Frozen Faces @ 4:20

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Thanks for the detailed explanations. I ran the above code on my laptop and it appears very slow, the webcam stream is almost frozen.

The compare method will compare each detected face with all the encodings, that will a lot of time for each frame i think. Please let me know your thoughts for the same. Additionally, you could use Haar cascades as well. Your blog, and the Practical Python and OpenCV system i purchased are really helping me become educated in this field! Thanks Bruce, I really appreciate that! Enjoy hacking with the code and always feel free to reach out if you have any questions. The Frames are frozen. I am using a i5 with 8gb ram. What should be hardware specifications for a decent real time face recognition sytem?

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Hey there Devarshi, make sure you read my reply to your original question. I have already answered it for you. Change the --detection-method to hog and it will run on your CPU. Thank you for this great tutarial. Which one of face recognition architectures you used in this tutarial?? I used the model discussed in the dlib library.

My laptop configuration is i7 processor with 8gb ram and 4GB graphics card It is working fine with hog. Can you please suggest how can i use CNN face detector with such configuration. It looks like your machine is running out of memory. I noticed that cnn takes a long time and appears to only be using one thread.

I received this error also — I just needed to put the full path name in for the input image file and it worked fine. Your GPU itself is likely running out of memory as it cannot hold both 1 the face detector and 2 the encoding model.

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NB Took me about 5 attempts to get Ubuntu up and running and I can still dual boot to Windows 10 if needed. They are two totally different techniques used for two totally different applications. The Inception network is used for typically image classification. The network here is used to compute a d quantification of a face.

‘I ran out at 4:20’: Canada faces weed shortages one day after legalization

Double-check your command line arguments. I believe the path to your input --image path is incorrect. If it the path does not exist, the cv2. Hi Adrian i test this with dlib without gpu and i was getting low fps,so i installed dlib with gpu and again low fps so how to use hog or other for better fps. Sorry for asking i am beginer. Hey Kubet — what type of GPU are you using? Can you confirm that dlib is actually accessing your GPU? I tried with HOG for face detection and it is still significantly slow compared to the other two face recognition programs you posted.

However, I believe this is the most accurate one among the three approaches Please correct me if I am wrong. Also, I am wondering if it is possible to use Movidius Neural Compute stick to speed up this program or the other 2 approaches? The deep learning-based face detector will be the slowest but most accurate.

Haar cascades will be faster but less accurate. HOG is a middle ground between the two. Your machine is running out of memory and it cannot load the CNN. You would need to use the HOG method. You would need to install OpenCV and dlib into your Anaconda environment. OpenCV should be available from the standard Anaconda repo. Both dlib and imutils are pip-installable as well. Double-check your output and ensure there are no errors.

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Why when running last code, on the video file, my MAC is moving soo slow. Is like time stad still. Thank you Adrian! Please read the other comments. Adrian, I am wondering if you have experience with cloning the virtual environment?

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I looked at the pip freeze and requirements. If I am off track on this just let me know. I am thinking ahead to other projects with out having completing this one I know. Instead, I recommend using a pip freeze and requirements. You would need to either 1 recompile or reinstall or 2 my preferred method, sym-link the libraries into the site-packages directory of the new virtual environment.

Hello, the articles you publish are very useful even for beginners like me. Thanks in advance. Be sure to keep an eye out for the post! Guess you made my day!!!!

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  8. Spent a day and a half compiling dlib without result, when i saw your post. Think it works now. Jesus this is a tutorial with a lot of depth. Thank you for that! I have used HOG detection method to speed up the face detection method and its working fine. You would want to 1 have a GPU and 2 install and configure dlib with GPU support this post demonstrates how, refer to the install instructions.

    Thank for great tutorial, my bro! I installed dlib use GPU. Thank so much. If you are using another GPU you should refer to the docs for it.

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    My syntax: — nvidia-smi. Are you using Windows? I am presently running with one issue.