FaceMask | FaceMask using XZIMG

I have two python3 file

#1 Facemask recognition (Deep Learning)

#2 QR Code scanner (Machine Learning)

Im using Raspberry Pi 3 B+ & 8 MP single Pi Cam

Both program does not have any connection, however I need to run both at the same time to detect someone who mask or not AND to scan QR code of user

The problem is I found conflict on pi camera because I only use one pi camera for two different program. Plus, facemask using videostream while QR Scan using videocaptures.

Hope someone can help me on pi camera conflict with two python3 file that using it.

Below is my code:

#1 Facemask Recognition based on Github

https://github.com/manish-1305/facemask_detection/blob/73f37f724b519731eec7d46cb4a23482147db24b/detect.py

#2 QR Code Scanner

It says to do:

After detecting a face with CameraX and MLKit I need to pass the image to a custom TFLite model (I'm using this one), which detects a facemask. The model accepts images of 224x224 pixels, so I need to take out the part of ImageProxy#getImage() corresponding to Face#getBoundingBox() and resize it accordingly.

I've seen this answer which could have been fine but ThumbnailUtils.extractThumbnail() can't work with a Rect of 4 coordinates and it's relative to the center of the image, while the face's bounding box might be elsewhere.

The TFLite model accepts inputs like this:

So I was reading this guide about object detector training. It is instructed to change step size to 80% and 90% of the maximum batch size. Can someone explain what this step size is? And how it impacts the training. And also why specifically 80 and 90 percent.

Thanks

I have data in elasticsearch fields which contains "face mask", I am able to fetch this data with the following query with search_term set to "face", "face mask", "mask" and "face masks".

Hi I would like to know any method that Im able to use to extract only the ‘result’ part of it into a txt file. The payload is extracted from a POST Request from a device to my own server. Example:

I am using Anaconda Spyder 4.0.1, 64-bit windows and TensorFlow version 2.0. I am trying to follow this tutorial (https://www.pyimagesearch.com/2020/05/04/covid-19-face-mask-detector-with-opencv-keras-tensorflow-and-deep-learning/), in order to detect the person with and without a facemask. I am trying to generate a classifier file, it is giving me this error.

Hi I have an 8GB file which I need to do some analysis. However my RAM is not that great. To efficiently work, I decided to split my csv file based on rows with following code:

I have a neural network that outputs segments of a face - I'm working on a function that combines these segments together and then clones them into a real face.

Example images are here: https://imgur.com/a/HnpqhEE, I do not have the reputation to include them inline.

So far my function takes the makeup face and lips segment and combines them with addition. The left and right eyes are then cloned in with seamlessClone (the right eye is flipped first). Then the combined makeup segments are cloned into the normal face.

Very occasionally, my combination function fails and returns a (-215:Assertion failed) 0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols && 0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows in function 'cv::Mat::Mat' error.

My function is below, I have only seen it error at the last seamlessClone