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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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from towhee.runtime.factory import ops_parse, _OperatorWrapper
from .image_embedding import ImageEmbedding
from .image_decode import ImageDecode
from .sentence_embedding import SentenceEmbedding
from .data_source import DataSource
from .ann_insert import AnnInsert
from .ann_search import AnnSearch
from .image_text_embedding import ImageTextEmbedding
from .audio_embedding import AudioEmbedding
from .audio_decode import AudioDecode
from .video_decode import VideoDecode
from .object_detection import ObjectDetection
from .utils import Utils
from .rerank import ReRank
from .llm import LLM
from .prompt import Prompt
from .data_loader import DataLoader
[docs]
class Ops:
"""
Class to loading operator with _OperatorWrapper.
An operator is usually referred to with its full name: namespace/name.
Examples:
>>> from towhee import ops
>>> op = ops.towhee.image_decode()
>>> img = op('./towhee_logo.png')
We can also specify the version of the operator on the hub via the `revision` method:
>>> op = ops.towhee.image_decode()
And the `latest` method is used to update the current version of the operator to the latest:
>>> op = ops.towhee.image_decode().latest()
"""
image_embedding: ImageEmbedding = ImageEmbedding()
"""
`image_embedding <https://towhee.io/tasks/detail/operator?field_name=Computer-Vision&task_name=Image-Embedding>`_
is a task that attempts to comprehend an entire image as a whole
and encode the image's semantics into a real vector.
It is a fundamental task type that can be used in a variety of applications,
including but not limited to reverse image search and image deduplication.
"""
image_text_embedding: ImageTextEmbedding = ImageTextEmbedding()
"""
`text_image_embedding <https://towhee.io/tasks/detail/operator?field_name=Multimodal&task_name=Image/Text-Embedding>`_
is a task that attempts to comprehend images and texts, and encode both image's and text's
semantics into a same embedding space. It is a fundamental task type that can be used in a variety
of applications, such as cross-modal retrieval.
"""
audio_embedding: AudioEmbedding = AudioEmbedding()
"""
`Audio embedding <https://towhee.io/tasks/detail/operator?field_name=Audio&task_name=Audio-Embedding>`_
is a task that encodes audio's semantics into a set of real vectors. It is a fundamental task type that
can be used in a variety of applications, including but not limited to reverse audio search and audio deduplication.
"""
image_decode: ImageDecode = ImageDecode()
"""
`image_decode <https://towhee.io/tasks/detail/operator?field_name=Computer-Vision&task_name=Image-Decode>`_
operators convert an encoded image back to its uncompressed format.
In most cases, image decoding is the first step of an image processing pipeline.
"""
audio_decode: AudioDecode = AudioDecode()
"""
Audio Decode converts the encoded audio back to uncompressed audio frames.
In most cases, audio decoding is the first step of an audio processing pipeline.
"""
video_decode: VideoDecode = VideoDecode()
"""
Video deocde, in most cases, video decode is the first step of an video processing pipeline.
"""
sentence_embedding: SentenceEmbedding = SentenceEmbedding()
"""
`sentence_embedding <https://towhee.io/tasks/detail/operator?field_name=Natural-Language-Processing&task_name=Sentence-Embedding>`_
is the extension of word or token embedding. Instead of generating a vector for each token or word,
it represents semantic information of the whole text as a vector.
"""
data_source: DataSource = DataSource()
"""
`data_source <https://towhee.io/data-source?index=1&size=30&type=2>`_ load data from many different sources.
Work with `DataLoader <https://towhee.readthedocs.io/en/latest/data_source/data_source.html>`_
"""
ann_insert: AnnInsert = AnnInsert()
"""
The ANN Insert Operator is used to insert embeddings and create ANN indexes for fast similarity searches.
"""
ann_search: AnnSearch = AnnSearch()
"""
The ANN search operator is used to find the closest (or most similar)
point to a given point in a given set, i.e. find similar embeddings.
"""
object_detetction: ObjectDetection = ObjectDetection()
"""
`Object detection <https://towhee.io/tasks/detail/operator?field_name=Computer-Vision&task_name=Object-Detection>`_
is a computer vision technique that locates and identifies people, items, or other objects in an image. Object detection has applications
in many areas of computer vision, including image retrieval, image annotation, vehicle counting, object tracking, etc.
"""
utils: Utils = Utils()
"""
Some utils.
"""
rerank: ReRank = ReRank()
"""
Re-rank the search results based on relevance
"""
LLM: LLM = LLM() # pylint: disable=invalid-name
"""
The LLM ops are designed to provide a standard interface for all of them.
"""
prompt: Prompt = Prompt()
"""
prompt template.
"""
data_loader: DataLoader = DataLoader()
"""
Load data from various sources.
"""
@classmethod
def __getattr__(cls, name):
@ops_parse
def wrapper(name, *args, **kws):
return _OperatorWrapper.callback(name, *args, **kws)
return getattr(wrapper, name)
