepath or URL of the image
Returns
a uint8 numpy array containing the image

def reencode_image(input_path, output_path): (source) ¶

Re-encodes the image to the format specified by the given output path.

Parameters
input_path	the path to the input image
output_path	the path to write the output image

def reencode_images(sample_collection, ext='.png', force_reencode=True, media_field='filepath', output_field=None, output_dir=None, rel_dir=None, update_filepaths=True, delete_originals=False, num_workers=None, skip_failures=False, progress=None): (source) ¶

Re-encodes the images in the sample collection to the given format.

If no output_dir is specified and delete_originals is False, then if a transformation would result in overwriting an existing file with the same filename, the original file is renamed to <name>-original.<ext>.

Note

This method will not update the metadata field of the collection after transforming. You can repopulate the metadata field if needed by calling:

sample_collection.compute_metadata(overwrite=True)

Parameters
sample_collection	a `fiftyone.core.collections.SampleCollection`
ext:".png"	the image format to use (e.g., ".png" or ".jpg")
force_reencode:`True`	whether to re-encode images whose extension already matches `ext`
media_field:"filepath"	the input field containing the image paths to transform
output_field:`None`	an optional field in which to store the paths to the transformed images. By default, `media_field` is updated in-place
output_dir:`None`	an optional output directory in which to write the transformed images. If none is provided, the images are updated in-place
rel_dir:`None`	an optional relative directory to strip from each input filepath to generate a unique identifier that is joined with `output_dir` to generate an output path for each image. This argument allows for populating nested subdirectories in `output_dir` that match the shape of the input paths
update_filepaths:`True`	whether to store the output paths on the sample collection
delete_originals:`False`	whether to delete the original images after re-encoding
num_workers:`None`	a suggested number of worker processes to use
skip_failures:`False`	whether to gracefully continue without raising an error if an image cannot be re-encoded
progress:`None`	whether to render a progress bar (True/False), use the default value `fiftyone.config.show_progress_bars` (None), or a progress callback function to invoke instead

def transform_image(input_path, output_path, size=None, min_size=None, max_size=None, interpolation=None): (source) ¶

Transforms the image according to the provided parameters.

Parameters
input_path	the path to the input image
output_path	the path to write the output image
size:`None`	an optional `(width, height)` for the image. One dimension can be -1, in which case the aspect ratio is preserved
min_size:`None`	an optional minimum `(width, height)` for the image. A dimension can be -1 if no constraint should be applied. The image is resized (aspect-preserving) if necessary to meet this constraint
max_size:`None`	an optional maximum `(width, height)` for the image. A dimension can be -1 if no constraint should be applied. The image is resized (aspect-preserving) if necessary to meet this constraint
interpolation:`None`	an optional `interpolation` argument for `cv2.resize()`

def transform_images(sample_collection, size=None, min_size=None, max_size=None, interpolation=None, ext=None, force_reencode=False, media_field='filepath', output_field=None, output_dir=None, rel_dir=None, update_filepaths=True, delete_originals=False, num_workers=None, skip_failures=False, progress=None): (source) ¶

Transforms the images in the sample collection according to the provided parameters.

Note

This method will not update the metadata field of the collection after transforming. You can repopulate the metadata field if needed by calling:

sample_collection.compute_metadata(overwrite=True)

Parameters
sample_collection	a `fiftyone.core.collections.SampleCollection`
size:`None`	an optional `(width, height)` for each image. One dimension can be -1, in which case the aspect ratio is preserved
min_size:`None`	an optional minimum `(width, height)` for each image. A dimension can be -1 if no constraint should be applied. The images are resized (aspect-preserving) if necessary to meet this constraint
max_size:`None`	an optional maximum `(width, height)` for each image. A dimension can be -1 if no constraint should be applied. The images are resized (aspect-preserving) if necessary to meet this constraint
interpolation:`None`	an optional `interpolation` argument for `cv2.resize()`
ext:`None`	an optional image format to re-encode the source images into (e.g., ".png" or ".jpg")
force_reencode:`False`	whether to re-encode images whose parameters already match the specified values
media_field:"filepath"	the input field containing the image paths to transform
output_field:`None`	an optional field in which to store the paths to the transformed images. By default, `media_field` is updated in-place
output_dir:`None`	an optional output directory in which to write the transformed images. If none is provided, the images are updated in-place
rel_dir:`None`	an optional relative directory to strip from each input filepath to generate a unique identifier that is joined with `output_dir` to generate an output path for each image. This argument allows for populating nested subdirectories in `output_dir` that match the shape of the input paths
update_filepaths:`True`	whether to store the output paths on the sample collection
delete_originals:`False`	whether to delete the original images if any transformation was applied
num_workers:`None`	a suggested number of worker processes to use
skip_failures:`False`	whether to gracefully continue without raising an error if an image cannot be transformed
progress:`None`	whether to render a progress bar (True/False), use the default value `fiftyone.config.show_progress_bars` (None), or a progress callback function to invoke instead

def write(img, path): (source) ¶

Writes image to file.

Parameters
img	a numpy array
path	the output path

logger = (source) ¶

Undocumented

def _do_transform(args): (source) ¶

Undocumented

def _get_outpath(inpath, output_dir=None, rel_dir=None): (source) ¶

Undocumented

def _parse_ext(ext): (source) ¶

Undocumented

def _parse_parameters(img, size, min_size, max_size): (source) ¶

Undocumented

def _transform_image(inpath, outpath, size=None, min_size=None, max_size=None, interpolation=None, force_reencode=False, delete_original=False, skip_failures=False): (source) ¶

Undocumented

def _transform_images(sample_collection, size=None, min_size=None, max_size=None, interpolation=None, ext=None, force_reencode=False, media_field='filepath', output_field=None, output_dir=None, rel_dir=None, update_filepaths=True, delete_originals=False, num_workers=None, skip_failures=False, progress=None): (source) ¶

Undocumented

def _transform_images_multi(sample_collection, num_workers, size=None, min_size=None, max_size=None, interpolation=None, ext=None, force_reencode=False, media_field='filepath', output_field=None, output_dir=None, rel_dir=None, update_filepaths=True, delete_originals=False, skip_failures=False, progress=None): (source) ¶

Undocumented

def _transform_images_single(sample_collection, size=None, min_size=None, max_size=None, interpolation=None, ext=None, force_reencode=False, media_field='filepath', output_field=None, output_dir=None, rel_dir=None, update_filepaths=True, delete_originals=False, skip_failures=False, progress=None): (source) ¶

Undocumented