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#dotnet – Detecting Faces using Cascades from the 🎦 camera feed in a WinForm using #OpenCV and #net5
Hi ! Let’s do some face detection using one of the most popular methods: Haar Casacades (See references). I won’t write about Cascades, there are almost 20 years of online documentation available. And, IMHO opinion code is much more useful that long writing, so let’s go there. 1st load the cascade definition file. And, once… — read more
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#dotnet – Display the 🎦 camera feed in a WinForm using #OpenCV and #net5
Hi ! Back on the Windows Forms days, cameras were tricky. We didn’t have a lot of libraries to work, and they usually require some extra work to handle unexpected errors. With Net 5 and OpenCVSharp, we can create a simple WebCam viewer like this one. Let’s start with a [Take a Photo] Windows Form… — read more
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#dotnet – detecting corners on the 🎦 camera feed with FAST algorithm, #OpenCV and #net5
Hi ! Today is a quick one: FAST corner detection algorithm. FAST (Features from Accelerated Segment Test) algorithm was proposed by Edward Rosten and Tom Drummond in their paper “Machine learning for high-speed corner detection” in 2006 (Later revised it in 2010). A basic summary of the algorithm is presented below. Refer original paper for… — read more
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#dotnet – detecting edges on the 🎦 camera feed with Canny algorithm, #OpenCV and #net5
Hi ! The Canny edge detection is one the most popular algorithms, and it’s also +30 years old. The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. It was developed by John F. Canny in 1986. OpenCV includes the Canny algorithm… — read more
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#dotnet – less than 20 lines to display a 🎦 camera feed with #OpenCV and #net5
Hi ! This post is the start of a series of posts around OpenCV and DotNet Core .Net 5. Most of my samples are going to be camera based, so I’ll start with the +20 13 lines needed to access a local camera and show the frames in a window. And the code using Net… — read more
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#AI – #Lobe, exporting to ONNX, and running in C# #csharp @lobe_ai
Hi ! Follow up post after yesterday post on Lobe, and today focusing on ONNX and C# code. And, it all started because someone asked in twitter about an ETA to export the model to ONNX I decided to give a try to the TensorFlow to Onnx tool, and it worked great ! (see references).… — read more
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#Python – Creating GUIs with #PySimpleGUI. 2 webcams view with 50 lines of code
Hi ! Working with Computer Vision is super fun. And there are some scenarios where display the step by step of the processing of an image is the best way to present this. In most of my scenarios I use OpenCV, however for a more detailed presentation I needed to search and learn a GUI… — read more
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#Python – #FastAPI Webserver sharing information from values in a different thread
Hi ! After my yesterday post using Flask, I was sure that a FastAPI version will be needed, so here it goes: I have a common scenario which involves: A sensor collecting information A web-server publishing the sensor information Read my previous posts to understand why I think this is the simple way to solve… — read more
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#Python – Flask Webserver sharing information from values in a different thread
Hi ! I have a common scenario which involves: A sensor collecting information A web-server publishing the sensor information This is simple, however the sensor does not support constants requests, and it may return a “too many requests” response when called directly. The idea to get the sensor information directly in the web-request was not… — read more
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#ComputerVision – Object Detection with #YoloV3 and #MobileNetSSD
Hi ! I have a ToDo in my list, to add some new drone demos. In order to do this, I was planning to perform some tests with pretrained models and use them. The 1st 2 in my list are Yolo and MobileNetSSD (see references). YoloV3 Let’s start with one of the most popular object… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (21/N)
Hi ! In my post series I already wrote about how to detect faces. We can do this with a camera and OpenCV. However, a drone can also be moved on command, so let’s write some lines to detect a face, and calculate the orientation and distance of the detected face from the center camera… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (20/N)
Hi ! We already have the drone camera feed ready to process, so let’s do some Image Segmentation today. As usual, let’s start with the formal definition of Image Segmentation In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (18/N)
Hi ! Today I’ll step back a couple of posts, and add 2 simple lines to allow me to save a video file from the Drone camera. This is a request, and it’s makes a lot of sense to have recorded a file with the drone camera. The video will later contains detected objects and… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (17/N)
Hi ! Once we have the a custom vision trained model instance, we can use it to recognize objects from the drone camera feed. Read my previous posts for descriptions on these. Another interesting scenario, is to save local files for every detected object. In the following code, I’ll save 2 different files for every… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (16/N)
Hi ! In my previous post, I shared an example where I analyzed the camera feed using a Image Recognition model created using Custom Vision. Today I’ll expand the sample, and show in real time the detected MVPs logos with a frame in the drone camera feed. Let’s take a look at the demo working… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (15/N)
Hi ! Let’s use Custom Vision to analyze the images from our drone camera. In this scenario, I created a custom model to recognize MVP awards from my MVP wall. I know, that’s bragging, but I like it. Disclaimer: There are plenty of documentation and tutorials about Custom Vision. I won’t go deep on the… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (12/N)
Hi! Today code objective is very simple, based on a request I received from internet: The drone is flying very happy, but if the camera detects a face, the drone will flip out ! Let’s take a look at the program working: This one is very similar to the previous one. I also realized that… — read more
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#Coding4Fun – How to control your #drone with 20 lines of code! (11/N)
Hi! Today code objective is very simple: The drone is flying very happy, but if the camera detects a banana, the drone must land ! Let’s take a look at the program working: And a couple of notes regarding the app Still use Haar Cascades for object detection. I found an article with a Xml… — read more
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El Bruno 