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  [1] Introduction

   [1] Getting started with computer vision.srt

   [2] What you should know.srt

   [3] Using the exercise files.srt

  [2] 1. Programming Python on the Raspberry Pi 4

   [1] Introducing the Raspberry Pi 4.srt

   [2] Setting up the environment.srt

   [3] Using the Thonny IDE.srt

  [3] 2. OpenCV on the Raspberry Pi

   [1] Introducing OpenCV.srt

   [2] NumPy array operations.srt

   [3] Running a simple image processing example.srt

   [4] Theory of convolution.srt

   [5] Convolution in OpenCV.srt

  [4] 3. Object Detection

   [1] Computing image gradients.srt

   [2] Forming histograms of gradients (HOGs).srt

   [3] Computing HOGs in OpenCV.srt

   [4] Understanding Support Vector Machines (SVMs).srt

   [5] Detecting objects with HOGs and SVMs.srt

  [5] 4. Understanding Neural Networks

   [1] Introducing neural networks.srt

   [2] Training neural networks.srt

   [3] Creating neural networks in OpenCV.srt

   [4] Classifying irises with a neural network.srt

  [6] 5. Convolutional Neural Networks (CNNs)

   [1] Introducing convolutional neural networks (CNNs).srt

   [2] Creating CNNs with Keras.srt

   [3] Training CNNs with TensorFlow.srt

   [4] Executing models with TensorFlow Lite.srt

   [5] Recognizing objects with the Raspberry Pi.srt

  [7] 6. The Raspberry Pi HQ Camera

   [1] Introducing the picamera package.srt

   [2] Accessing a Raspberry Pi camera in Python.srt

   [3] Object detection with a Raspberry Pi camera.srt

   [4] Object recognition with a Raspberry Pi camera.srt

  [8] Conclusion

   [1] Next steps.srt