Linkedin - Computer Vision on the Raspberry Pi 4

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[ CourseLala.com ] Linkedin - Computer Vision on the Raspberry Pi 4
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    • Bonus Resources.txt (0.3 KB)
      • [1] Introduction
      • [1] Getting started with computer vision.mp4 (4.3 MB)
      • [1] Getting started with computer vision.srt (1.5 KB)
      • [2] What you should know.mp4 (2.7 MB)
      • [2] What you should know.srt (1.4 KB)
      • [3] Using the exercise files.mp4 (5.8 MB)
      • [3] Using the exercise files.srt (3.2 KB)
      [2] 1. Programming Python on the Raspberry Pi 4
      • [1] Introducing the Raspberry Pi 4.mp4 (9.8 MB)
      • [1] Introducing the Raspberry Pi 4.srt (5.7 KB)
      • [2] Setting up the environment.mp4 (12.5 MB)
      • [2] Setting up the environment.srt (6.0 KB)
      • [3] Using the Thonny IDE.mp4 (5.5 MB)
      • [3] Using the Thonny IDE.srt (3.7 KB)
      [3] 2. OpenCV on the Raspberry Pi
      • [1] Introducing OpenCV.mp4 (9.4 MB)
      • [1] Introducing OpenCV.srt (6.8 KB)
      • [2] NumPy array operations.mp4 (8.1 MB)
      • [2] NumPy array operations.srt (6.1 KB)
      • [3] Running a simple image processing example.mp4 (13.3 MB)
      • [3] Running a simple image processing example.srt (6.0 KB)
      • [4] Theory of convolution.mp4 (10.0 MB)
      • [4] Theory of convolution.srt (6.3 KB)
      • [5] Convolution in OpenCV.mp4 (12.5 MB)
      • [5] Convolution in OpenCV.srt (6.4 KB)
      [4] 3. Object Detection
      • [1] Computing image gradients.mp4 (8.5 MB)
      • [1] Computing image gradients.srt (5.7 KB)
      • [2] Forming histograms of gradients (HOGs).mp4 (12.1 MB)
      • [2] Forming histograms of gradients (HOGs).srt (6.5 KB)
      • [3] Computing HOGs in OpenCV.mp4 (10.2 MB)
      • [3] Computing HOGs in OpenCV.srt (6.5 KB)
      • [4] Understanding Support Vector Machines (SVMs).mp4 (13.2 MB)
      • [4] Understanding Support Vector Machines (SVMs).srt (8.0 KB)
      • [5] Detecting objects with HOGs and SVMs.mp4 (11.7 MB)
      • [5] Detecting objects with HOGs and SVMs.srt (5.9 KB)
      [5] 4. Understanding Neural Networks
      • [1] Introducing neural networks.mp4 (11.3 MB)
      • [1] Introducing neural networks.srt (6.5 KB)
      • [2] Training neural networks.mp4 (10.7 MB)
      • [2] Training neural networks.srt (6.4 KB)
      • [3] Creating neural networks in OpenCV.mp4 (8.8 MB)
      • [3] Creating neural networks in OpenCV.srt (5.3 KB)
      • [4] Classifying irises with a neural network.mp4 (9.9 MB)
      • [4] Classifying irises with a neural network.srt (2.8 KB)
      [6] 5. Convolutional Neural Networks (CNNs)
      • [1] Introducing convolutional neural networks (CNNs).mp4 (9.7 MB)
      • [1] Introducing convolutional neural networks (CNNs).srt (6.3 KB)
      • [2] Creating CNNs with Keras.mp4 (10.8 MB)
      • [2] Creating CNNs with Keras.srt (5.6 KB)
      • [3] Training CNNs with TensorFlow.mp4 (12.5 MB)
      • [3] Training CNNs with TensorFlow.srt (4.9 KB)
      • [4] Executing models with TensorFlow Lite.mp4 (5.2 MB)
      • [4] Executing models with TensorFlow Lite.srt (4.7 KB)
      • [5] Recognizing objects with the Raspberry Pi.mp4 (10.6 MB)
      • [5] Recognizing objects with the Raspberry Pi.srt (5.2 KB)
      [7] 6. The Raspberry Pi HQ Camera
      • [1] Introducing the picamera package.mp4 (6.6 MB)
      • [1] Introducing the picamera package.srt (5.1 KB)
      • [2] Accessing a Raspberry Pi camera in Python.mp4 (6.8 MB)
      • [2] Accessing a Raspberry Pi camera in Python.srt (4.4 KB)
      • [3] Object detection with a Raspberry Pi camera.mp4 (15.4 MB)
      • [3] Object detection with a Raspberry Pi camera.srt (6.6 KB)
      • [4] Object recognition with a Raspberry Pi camera.mp4 (14.4 MB)
      • [4] Object recognition with a Raspberry Pi camera.srt (6.3 KB)
      [8] Conclusion
      • [1] Next steps.mp4 (3.0 MB)
      • [1] Next steps.srt (2.4 KB)

Description

Computer Vision on the Raspberry Pi 4



https://CourseLala.com

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 43m | Size: 241.9 MB
More and more applications are using computer vision to detect and recognize objects. These applications usually execute on large computers, but developers can save money and power by running them on single-board computers (SBCs). The Raspberry Pi 4 is one of the most popular SBCs available. It's also the first computer in the Raspberry Pi family powerful enough to execute computer vision applications. Also, the software needed to build these applications can be downloaded freely from the Internet. In this course, instructor Matt Scarpino shows programmers how to write and execute computer vision applications on the Raspberry Pi 4. Matt introduces you to using the Thonny IDE, the OpenCV library, and NumPy array operations. He steps through object detection and neural networks, then explores convolutional neural networks (CNNs), including the Keras package and the TensorFlow package. Matt also walks you through what you can do with a Raspberry Pi HQ camera



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Linkedin - Computer Vision on the Raspberry Pi 4

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285.7 MB
seeders:10
leechers:9
Linkedin - Computer Vision on the Raspberry Pi 4

Torrent hash: E8C52D071BB43C30FD9D1335DBBF8BC4F2AE492E