m-peker

m-peker's Stars

• fastapi/fastapi

  FastAPI framework, high performance, easy to learn, fast to code, ready for production

  Language:Python76.3k6783.4k6.4k

• ultralytics/yolov3

  YOLOv3 in PyTorch > ONNX > CoreML > TFLite

  Language:Python10.2k1561.8k3.4k

• Megvii-BaseDetection/YOLOX

  YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

  Language:Python9.4k761.5k2.2k

• david8862/keras-YOLOv3-model-set

  end-to-end YOLOv4/v3/v2 object detection pipeline, implemented on tf.keras with different technologies

  Language:Python63918244221

• dataloop-ai/AutoML

  ZazuML - easy AutoML for Object Detection

  Language:Python33623744

• alexattia/ExtendedTinyFaces

  Detecting and counting small objects - Analysis, review and application to counting

  Language:Jupyter Notebook19914967

• mavoll/MotionPathsExtraction

  Approach to extract motion paths (trajectories) of vehicles and pedestrians from videos (Multiple object detection & tracking)

  Language:Python717122

• ankit1khare/Smart-Park-with-YOLO-V3

  Maintaining empty parking spot count using YOLO real-time vehicle detection. Code readily runnable in google colab.

  Language:Python655545

• takyamamoto/Fixation-Densitymap

  Generate Heatmaps from eye tracking data

  Language:Python321210

• siddhantmaharana/counting-objects

  This project aims to count the retail objects present in the image. It uses OpenCV and Deep Learning models to count the images

  Language:Jupyter Notebook26007

• hpc203/YOLObile-opencv-dnn

  使用opencv的dnn模块做YOLObile的目标检测

  Language:Python17124

• Muhamob/Simple-Python-heatmap

  heatmap using OpenCV and Python

  Language:Python15108

• abdoghareeb46/license-plate-recognition-system

  license plate recognition system will work with camera to identify the plate number of the car that tries to enter the parking lot, and also check if the car allowed/not allowed to enter by checking the DB of the system.

  Language:CSS11114

• thesagarsehgal/Abandoned-Object-Detection

  Detects abandoned objects in a video, particularly useful for identifying suspicious abandoned luggage in railway stations and bus stands.

  Language:MATLAB10003

• prashantksharma/ee763

  Drone Surveillance: Pedestrian Detection + neural network compression

  Language:Jupyter Notebook9403

• Sunmi-AI-Lab/head-detection-and-tracking

  Head detection and tracking

  9403

• ableabhinav/Fall-Alert

  Fall Detection of Person at Night (Using IR-based CCTV Cameras)

  Language:Python6201

• beingnothing/FaceTrack_by_MTCNN

  Face tracking based on MTCNN, including counting face, judging and cropping frontal face from video real time

  Language:Python6100

• rashidch/Elevator-Passenger-Counting-using-Yolov3

  Uisng Deep Sort + Yolov3 model Pretrained on COCO dataset for passenger detection and counting

  Language:Python5102

• gohurali/Lane_Vehicle_Detection

  Vehicle and Lane Detection using Hough Transforms and Sliding Window with ROI Proposals & HOG + SVM in C++ and Python

  Language:Jupyter Notebook4101

• jjxxmiin/MCCNN

  people counting

  Language:Python410

• huuthieu/Deep-Learning-based-Goods-Management

  Language:Jupyter Notebook3110

• lakshmanmallidi/AttendaceTrackingWithFaceRecognition

  Real Time Attendace tracking with camera using python and opencv. Uploading In and Out time into database and web portal for admin and users.

  Language:Python3002

• drmacsika/django_technical_challenge

  Here's a short technical challenge for the use of Django and Django Rest Frame work

  210

• Lyyoness/ALS-Exploratory-Data-Analysis

  In this project I present a concise overview of past attempts at brain-computer interface (BCI) communication with ALS patients and some of the hypotheses about why they have been unsuccessful to date. My project is an exploratory data analysis of 86 hours of current EEG data collected from a CLIS (completely locked-in state) ALS patient. The analysis is aimed at extracting cognitive activity in different frequency bands and observing their change over time. The goal of this is to identify cognitive measures that are stable enough to facilitate the identification of "high interest/high alertness" periods during which BCI communication with the patient is more likely to succeed. The preliminary results of the data analysis are presented and a follow-up experiment (currently in progress) is described.

  Language:Jupyter Notebook2210

• benoitLemoine/peopleCounting

  Language:Python1000

• DinushaISL/people_counting_demo_api

  people counting for night club

  Language:Python1101

• RodriguesLs/people-counting

  Language:Python1200

• SayakGiri/Extract-locations-form-a-text-using-NLP-

  People, places, and things—nouns—play a crucial role in language, conveying the sentence’s subject and often its object. Due to their importance, it’s often useful when processing text to try to identify nouns and use them in applications. This is known as either entity identification or named-entity recognition (NER). Entity Recognition is used in almost all application of NLP. As an example, suppose you have a list of reviews on mobile phones. Using NLP, you can extract different entities like company name, mobile phone model, price, place etc.

  Language:Jupyter Notebook1100

• setiadeepanshu01/Driver-Drowsiness-Detection

  Language:Python1000