Shanoa00

Shanoa00's Stars

• ZZZHANG-jx/DocRes

  [CVPR 2024] DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks

  Language:Python29629

• HCIILAB/Scene-Text-Recognition-Recommendations

  Papers, Datasets, Algorithms, SOTA for STR. Long-time Maintaining

  Language:Python31937

• ggerganov/llama.cpp

  LLM inference in C/C++

  Language:C++65.9k9.5k

• stanfordnlp/dspy

  DSPy: The framework for programming—not prompting—foundation models

  Language:Python17.5k1.3k

• microsoft/LLMLingua

  To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

  Language:Python4.5k251

• hiyouga/LLaMA-Factory

  Efficiently Fine-Tune 100+ LLMs in WebUI (ACL 2024)

  Language:Python31.9k3.9k

• ZofiaQlt/market_research_nlp_clustering

  🎯 International market analysis and optimization program for reducing food waste and improving the vegetable export industry - use of Python, JupyterLab and NLP (Background research, Data collection, Cleaning, EDA, Unsupervised Machine Learning, Factorial method, HCA, Clustering, Data Visualization and 10-year projection with Sankey Diagram

  Language:Jupyter Notebook1

• alibaba/EasyRec

  A framework for large scale recommendation algorithms.

  Language:Python1.7k316

• alvinwan/neural-backed-decision-trees

  Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

  Language:Python605130

• lmartak/distill-nn-tree

  Distillation of Neural Network Into a Soft Decision Tree

  Language:Jupyter Notebook6429

• shivammehta25/Matcha-TTS

  [ICASSP 2024] 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching

  Language:Jupyter Notebook64881

• google/sentencepiece

  Unsupervised text tokenizer for Neural Network-based text generation.

  Language:C++10.1k1.2k

• explosion/spaCy

  💫 Industrial-strength Natural Language Processing (NLP) in Python

  Language:Python29.8k4.4k

• Mingjian-Zhu/DyFPN

  Language:Python468

• Genymobile/scrcpy

  Display and control your Android device

  Language:C110k10.6k

• potterhsu/easy-fpn.pytorch

  An easy implementation of FPN (https://arxiv.org/pdf/1612.03144.pdf) in PyTorch.

  Language:Python12121

• KevinKecc/MAL

  MAL for cvpr765

  Language:Python357

• obss/sahi

  Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

  Language:Python4k580

• Mr-TalhaIlyas/EMPatches

  Extract and Merge image patches for easy, fast and self-contained digital image processing and deep learning model training.

  Language:Jupyter Notebook459

• Zhangbaisong/DSFP-GA

  Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection

  51

• dell-research-harvard/HJDataset

  A Large Dataset of Historical Japanese Documents with Complex Layouts

  Language:Jupyter Notebook304

• fundamentalvision/Deformable-DETR

  Deformable DETR: Deformable Transformers for End-to-End Object Detection.

  Language:Python3.2k514

• tascj/kaggle-kuzushiji-recognition

  Kaggle Kuzushiji Recognition Solution

  Language:Python9425

• HCIILAB/MTHv2_Datasets_Release

  502

• knjcode/kaggle-kuzushiji-recognition-2019

  Language:Python287

• ZFTurbo/Weighted-Boxes-Fusion

  Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.

  Language:Python1.7k238

• opensuh/DocumentBinarization

  Language:Python546

• VIROBO-15/UDBNET

  ICPR 2020 Official code repository of paper titled "UDBNET: Unsupervised Document Binarization Network via Adversarial Game"

  Language:Python63

• ajgallego/SAE-DANN

  Unsupervised neural domain adaptation for document image binarization

  Language:Python2

• sanakhamekhem/GAN-HTR

  This is an implementation for the paper Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement designed to enhance the document quality before the recognition process. It could be used for document cleaning and binarization. The weights are available to test the enhancement.

  Language:Python71