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abnormal-behavior-detection-based-on-optical-flow-features

CSC2515-University of Toronto. This project applied computer vision and mechine learning methods aimed to detect abnormal behaved object in crowd, by Hanwen Liang and Haohan Li.

ccpd

[ECCV 2018] CCPD: a diverse and well-annotated dataset for license plate detection and recognition

dic

Digital image correlation method, also known as digital speckle correlation method, It is the two digital images before and after the specimen is deformed, and the deformation information of the region of interest is obtained through related calculations. Because this method has extremely loose requirements for the experimental environment, and has the advantages of full-field measurement, strong anti-interference ability, and high measurement accuracy.

models

Models and examples built with TensorFlow

mudic

Digital Image Correlation in Python

plate

project-based-learning

Curated list of project-based tutorials

python-programming-exercises

100+ Python challenging programming exercises

traffic-survalance-with-computer-vision-and-deep-learning

The system takes video footage of a highway as input and provides statistics like the count of vehicles and an average estimated speed of vehicles on the highway. The statistics provided by the system can have many applications. Like, pricing the billboards on a highway for advertisement, higher the count of vehicles, higher the price. Moreover, the government can use this statistic to know how many vehicles are entering a city each day. The system internally uses YOLO object detection algorithm for vehicle detection, followed by, Centroid Tracking algorithm for tracking the detected vehicles.

yolov3_deepsort

Object tracking implemented with YOLOv3, Deep Sort and Tensorflow.

yolox

YOLOX is a high-performance anchor-free YOLO. Exceeding yolov3~v5 with ONNX, TensorRT, ncnn, and Openvino supported.