The Junkyard Cars are detected using HOG and SVM detector (from DLib library) trained on the dataset created from input video. The counting is done using normal python code in IDLE environment (Python 3.9.6). The input video has been resized to 720p as 1080p video couldn't be opened in opencv window for further processing. Yet, […]
Hello, I used OPENCV processing to detect the cars (bounding box) and euclidean distance tracker to detect ID and filter the bounding boxes. Thanks for the vote.
I used here YOLO version3 and tensor flow object detection api. I used Deep sort for tracking.
Here I have used yolo version 3 custom dataset model and for training I used tensor flow. For car counting I used Deep sort algorithm. I draw lines for counting car.
A YOLOv5 Model With Deepsort For Tracking
I have used opencv for detecting cars and canny edges detector for detecting edges. and i have used non max suppression for reducing overlapping boxes and centroid tracker for tracking and counting the cars. please vote for me.
Hi I am Afonso, and this is my attempt at the contest. I trained and used a yolov3 model with only a single class, Car, trained on this video. I then used deepsort to track all the objects and count them. To avoid over detections I only counted the cars which pass between the green […]
Hi I am Afonso, and this is my attempt at the contest. I trained and used a yolov3 model with only a single class, Car, trained on this video. I then used deepsort to track all the objects and count them. To avoid over detections I only count the cars which pass between the green […]
Tournament name: 'Drone Surveillance Contest'. Tournament task: to count and track the number of cars by drone passing over a junkyard. Drone Surveillance Counter Project steps: 1. Create an image dataset * Split the video into frames * Add new images data to prevent overfitting and achieve versatile performance * Perform augmentation to achieve the […]
Hi I am Ted, and this is my attempt at the contest. I trained and used a yolov3 model with only a single class, Car, trained on this video. I then used deepsort to track all the objects and count them. To avoid over detections I only count the cars which pass between the green […]
One Stop Computer vision
