- 10月 22 週二 202409:44
Increase OpenCV speed by 2x with Python and Multithreading | Tutorial
- 10月 17 週四 202407:54
ArUco marker Detection
Basic-Augmented-reality-course-opencv
- 11月 27 週一 202311:10
Open Source Motion Capture for Autonomous Drones
室內無人機結合3D空間定位及追蹤
- 11月 18 週六 202309:06
ffmpeg轉檔
查詢影片FPS(frames per second)
(base) C:\ffmpeg>ffmpeg -i cam1.avi 2>&1 | findstr "fps"
調整影片FPS = 5.99
(base) C:\ffmpeg>ffmpeg -i cam1.avi 2>&1 | findstr "fps"
調整影片FPS = 5.99
- 8月 12 週五 202210:49
安裝darknet yolov4
開啟 darknet
CUDA >= 10.2
- 8月 12 週五 202209:57
安裝OpenCV 4.6.0 + OpenCV contrib
到OpenCV github下載OpenCV
點選tags
- 6月 08 週三 202210:02
Case study
FFT spectrum amplitude using median filters with different kernel sizes
ex13_socre_median_filters.py
FFT spectrum amplitude using different filters, including median filter, moving average filter, and Laplacian filter.
- 5月 27 週五 202209:21
Unity is not as hard as I thought before
Unity is not as hard as I thought, although I am a newbie in this field. I believe my little step leads me to the future. After a day of playing in the Unity world for the first time. I felt great when I finished a small project. In this project, I tried to integrate EmguCV, which is a wrapped OpenCV for .net framework, into the Unity C# program and did a simple face detection. Each face's location represents an NBA player's position. For example, Stephen Curry is corresponding to face #0, Lebron James is face #1, and Ja Morant is face #2. As the video plays, all the NBA players can move to the locations according to their face numbers.
It's so fun for the beginner, isn't it?
- 3月 26 週六 202220:45
Camera Calibrartion
1. Camera calibration with square chessboard
2. Real Time pose estimation of a textured object
