Artificial Intelligence

The Quick OAK on Raspberry Pi Installation Procedure Go over to https://docs.luxonis.com/api/#python_version and follow the instructions there If you run into any issues, then upgrade pip python3 -m pip install -U pip python3 -m pip install -r requirements.txt 3. To install OpenCV manually follow instructions here https://www.raspberrypi.org/forums/viewtopic.php?t=232294 or execute the following commands. sudo pip3 install opencv-python sudo apt-get install libcblas-dev sudo apt-get install libhdf5-dev sudo apt-get install libhdf5-serial-dev sudo apt-get install libatlas-base-dev sudo apt-get install libjasper-dev sudo apt-get install libqtgui4 sudo apt-get install libqt4-test 4. Connect your device and try python3 test.py If you are interested in Enrolling in my upcoming course on YOLOv4 and OAK then sign up over here when it gets released - Click Here Source : https://augmentedstartups.info/yolov4release

NVIDIA launched its new member for the Jetson class of smaller processing units - the Jetson Xavier NX . The size of the entire setup is smaller than a normal sized debit or credit card. The module although not the smallest in business but more than makes up for its size with the processing capabilities and other qualities that it has to offer. The earlier launches like Jetson Nano, the smallest GPU based device, will also have its compatibility with the latest Xavier NX with the pin compatibility making it possible to port the AIoT applications deployed on the Nano. The new device has been launched to ensure compatibility with all major AI frameworks , including the likes of PyTorch [1] , TensorFlow [2] etc. Jetsons Xavier NX Attributes of Xavier NX NVIDIA’s website [3] claims that the new device is capable of delivering upto 14 terra operations per seconds [4] also known as TOPS with the power consumption of 10W, with the power consumption of 15W it is capable of doing 21 TOPS, ma...

MS Vision AI Kit vs Deep Lens Introduction Artificial intelligence has glorified many sections of recent times and among them, one of the most notable ones is the computer vision . Computer vision-based AI can have significant contributions in the classification of specific images, object detection, and segmentation and all of that can be used directly or indirectly in consumer aspects. From face recognition in verifying user identity to digital number plate detection in vehicles, computer vision is playing a significant role and undeniably gaining much popularity. Algorithms Neural networks and some specific deep learning algorithms are the most important constituents of the computer vision. Among those algorithms, CNN 's, GAN 's, and SSD 's are notable. For a newbie or even for an average skilled machine learning developer the Convolutional Neural Network (CNN) is one of the most complex sections. CNNs are not only complex to understand but also they have some spec...

Lately, there has been a lot of talk regarding the possibility of machines learning to do what human beings do in factories, homes, and offices. With the advancement in artificial intelligence , there has been widespread fear and excitement about what AI, machine learning, and deep learning is capable of doing. What is really cool is that Deep Learning and AI models are making their way from the cloud and bulky desktops to smaller and lower powered hardware. In this article, we will help you understand the strengths and weaknesses about three of the most dominant deep learning AI hardware platforms out there. The Intel Movidius Neural Compute Stick (NCS) with Raspberry Pi Developed by Intel Corporation, the Movidius Neural Compute Stick can efficiently operate without an active internet connection. Its computing capabilities come from the Myriad 2 Vision Processing Unit (VPU) . It offers profiling, tuning, and compiling a Deep Neural Network (DNN) on a development computer with the ri...