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zyuan2009's Projects

adanet icon adanet

Fast and flexible AutoML with learning guarantees.

awesome-rnn icon awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

corenlp icon corenlp

Stanford CoreNLP: A Java suite of core NLP tools.

dain icon dain

Depth-Aware Video Frame Interpolation (CVPR 2019)

diffusers icon diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

draggan icon draggan

Official Code for DragGAN (SIGGRAPH 2023)

east icon east

A tensorflow implementation of EAST text detector

gflags icon gflags

The gflags package contains a C++ library that implements commandline flags processing. It includes built-in support for standard types such as string and the ability to define flags in the source file in which they are used. Online documentation available at:

glog icon glog

C++ implementation of the Google logging module

iccv17-fashiongan icon iccv17-fashiongan

Full version (training+testing) of implementation of Shizhan Zhu et al.'s ICCV-17 work Be Your Own Prada: Fashion Synthesis with Structural Coherence

imagen-pytorch icon imagen-pytorch

Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch

labelimg icon labelimg

:metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images

magento2 icon magento2

Prior to making any Submission(s), you must sign an Adobe Contributor License Agreement, available here at: https://opensource.adobe.com/cla.html. All Submissions you make to Adobe Inc. and its affiliates, assigns and subsidiaries (collectively “Adobe”) are subject to the terms of the Adobe Contributor License Agreement.

mask_rcnn icon mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

mediapipe icon mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

neuroner icon neuroner

Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.

pydensecrf icon pydensecrf

Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.

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