Pinned Repositories
ASTGCN
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019
darknet
Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection (Tensor Cores are used)
DCRNN
Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow
deep_sort
Simple Online Realtime Tracking with a Deep Association Metric
deep_sort_yolov3
Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow
GMAN
GMAN
Graph-WaveNet
graph wavenet
GraphSAGE
Representation learning on large graphs using stochastic graph convolutions.
keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
vehicle_counting_tensorflow
"MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
captainsparrow11's Repositories
captainsparrow11/vehicle_counting_tensorflow
"MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
captainsparrow11/ASTGCN
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019
captainsparrow11/darknet
Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection (Tensor Cores are used)
captainsparrow11/DCRNN
Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow
captainsparrow11/deep_sort
Simple Online Realtime Tracking with a Deep Association Metric
captainsparrow11/deep_sort_yolov3
Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow
captainsparrow11/GMAN
GMAN
captainsparrow11/Graph-WaveNet
graph wavenet
captainsparrow11/GraphSAGE
Representation learning on large graphs using stochastic graph convolutions.
captainsparrow11/keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
captainsparrow11/Object-Detection-and-Tracking
YOLO & RCNN Object Detection and Multi-Object Tracking
captainsparrow11/Real-Time-Detection-and-Classification-of-Vehicles-and-Pedestrians-Using-Haar-Cascade-Classifier
Real Time Detection and Classification of Vehicles and Pedestrians Using Haar Cascade Classifier with Background Subtraction
captainsparrow11/Speed-Estimation-of-Vehicles-with-Plate-Detection
The main objective of this project is to identify overspeed vehicles, using Deep Learning and Machine Learning Algorithms. After acquisition of series of images from the video, trucks are detected using Haar Cascade Classifier. The model for the classifier is trained using lots of positive and negative images to make an XML file. This is followed by tracking down the vehicles and estimating their speeds with the help of their respective locations, ppm (pixels per meter) and fps (frames per second). Now, the cropped images of the identified trucks are sent for License Plate detection. The CCA (Connected Component Analysis) assists in Number Plate detection and Characters Segmentation. The SVC model is trained using characters images (20X20) and to increase the accuracy, 4 cross fold validation (Machine Learning) is also done. This model aids in recognizing the segmented characters. After recognition, the calculated speed of the trucks is fed into an excel sheet along with their license plate numbers. These trucks are also assigned some IDs to generate a systematized database.
captainsparrow11/ST-MetaNet
The codes and data of paper "Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning"
captainsparrow11/STGCN
implementation of STGCN for traffic prediction in IJCAI2018
captainsparrow11/STGCN_IJCAI-18
Spatio-Temporal Graph Convolutional Networks
captainsparrow11/T-GCN
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
captainsparrow11/T-GCN-Pytorch
captainsparrow11/tensorflow_object_counting_api
🚀 The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems!
captainsparrow11/test
captainsparrow11/Traffic-speed-forecast
XGBRegressor and T-GCN for traffic speed prediction
captainsparrow11/Vehicle-And-Pedestrian-Detection-Using-Haar-Cascades
Real Time Detection and Classification of Vehicles and Pedestrians Using Haar Cascade Classifier
captainsparrow11/Vehicle-and-Speed-Identification
Detecting Cars in real time and identifying the speed of cars and tracking
captainsparrow11/vehicle-speed-check
Vehicle Speed Check
captainsparrow11/vehicle_counting_and_classification
Tracks vehicles, classifies as moving up or down, estimates the speed of the vehicles within a boundary and finally predicts the type of the vehicle as light-, heavy-weight, or motor vehicle.
captainsparrow11/Vehicle_Detection
Using the OpenCV framework in Python to detect vehicles from a video stream, dataset trained with the help of Haar Cascade classifier.
captainsparrow11/yolo3-keras
这是一个yolo3-keras的源码，可以用于训练自己的模型。
captainsparrow11/yolo3-training-keras-master
YOLOv3 training with own data on GPU. A Keras implementation of YOLOv3
captainsparrow11/yolov3_deepsort
Object tracking implemented with YOLOv3, Deep Sort and Tensorflow.