zqcrafts

zqcrafts

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segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:47552Issues:308Issues:668

CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Language:Jupyter NotebookLicense:MITStargazers:25824Issues:323Issues:403

Qwen

The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.

Language:PythonLicense:Apache-2.0Stargazers:13995Issues:104Issues:1052

open_clip

An open source implementation of CLIP.

Language:PythonLicense:NOASSERTIONStargazers:10272Issues:78Issues:487

GroundingDINO

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

Language:PythonLicense:Apache-2.0Stargazers:6715Issues:42Issues:303

InternVL

[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型

Language:PythonLicense:MITStargazers:5969Issues:52Issues:604

efficient-kan

An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

Language:PythonLicense:MITStargazers:4074Issues:36Issues:39

reproducible-image-denoising-state-of-the-art

Collection of popular and reproducible image denoising works.

awesome-community-detection

A curated list of community detection research papers with implementations.

Language:PythonLicense:CC0-1.0Stargazers:2331Issues:110Issues:8

ml-4m

4M: Massively Multimodal Masked Modeling

Language:PythonLicense:Apache-2.0Stargazers:1602Issues:33Issues:21

SoM

Set-of-Mark Prompting for GPT-4V and LMMs

Language:PythonLicense:MITStargazers:1165Issues:22Issues:35

Grounded-SAM-2

Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:1060Issues:9Issues:49

SAM-Adapter-PyTorch

Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

Language:PythonLicense:MITStargazers:1043Issues:8Issues:95

Osprey

[CVPR2024] The code for "Osprey: Pixel Understanding with Visual Instruction Tuning"

Language:PythonLicense:Apache-2.0Stargazers:770Issues:14Issues:44

graphrag-local-ollama

Local models support for Microsoft's graphrag using ollama (llama3, mistral, gemma2 phi3)- LLM & Embedding extraction

Language:PythonLicense:MITStargazers:742Issues:9Issues:40

all-seeing

[ICLR 2024 & ECCV 2024] The All-Seeing Projects: Towards Panoptic Visual Recognition&Understanding and General Relation Comprehension of the Open World"

DINOv

[CVPR 2024] Official implementation of the paper "Visual In-context Learning"

Deblur-GS

[I3D 2024] Deblur-GS: 3D Gaussian Splatting from Camera Motion Blurred Images

Language:PythonLicense:NOASSERTIONStargazers:346Issues:6Issues:17

SAN

Open-vocabulary Semantic Segmentation

Language:PythonLicense:MITStargazers:314Issues:6Issues:59

SAMRS

The official repo for [NeurIPS'23] "SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model"

OmniCorpus

OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text

CAT-Seg

Official Implementation of "CAT-Seg🐱: Cost Aggregation for Open-Vocabulary Semantic Segmentation"

Language:PythonLicense:MITStargazers:247Issues:6Issues:37

AnyGraph

"AnyGraph: Graph Foundation Model in the Wild"

Language:PythonStargazers:185Issues:0Issues:0

xLSTM-UNet-PyTorch

Replacing Mamba with xLSTM! It works better. We show that xLSTM-Unet can be an effective semantic segmentation backbone.

Ant-Multi-Modal-Framework

Research Code for Multimodal-Cognition Team in Ant Group

Language:PythonLicense:CC-BY-4.0Stargazers:121Issues:4Issues:20

KGCL-SIGIR22

[SIGIR'22] Knowledge Graph Contrastive Learning for Recommendation

Language:PythonLicense:MITStargazers:105Issues:4Issues:24

Reason3D-PyTorch

Reasoning 3D Segmentation - "segment anything"/grounding/part seperation in 3D with natural conversations.

Language:PythonLicense:NOASSERTIONStargazers:75Issues:10Issues:1

CLAP

CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts

Language:PythonStargazers:42Issues:0Issues:0