object detectorObject detector from HOG + Linear SVM framework
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udacity-cvnd-projectsMy solutions to the projects assigned for the Udacity Computer Vision Nanodegree
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facial-landmarksFacial landmarks detection with OpenCV, Dlib, DNN
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rps-cvA Rock-Paper-Scissors game using computer vision and machine learning on Raspberry Pi
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BlurryFacesA tool to blur faces or other regions in images and videos 🤡🔍
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FaceRecogRealtime Facial recognition system using Siamese neural network
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Cnn Paper2🎨 🎨 深度学习 卷积神经网络教程 :图像识别,目标检测,语义分割,实例分割,人脸识别,神经风格转换,GAN等🎨🎨 https://dataxujing.github.io/CNN-paper2/
Stars: ✭ 77 (+234.78%)
Age-PredictionThis Project is an applicaton based on Computer vision and Machine learning implementation using regression supervised classification.
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lite.ai.toolkit🛠 A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOX, YOLOP, MODNet, YOLOR, NanoDet, YOLOX, SCRFD, YOLOX . MNN, NCNN, TNN, ONNXRuntime, CPU/GPU.
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Face-Detection-and-TrackingComputer Vision model to detect face in the first frame of a video and to continue tracking it in the rest of the video. This is implemented in OpenCV 3.3.0 and Python 2.7
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Insta flters with pythonWith this program you can add hat & glass on your face(it's support multiple faces)
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DSegInvariant Superpixel Features for Object Detection
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enhanced-ssh-mxnetThe MXNet Implementation of Enhanced SSH (ESSH) for Face Detection and Alignment
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U-Net-SatelliteRoad Detection from satellite images using U-Net.
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LEDNetThis is an unofficial implemention of LEDNet https://arxiv.org/abs/1905.02423
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Segmentation-Series-ChaosSummary and experiment includes basic segmentation, human segmentation, human or portrait matting for both image and video.
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HRFormerThis is an official implementation of our NeurIPS 2021 paper "HRFormer: High-Resolution Transformer for Dense Prediction".
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UCTransNetImplementation of our AAAI'22 work: 'UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer'.
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DigiPathAIDigital Pathology AI
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volkscvA Python toolbox for computer vision research and project
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LightNetLightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)
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MONAILabelMONAI Label is an intelligent open source image labeling and learning tool.
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EntityEntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
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Image ProcessingImage Processing techniques using OpenCV and Python.
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DeepVTB🌌 OpenVTuber-虚拟アイドル共享计划 An application of real-time face and gaze analyzation via deep nerual networks.
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opencv-steel-dartsAutomatic scoring system for steel darts using OpenCV, a Raspberry Pi 3 Model B and two webcams.
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pigalleryPiGallery: AI-powered Self-hosted Secure Multi-user Image Gallery and Detailed Image analysis using Machine Learning, EXIF Parsing and Geo Tagging
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pycv4rtspVideoCapture封装,读取rtsp的实时帧
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Dynamic ORB SLAM2Visual SLAM system that can identify and exclude dynamic objects.
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OpenCV-Anime-Face-DetectorUsing OpenCV to detect and mark face and eye features in videos and images. Anime and manga faces are also detected.
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Deep-LearningThis repo provides projects on deep-learning mainly using Tensorflow 2.0
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Z-Spider一些爬虫开发的技巧和案例
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shunyafaceFast Face Recognition on the edge
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Face-XDemonstration of different algorithms and operations on faces. Join the Discord channel for discussion.
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face detectionusing caffemode which is provided by shiqi yu
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CAPECylinder and Plane Extraction from Depth Cameras
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segmenter[ICCV2021] Official PyTorch implementation of Segmenter: Transformer for Semantic Segmentation
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MTCNN TRAINMTCNN_Training Scripts For Face Detection with PyTorch 0.4.0
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Lyrics-to-Audio-AlignmentAligns text (lyrics) with monophonic singing voice (audio). The algorithm uses structural segmentation to segment the audio into structures and then uses hidden markov models to obtain alignment within segments. The final alignment is concatenation of time stamps of lyrics within the segments for each song.
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GStreamer-PythonFetch RTSP Stream using GStreamer in Python and get image in Numpy
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mobilenet segmentationBinary semantic segmentation with UNet based on MobileNetV2 encoder
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