mbodied.types.sense package∞

Submodules∞

mbodied.types.sense.sensor_reading module∞

class mbodied.types.sense.sensor_reading.SensorReading(datum=None, **data)[source]∞

Bases: Sample

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}∞

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ConfigDict = {'arbitrary_types_allowed': True, 'extra': 'allow', 'from_attributes': True, 'use_enum_values': False, 'validate_assignment': False}∞

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {}∞

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

mbodied.types.sense.vision module∞

Wrap any common image representation in an Image class to convert to any other common format.

The following image representations are supported: - NumPy array - PIL Image - Base64 encoded string - File path - URL - Bytes object

The image can be resized to and from any size, compressed, and converted to and from any supported format:

```python image = Image(“path/to/image.png”, size=new_size_tuple).save(“path/to/new/image.jpg”) image.save(“path/to/new/image.jpg”, quality=5)

TODO: Implement Lazy attribute loading for the image data.

class mbodied.types.sense.vision.Image(arg: ndarray | Image | str | Url | Path = None, url: str | None = None, path: str | None = None, base64: str | None = None, array: ndarray | None = None, pil: Image | None = None, encoding: str | None = 'jpeg', size: Tuple | None = None, bytes_obj: bytes | None = None, **kwargs)[source]∞

Bases: Sample

An image sample that can be represented in various formats.

The image can be represented as a NumPy array, a base64 encoded string, a file path, a PIL Image object, or a URL. The image can be resized to and from any size and converted to and from any supported format.

array∞

The image represented as a NumPy array.

Type:

Optional[np.ndarray]

base64∞

The base64 encoded string of the image.

Type:

Optional[Base64Str]

path∞

The file path of the image.

Type:

Optional[FilePath]

pil∞

The image represented as a PIL Image object.

Type:

Optional[PILImage]

url∞

The URL of the image.

Type:

Optional[AnyUrl]

size∞

The size of the image as a (width, height) tuple.

Type:

Optional[tuple[int, int]]

encoding∞

The encoding of the image.

Type:

Optional[Literal[“png”, “jpeg”, “jpg”, “bmp”, “gif”]]

Example

>>> image = Image("https://example.com/image.jpg")
>>> image = Image("/path/to/image.jpg")
>>> image = Image("data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/4Q3zaHR0cDovL25zLmFkb2JlLmNvbS94YXAvMS4wLwA")

>>> jpeg_from_png = Image("path/to/image.png", encoding="jpeg")
>>> resized_image = Image(image, size=(224, 224))
>>> pil_image = Image(image).pil
>>> array = Image(image).array
>>> base64 = Image(image).base64
array: ndarray[Any, dtype[Any]] | Path | MultiArrayNumpyFile∞
base64: str | None∞
static bytes_to_data(bytes_data: bytes, encoding: str = 'jpeg', size=None) → dict[source]∞

Creates an Image instance from a bytes object.

Parameters:

  • bytes_data (bytes) – The bytes object to convert to an image.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

dump(*args, as_field: str | None = None, **kwargs) → dict | Any[source]∞

Return a dict or a field of the image.

encoding: Literal['png', 'jpeg', 'jpg', 'bmp', 'gif']∞
exclude_pil() → dict[source]∞

Convert the image to a base64 encoded string.

static from_base64(base64_str: str, encoding: str, size=None) → Image[source]∞

Decodes a base64 string to create an Image instance.

Parameters:

  • base64_str (str) – The base64 string to decode.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

classmethod from_bytes(bytes_data: bytes, encoding: str = 'jpeg', size=None) → Image[source]∞

Creates an Image instance from a bytes object.

Parameters:

  • bytes_data (bytes) – The bytes object to convert to an image.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

infer_features_dict() → Features[source]∞

Infer features of the image.

static load_url(url: str, download=False) → Image | None[source]∞

Downloads an image from a URL or decodes it from a base64 data URI.

Parameters:

url (str) – The URL of the image to download, or a base64 data URI.

Returns:

The downloaded and decoded image as a PIL Image object.

Return type:

PIL.Image.Image

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}∞

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ConfigDict = {'arbitrary_types_allowed': True, 'extra': 'allow', 'extras': 'forbid', 'from_attributes': True, 'use_enum_values': False, 'validate_assignment': False}∞

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'array': FieldInfo(annotation=Union[ndarray[Any, dtype[Any]], Annotated[Path, PathType], MultiArrayNumpyFile], required=True, metadata=[<class 'pydantic_numpy.helper.annotation.NpNDArrayPydanticAnnotation'>]), 'base64': FieldInfo(annotation=Union[Annotated[str, EncodedStr, InstanceOf], NoneType], required=False, default=None), 'encoding': FieldInfo(annotation=Literal['png', 'jpeg', 'jpg', 'bmp', 'gif'], required=True), 'path': FieldInfo(annotation=Union[Annotated[Path, PathType], NoneType], required=False, default=None), 'pil': FieldInfo(annotation=Union[Annotated[Image, InstanceOf], NoneType], required=False, default=None, description='The image represented as a PIL Image object.', exclude=True, repr=False), 'size': FieldInfo(annotation=tuple[int, int], required=True), 'url': FieldInfo(annotation=Union[Annotated[Url, InstanceOf], str, NoneType], required=False, default=None)}∞

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

static open(path: str, encoding: str = 'jpeg', size=None) → Image[source]∞

Opens an image from a file path.

Parameters:

  • path (str) – The path to the image file.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

path: Path | None∞
pil: Image | None∞
static pil_to_data(image: Image, encoding: str, size=None) → dict[source]∞

Creates an Image instance from a PIL image.

Parameters:

  • image (PIL.Image.Image) – The source PIL image from which to create the Image instance.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

save(path: str, encoding: str | None = None, quality: int = 10) → None[source]∞

Save the image to the specified path.

If the image is a JPEG, the quality parameter can be used to set the quality of the saved image. The path attribute of the image is updated to the new file path.

Parameters:

  • path (str) – The path to save the image to.

  • encoding (Optional[str]) – The encoding to use for saving the image.

  • quality (int) – The quality to use for saving the image.

show() → None[source]∞
size: tuple[int, int]∞
space() → Box[source]∞

Returns the space of the image.

classmethod supports(arg: ndarray | Image | str | Url | Path) → bool[source]∞
url: Url | str | None∞
classmethod validate_kwargs(values) → dict[source]∞

Module contents∞

class mbodied.types.sense.Image(arg: ndarray | Image | str | Url | Path = None, url: str | None = None, path: str | None = None, base64: str | None = None, array: ndarray | None = None, pil: Image | None = None, encoding: str | None = 'jpeg', size: Tuple | None = None, bytes_obj: bytes | None = None, **kwargs)[source]∞

Bases: Sample

An image sample that can be represented in various formats.

The image can be represented as a NumPy array, a base64 encoded string, a file path, a PIL Image object, or a URL. The image can be resized to and from any size and converted to and from any supported format.

array∞

The image represented as a NumPy array.

Type:

Optional[np.ndarray]

base64∞

The base64 encoded string of the image.

Type:

Optional[Base64Str]

path∞

The file path of the image.

Type:

Optional[FilePath]

pil∞

The image represented as a PIL Image object.

Type:

Optional[PILImage]

url∞

The URL of the image.

Type:

Optional[AnyUrl]

size∞

The size of the image as a (width, height) tuple.

Type:

Optional[tuple[int, int]]

encoding∞

The encoding of the image.

Type:

Optional[Literal[“png”, “jpeg”, “jpg”, “bmp”, “gif”]]

Example

>>> image = Image("https://example.com/image.jpg")
>>> image = Image("/path/to/image.jpg")
>>> image = Image("data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/4Q3zaHR0cDovL25zLmFkb2JlLmNvbS94YXAvMS4wLwA")

>>> jpeg_from_png = Image("path/to/image.png", encoding="jpeg")
>>> resized_image = Image(image, size=(224, 224))
>>> pil_image = Image(image).pil
>>> array = Image(image).array
>>> base64 = Image(image).base64
array: ndarray[Any, dtype[Any]] | Path | MultiArrayNumpyFile∞
base64: str | None∞
static bytes_to_data(bytes_data: bytes, encoding: str = 'jpeg', size=None) → dict[source]∞

Creates an Image instance from a bytes object.

Parameters:

  • bytes_data (bytes) – The bytes object to convert to an image.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

dump(*args, as_field: str | None = None, **kwargs) → dict | Any[source]∞

Return a dict or a field of the image.

encoding: Literal['png', 'jpeg', 'jpg', 'bmp', 'gif']∞
exclude_pil() → dict[source]∞

Convert the image to a base64 encoded string.

static from_base64(base64_str: str, encoding: str, size=None) → Image[source]∞

Decodes a base64 string to create an Image instance.

Parameters:

  • base64_str (str) – The base64 string to decode.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

classmethod from_bytes(bytes_data: bytes, encoding: str = 'jpeg', size=None) → Image[source]∞

Creates an Image instance from a bytes object.

Parameters:

  • bytes_data (bytes) – The bytes object to convert to an image.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

infer_features_dict() → Features[source]∞

Infer features of the image.

static load_url(url: str, download=False) → Image | None[source]∞

Downloads an image from a URL or decodes it from a base64 data URI.

Parameters:

url (str) – The URL of the image to download, or a base64 data URI.

Returns:

The downloaded and decoded image as a PIL Image object.

Return type:

PIL.Image.Image

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}∞

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ConfigDict = {'arbitrary_types_allowed': True, 'extra': 'allow', 'extras': 'forbid', 'from_attributes': True, 'use_enum_values': False, 'validate_assignment': False}∞

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'array': FieldInfo(annotation=Union[ndarray[Any, dtype[Any]], Annotated[Path, PathType], MultiArrayNumpyFile], required=True, metadata=[<class 'pydantic_numpy.helper.annotation.NpNDArrayPydanticAnnotation'>]), 'base64': FieldInfo(annotation=Union[Annotated[str, EncodedStr, InstanceOf], NoneType], required=False, default=None), 'encoding': FieldInfo(annotation=Literal['png', 'jpeg', 'jpg', 'bmp', 'gif'], required=True), 'path': FieldInfo(annotation=Union[Annotated[Path, PathType], NoneType], required=False, default=None), 'pil': FieldInfo(annotation=Union[Annotated[Image, InstanceOf], NoneType], required=False, default=None, description='The image represented as a PIL Image object.', exclude=True, repr=False), 'size': FieldInfo(annotation=tuple[int, int], required=True), 'url': FieldInfo(annotation=Union[Annotated[Url, InstanceOf], str, NoneType], required=False, default=None)}∞

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

static open(path: str, encoding: str = 'jpeg', size=None) → Image[source]∞

Opens an image from a file path.

Parameters:

  • path (str) – The path to the image file.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

path: Path | None∞
pil: Image | None∞
static pil_to_data(image: Image, encoding: str, size=None) → dict[source]∞

Creates an Image instance from a PIL image.

Parameters:

  • image (PIL.Image.Image) – The source PIL image from which to create the Image instance.

  • encoding (str) – The format used for encoding the image when converting to base64.

  • size (Optional[Tuple[int, int]]) – The size of the image as a (width, height) tuple.

Returns:

An instance of the Image class with populated fields.

Return type:

Image

save(path: str, encoding: str | None = None, quality: int = 10) → None[source]∞

Save the image to the specified path.

If the image is a JPEG, the quality parameter can be used to set the quality of the saved image. The path attribute of the image is updated to the new file path.

Parameters:

  • path (str) – The path to save the image to.

  • encoding (Optional[str]) – The encoding to use for saving the image.

  • quality (int) – The quality to use for saving the image.

show() → None[source]∞
size: tuple[int, int]∞
space() → Box[source]∞

Returns the space of the image.

classmethod supports(arg: ndarray | Image | str | Url | Path) → bool[source]∞
url: Url | str | None∞
classmethod validate_kwargs(values) → dict[source]∞