This is a collection of utilities for handling various types of multimedia data. Enhance your experience by seamlessly integrating these utilities with the Clarifai Python SDK. This powerful combination empowers you to address both visual and textual use cases effortlessly through the capabilities of Artificial Intelligence. Unlock new possibilities and elevate your projects with the synergy of versatile data utilities and the robust features offered by the Clarifai Python SDK. Explore the fusion of these tools to amplify the intelligence in your applications! 🌐🚀
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Install from PyPi:
pip install clarifai-datautils
Install from Source:
git clone https://github.com/Clarifai/clarifai-python-datautils
cd clarifai-python-datautils
python3 -m venv env
source env/bin/activate
pip3 install -r requirements.txt
Quick intro to Image Annotation Conversion feature
from clarifai_datautils.image import ImageAnnotations
annotated_dataset = ImageAnnotations.import_from(path= 'folder_path', format= 'annotation_format')
-
- Load various annotated image datasets and export to clarifai Platform
- Convert from one annotation format to other supported annotation formats
- Easy to use pipelines to load data from files and ingest into clarifai platfrom.
- Load text files(pdf, doc, etc..) , transform, chunk and upload to the Clarifai Platform
To use Image Annotation Loader, please install the extra libs required for annotations
from clarifai_datautils.image import ImageAnnotations
#import from folder
coco_dataset = ImageAnnotations.import_from(path='folder_path',format= 'coco_detection')
#Using clarifai SDK to upload to Clarifai Platform
#export CLARIFAI_PAT={your personal access token} # set PAT as env variable
from clarifai.client.dataset import Dataset
dataset = Dataset(user_id="user_id", app_id="app_id", dataset_id="dataset_id")
dataset.upload_dataset(dataloader=coco_dataset.dataloader)
#info about loaded dataset
coco_dataset.get_info()
#exporting to other formats
coco_dataset.export_to('voc_detection')
To use Data Ingestion Pipeline, please run
pip install -r requirements-dev.txt
from clarifai_datautils.text import Pipeline, PDFPartition
from clarifai_datautils.text.pipeline.cleaners import Clean_extra_whitespace
# Define the pipeline
pipeline = Pipeline(
name='pipeline-1',
transformations=[
PDFPartition(chunking_strategy = "by_title",max_characters = 1024),
Clean_extra_whitespace()
]
)
# Using SDK to upload
from clarifai.client import Dataset
dataset = Dataset(dataset_url)
dataset.upload_dataset(pipeline.run(files = file_path, loader = True))
See many more code examples in this repo.