Updated tutorial

Author: 8bitkick

GestureToEmoji/README.md

@@ -1,9 +1,9 @@
 # Machine Learning on Arduino
 ## TensorFlow Lite gesture training tutorial
 
-In this tutorial we will teach a board to recognise gestures! We'll capture motion data from the [Arduino Nano 33 BLE Sense](https://store.arduino.cc/arduino-nano-33-ble-sense) board, import it into TensorFlow to train a model, and deploy inferencing onto the board using [TensorFlow Lite for microcontrollers](https://www.tensorflow.org/lite/microcontrollers/overview). 
+In this tutorial we will teach a board to recognise gestures! We'll capture motion data from the [Arduino Nano 33 BLE Sense](https://store.arduino.cc/arduino-nano-33-ble-sense) board, import it into TensorFlow to train a model, and deploy a classifier onto the board using [TensorFlow Lite for microcontrollers](https://www.tensorflow.org/lite/microcontrollers/overview). 
 
-Credits
+### Credits
 
 This tutorial is adapted from the [workshop](https://github.com/sandeepmistry/aimldevfest-workshop-2019) Sandeep Mistry, Arduino and Don Coleman, Chariot Solutions presented at AI/ML Devfest in September 2019. 
 
@@ -13,7 +13,7 @@ This tutorial is adapted from the [workshop](https://github.com/sandeepmistry/ai
 ## Exercises
 
 * [Exercise 1: Development Environment](exercises/exercise1.md)
-* [Exercise 2: Assemble the Hardware](exercises/exercise2.md)
+* [Exercise 2: Connecting the Board](exercises/exercise2.md)
 * [Exercise 3: Visualizing the IMU Data](exercises/exercise3.md)
 * [Exercise 4: Gather the Training Data](exercises/exercise4.md)
 * [Exercise 5: Machine Learning](exercises/exercise5.md)

GestureToEmoji/arduino_tinyml_workshop.ipynb

@@ -21,16 +21,14 @@
         "colab_type": "text"
       },
       "source": [
-        "<a href=\"https://www.aimldevfest.com\"><img src=\"https://www.aimldevfest.com/files/2019/09/AI-ML-devfest-AZ-2019-horz.png\" width=200/></a>\n",
-        "\n",
-        "# TinyML on Arduino Workshop\n",
-        "[AI/ML Devfest](https://aimldevfest.com) September 28, 2019\n",
-        "\n",
-        "\n",
+        "<a href=\"https://www.arduino.cc/\"><img src=\"https://raw.githubusercontent.com/sandeepmistry/aimldevfest-workshop-2019/master/images/Arduino_logo_R_highquality.png\" width=200/></a>\n",
+        "# Tiny ML on Arduino\n",
+        "## Gesture recognition tutorial\n",
         " * Sandeep Mistry - Arduino\n",
         " * Don Coleman - Chariot Solutions\n",
+        "\n",
         " \n",
-        "https://github.com/sandeepmistry/aimldevfest-workshop-2019"
+        "https://github.com/arduino/ArduinoTensorFlowLiteTutorials/"
       ]
     },
     {
@@ -545,9 +543,7 @@
       "source": [
         "# Classifying IMU Data\n",
         "\n",
-        "Now it's time to switch back to the instructions on Github and run our new model on the Arduino Nano 33 BLE Sense to classify the accelerometer and gyroscope data.\n",
-        "\n",
-        "[Exercise 6:Classifying IMU Data](https://github.com/sandeepmistry/aimldevfest-workshop-2019/blob/master/exercises/exercise6.md)"
+        "Now it's time to switch back to the tutorial instructions and run our new model on the Arduino Nano 33 BLE Sense to classify the accelerometer and gyroscope data.\n"
       ]
     }
   ]

GestureToEmoji/exercises/exercise1.md

@@ -19,25 +19,20 @@ Search for "Nano 33 BLE" and install the Arduino nRF528x Boards (Mbed OS) defini
 ### Arduino Libraries        
 Install the following Arduino libraries using the Library manager:
 
+* TensorFlow Lite library (search for "Arduino_TensorFlowLite")
 * Arduino LSM9DS1 library (search for "Arduino_LSM9DS1")
 
 Open the library manager using the menu _Tools ->  Manage Libraries..._
 
 ![Arduino Library Manager Menu](../images/ManageLibraries.png)
 
-Search for "Arduino_LSM9DS1". Click the row and press the +Install+ button to install the Arduino LSM9DS1 accelerometer, magnetometer, and gyroscope library. 
+Search for "Arduino_TensorFlowLite". Click the row and press the __Install__ button to install TensorFlow Lite for Microcontrollers
 
-![Arduino LSM9DS1 library](../images/library-arduinolsm9ds1.png)
-
-The TensorFlow Lite library isn't available in the Arduino Library Manager yet.
+Search for "Arduino_LSM9DS1". Click the row and press the __Install__ button to install the Arduino LSM9DS1 accelerometer, magnetometer, and gyroscope library. 
 
-1. Download the zip file [tensorflow_lite.zip](https://storage.googleapis.com/tensorflow-nightly/github/tensorflow/tensorflow/lite/experimental/micro/tools/make/gen/arduino_x86_64/prj/tensorflow_lite.zip)
-2. Import downloaded library into the IDE using _Sketch -> Include Library -> Add .ZIP library ..._
-
-![Importing Tensor Flow Lite Library from ZIP file](../images/AddZipLibrary.png)
+![Arduino LSM9DS1 library](../images/library-arduinolsm9ds1.png)
 
-![Selecting Tensor Flow Lite ZIP file](../images/AddZipLibrary_2.png)
 
 __Linux users__ may need to configure permissions so their user can access the serial port. See the [Getting Started Guide for Linux](https://www.arduino.cc/en/guide/linux) on the Arudino website for more information.
 
-Next [Exercise 2: Assemble the Hardware](exercise2.md)
+Next [Exercise 2: Connecting the board](exercise2.md)

GestureToEmoji/exercises/exercise2.md

@@ -1,31 +1,19 @@
-# Exercise 2: Assemble the Hardware
+# Exercise 2: Connecting the board
 
-1. Remove the Arduino Nano 33 BLE Sense board from the box
-1. Hold the Arduino with the USB connector toward the left
-1. Plug the Arduino into the bottom of the mini solderless breadboard
-1. You should see 4 rows of holes above the Arduino board
-1. Take the button and gently insert it into the breadboard
-1. The right side of the button should be in the ground pin, which is denoted by a white mark
-1. The left side of the button should be in pin D3. (The pin labels are on the bottom of the board, so match your setup with the picture below.)
 
-![Picture of assembled hardware](../images/assembled-hardware.jpg)
 
-## Get the Code
 
-Clone or download this [git repository](https://github.com/sandeepmistry/aimldevfest-workshop-2019/). If you're familiar with [git](https://git-scm.com), clone this repository, otherwise, click the [green button]((https://github.com/sandeepmistry/aimldevfest-workshop-2019/) to download a zip file with all the code.
+![Picture of assembled hardware](../images/ble-sense.jpg)
 
-![screenshot of the git repository](../images/download-repo.png)
 
-## Hardware Test
+## Unboxing and set up
 
+1. Remove the Arduino Nano 33 BLE Sense board from the box
 1. Plug the micro USB cable into the board and your computer
-1. Open ArduinoSketches/HardwareTest/HardwareTest.ino in the Arduino IDE
+1. Open the Arduino IDE application on your computer
 1. Choose the board `Tools -> Board -> Arduino Nano 33 BLE`
 1. Choose the port `Tools -> Port -> COM5 (Arduino Nano 33 BLE)` Note that the actual port may be different on your computer
-1. Upload the code to the board `Sketch -> Upload`
-1. Press the button and the on-board LED will light up
-1. Release the button and the on-board LED will shut off
-1. Open the serial monitor `Tools -> Serial Monitor` to see debug messages
+
 
 ## LSM9DS1 Examples (Optional)
 

GestureToEmoji/exercises/exercise4.md

@@ -2,13 +2,13 @@
 
 1. Press the reset button on the board
 1. Open the Serial Monitor: `Tools -> Serial Monitor`
-1. Push the button, make a punch gesture with the board in your hand
+1. Make a punch gesture with the board in your hand - you should see the sensor data log in the Serial Monitor
 1. Repeat 10 times to gather more data
 1. Copy and paste the data from the serial output to new text file called `punch.csv` using your favorite text editor
 1. Close the Serial Monitor
 1. Press the reset button on the board
 1. Open the Serial Monitor: `Tools -> Serial Monitor`
-1. Push the button, flex
+1. Make a flex gesture with the board in your hand
 1. Repeat 10 times
 1. Copy and paste the serial output to new text file `flex.csv` using your favorite text editor
 

GestureToEmoji/exercises/exercise5.md

@@ -18,6 +18,6 @@ You can enable 3rd party cookies, or better yet, add an exception for `[*.]googl
 
 Open the notebook in Colab.
 
-https://colab.research.google.com/github/sandeepmistry/aimldevfest-workshop-2019/blob/master/arduino_tinyml_workshop.ipynb
+https://colab.research.google.com/github/arduino/ArduinoTensorFlowLiteTutorials/blob/master/GestureToEmoji/arduino_tinyml_workshop.ipynb
 
 Next [Exercise 6: Classifying IMU Data](exercise6.md)