naseemap47

naseemap47's Stars

• AILab-CVC/YOLO-World

  [CVPR 2024] Real-Time Open-Vocabulary Object Detection

  Language:Python4.4k427

• WongKinYiu/yolov9

  Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

  Language:Python8.9k1.4k

• damiafuentes/DJITelloPy

  DJI Tello drone python interface using the official Tello SDK. Feel free to contribute!

  Language:Python1.2k491

• lucidrains/gigagan-pytorch

  Implementation of GigaGAN, new SOTA GAN out of Adobe. Culmination of nearly a decade of research into GANs

  Language:Python1.8k103

• naseemap47/ImageRestoration-Streamlit

  Restore image using NAFNet model with streamlit dashboard

  Language:Python81

• megvii-research/NAFNet

  The state-of-the-art image restoration model without nonlinear activation functions.

  Language:Python2.2k266

• ifzhang/ByteTrack

  [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box

  Language:Python4.7k886

• naseemap47/Streamlit-GroundingDINO

  Dashboard for Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

  Language:Jupyter Notebook5

• naseemap47/PoseClassifier-yolo

  Classify human poses with help of yolo pose model.

  Language:Python87

• obss/sahi

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

  Language:Python4k577

• roboflow/notebooks

  Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

  Language:Jupyter Notebook5.2k806

• autodistill/autodistill

  Images to inference with no labeling (use foundation models to train supervised models).

  Language:Python1.9k147

• KDE/kdenlive

  Free and open source video editor, based on MLT Framework and KDE Frameworks

  Language:C++3.1k262

• OpenGVLab/DragGAN

  Unofficial Implementation of DragGAN - "Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold" （DragGAN 全功能实现，在线Demo，本地部署试用，代码、模型已全部开源，支持Windows, macOS, Linux）

  Language:Python5k492

• Deci-AI/super-gradients

  Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

  Language:Jupyter Notebook4.5k495

• naseemap47/DETR

  Detection Transformer (DETR) is an end-to-end object detection model implemented using the Transformer architecture.

  Language:Python1

• naseemap47/YOLO-NAS

  Train and Inference your custom YOLO-NAS model by Single Command Line

  Language:Python9813

• naseemap47/streamlit-yolov5

  Display predicted Video, Images and webcam using YOLO5 models with Streamlit

  Language:Python2

• IDEA-Research/GroundingDINO

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

  Language:Python6.3k656

• ultralytics/yolov5

  YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

  Language:Python49.8k16.1k

• naseemap47/Custom-MoViNet

  Create your own custom MoViNet model using your custom data. You can train and inference from "a single of code".

  Language:Python71

• r1c7/SlowFastNetworks

  PyTorch implementation of "SlowFast Networks for Video Recognition".

  Language:Python33880

• WongKinYiu/yolov7

  Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

  Language:Jupyter Notebook13.2k4.2k

• marcoslucianops/DeepStream-Yolo

  NVIDIA DeepStream SDK 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models

  Language:C++1.4k357

• ultralytics/ultralytics

  NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

  Language:Python28.6k5.7k

• RizwanMunawar/yolov7-pose-estimation

  YOLOv7 Pose estimation using OpenCV, PyTorch

  Language:Python33678

• NVIDIA-AI-IOT/deepstream_python_apps

  DeepStream SDK Python bindings and sample applications

  Language:Jupyter Notebook1.4k472

• metal3d/keras-video-generators

  Keras generators to generate sequences from videos as input

  Language:Jupyter Notebook9932

• tryolabs/norfair

  Lightweight Python library for adding real-time multi-object tracking to any detector.

  Language:Python2.4k240

• bluenviron/mediamtx

  Ready-to-use SRT / WebRTC / RTSP / RTMP / LL-HLS media server and media proxy that allows to read, publish, proxy, record and playback video and audio streams.

  Language:Go11.7k1.5k