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I want to build face recognition door. Can someone help me with the flow chat and the necessary things that will enable me carry out the project.
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Is that a "real" door or a "portal"? If it is a real door, does if have a lock? A camera? Both?
"Before entering on an understanding, I have meditated for a long time, and have foreseen what might happen. It is not genius which reveals to me suddenly, secretly, what I have to say or to do in a circumstance unexpected by other people; it is reflection, it is meditation." - Napoleon I
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I have blueiris + codeproject successfully detecting faces and putting them in a folder.
I then go into the explorer/vision tool, attempt to do the registration, and on the 3 or 4 images i did as a test each time it says operation failed. The images dont seem bad just a little fuzzy or grainy.
How do you troubleshoot this error? Or what could it mean
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I've got a real mess with my install, i've tried removing it, restarting, reinstalling to no avail.
Then if i try to install a module again, it will error out and say it already exists or give me a "python not installed" error.. i look in the runtimes and i see python in both paths (not sure why there are two). Specifically this python error came from trying to install ObjectDetection (YOLOv5.NET)
If i try another module to instsall, it says installed successfully, but then "unable to start newly installed module" "unknown response from the server"
Also, if i remove everything start over, try face processing module, i get this
11:26:33:FaceProcessing: Installing python.= in C:\Program Files\CodeProject\AI\runtimes\bin\windows\python.=
11:26:34:FaceProcessing: Start-BitsTransfer : HTTP status 403: The client does not have sufficient access rights to the requested server object.
modified 16-Sep-23 11:28am.
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That link doesnt work, this is the AI forum?
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Yes, that link does work, and that is the correct place for questions about the CodeProject AI server. This forum is for general questions on Artificial Intelligence, which is not the same thing.
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Quote: Do not try and find the page. That’s impossible. Instead only try to realise the truth
It's a "2 part" link ... this is what happens if you click on the "first part".
"Before entering on an understanding, I have meditated for a long time, and have foreseen what might happen. It is not genius which reveals to me suddenly, secretly, what I have to say or to do in a circumstance unexpected by other people; it is reflection, it is meditation." - Napoleon I
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Thanks Gerry. It appears there was a space in the first part that did not belong there; now fixed.
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My apologies, part of the link had a typo that I was not aware of. I have corrected it and it now works.
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I am running latest Blue Iris version with Codeproject AI 2.1.9. I only had the Yolo Net module installed (V1.4). This morning I saw an update to 1.5 of Yolo.Net so I installed it. Now no object detection and custom models show nothing. When I click to browse it says to refresh AI list. How can I resolve this issue?
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Getting this lovely error
24:36:00:
24:36:00:Started Face Processing module
24:36:00:face.py: Traceback (most recent call last):
24:36:00:face.py: File "C:\Program Files\CodeProject\AI\modules\FaceProcessing\intelligencelayer\face.py", line 21, in
24:36:00:face.py: from request_data import RequestData
24:36:00:face.py: File "../../SDK/Python\request_data.py", line 8, in
24:36:00:face.py: from PIL import Image
24:36:00:face.py: ModuleNotFoundError: No module named 'PIL'
24:36:00:Module FaceProcessing has shutdown
24:36:00:face.py: has exited
I know PIL is not supported anymore and you have to use Pillow now, but I am also new to Python so I'm pretty lost when I try to install it or set it up.
What I have tried:
Tried re-installing codeproject server.
Tried installing python from the website and then pip installing Pillow.
Tried installing Pillow through Anaconda.
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I have data in two columns, X and Y where the function Y changes for increasing values of the X variable. If Y shows variations with X, the simplest way to do this is by fitting the data with a linear function.(In python), but I am looking for some "advanced" strategy (other than linear regression, i.e., using Neural Networks or other machine learning techniques) to elaborate on these data because i also want to find pattern in it. Need guidance .
modified 9-Aug-23 13:21pm.
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Stop reposting the same question all over the site. ONCE in QA is enough.
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To be fair, Andre did tell him to repost it here. 
"These people looked deep within my soul and assigned me a number based on the order in which I joined."
- Homer
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Thanks, I made the suggestion as it is an AI related question.
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I wasn't aware that Q&A was "non-AI" related. It's a poor "AI question" to start with, and the whole concept of "moving the question" has made this painful.
"Before entering on an understanding, I have meditated for a long time, and have foreseen what might happen. It is not genius which reveals to me suddenly, secretly, what I have to say or to do in a circumstance unexpected by other people; it is reflection, it is meditation." - Napoleon I
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Hi Gerry, I followed suit as the more experienced posters tend to send al AI questions to the AI forum because, like I do, we tend to think that a better answer or response will be achieved there than in the Q&A.
I will refrain from making the suggestion again.
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The redirects are usually to people who post questions relating to the CodeProject AI, and we point them to the CodeProject.AI Discussions[^] forum, rather than the general AI one here. And yes, I agree it can be confusing.
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This is not remotely in my field of expertise, I decided to ask AI about an AI question. Please check and confirm each suggestion as it is commonly known that false values are given by ChatGPT in certain scenarios. Suggestions given by ChatGPT -
You can explore more advanced techniques like polynomial regression, decision trees, random forests, support vector machines, and neural networks.
Polynomial Regression: This involves fitting a polynomial equation to the data, allowing for curved relationships between X and Y. You can experiment with different polynomial degrees to capture varying degrees of complexity.
Decision Trees and Random Forests: Decision trees split the data based on different conditions and can handle both linear and non-linear relationships. Random forests are an ensemble of decision trees that can handle complex relationships more effectively.
Support Vector Machines (SVM): SVMs are good for both linear and non-linear patterns. They aim to find a hyperplane that best separates the data while considering a "kernel trick" to map the data into a higher-dimensional space for better separation.
Neural Networks: Neural networks are capable of capturing complex patterns and relationships in data. You can design a network with multiple layers and nodes to model intricate non-linear connections between X and Y.
Gradient Boosting: This ensemble technique combines multiple weak learners (usually decision trees) to create a strong predictive model. It's powerful for capturing complex relationships.
K-Nearest Neighbors (KNN): This instance-based learning algorithm uses nearby data points to predict the value of a new point. It can capture local patterns that may not be apparent with global models.
Clustering Algorithms: If you're interested in discovering inherent patterns in your data without a specific Y variable, clustering techniques like k-means or hierarchical clustering might be useful.
Feature Engineering: Transform your features (X variables) to create new ones that might capture complex relationships more effectively. This might involve interactions, logarithmic transformations, or other functions.
Time Series Analysis: If your data has a temporal component, time series techniques like ARIMA (AutoRegressive Integrated Moving Average) or LSTM (Long Short-Term Memory) networks could be useful.
Dimensionality Reduction: Techniques like Principal Component Analysis (PCA) or t-SNE (t-Distributed Stochastic Neighbor Embedding) can help you visualize and analyze high-dimensional data.
Remember that selecting the best technique depends on your specific data and problem. Experiment with different methods, possibly even combining some, to see which one works best for uncovering the patterns you're interested in. Also, don't forget to split your data into training and testing sets to evaluate the performance of each technique accurately.
End of ChatGPT, I hope this points you in the right direction.
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great answer, thanks !
when can i enroll in your classes ?
cheers, Bill
«The mind is not a vessel to be filled but a fire to be kindled» Plutarch
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