![]() ![]() I tried with the CPU-only mode but I could not get a real-time result (my computer almost crashed). ![]() It can also do real-time object recognition but requires a GPU to do it efficiently. It allows us to do post-processing object detection for still pictures and videos. I found quite an interesing piece of work for object detection by using Neural Networks. I also searched for more related software which could possibly provide an alternative to the face recognition. For now, however, some manual work needed to be done in order to add more datasets (images of faces) if you want to use the code right away. My daughter Aufa is joining me in this facial recognition session.Īpart from that there is also a fork on GitHub which allows us to do the real-time face recognition. If the code provided in the video isn’t working directly, you could try my small patches, in which I corrected a typo and extended the filename extensions towards the source file from here. I found one tutorial which explained clearly how we could get the face recognition working from the web camera, in real time. I continued my search for existing face recognition software and found several projects which could be tested right away, with some modifications from the original source. For example, in the facial regcognition tools, the training file contains the following matrices: opencv_lbphfaces:ĭata: ĭata: [ 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 4, 4, 4, 4, 5, 5, 5, 5, 5, ![]() The computer doesn’t see the image directly as the humans seem to, so we need to convert the images into numerical values. Makan-small.jpg: JPEG image data, JFIF standard 1.01, resolution (DPI), density 72x72, segment length 16, Exif Standard:, baseline, precision 8, 640x480, frames 3 $ convert makan.jpg -resize 640x480 makan-small.jpg Makan.jpg: JPEG image data, JFIF standard 1.01, aspect ratio, density 1x1, segment length 16, Exif Standard:, baseline, precision 8, 4160x3120, frames 3 You can use ImageMagick to resize the file to say, 640x480 pixels. You might have noticed that if you use the image file that you import directly from your smartphone, the output will be displayed in a large file to the screen. How would the computer be able to recognize who’s who? Then I stumbled upon the phrase “face recognition”. So I was able to detect faces, but upon sharing the “findings” with a friend he said this only detects faces. I searched around for existing face detection software and found this Python script using Haarcascade. So I thought, what if I could use a web cam to monitor my door and let me know who’s actually standing at the door? Face Detection Since I am working at home, I want to know who is actually knocking my door. The reason I explored these tools is simple: I plan to deploy a poor man’s security camera in my home with some “sense” of intelligence. In this post I will share the existing tools and the associated libraries to make them work, at least for me. However, since I am not an expert in the field I decided to let the researchers and scholars elaborate more on them. I’m always impressed with the advancement of machine learning, and, more recently, deep learning. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |