Push dev branch build

docs/contents/contributors.html

@@ -722,10 +722,10 @@ <h1 class="title">Contributors</h1>
 <a href="https://github.com/Mjrovai"><img src="https://avatars.githubusercontent.com/Mjrovai?s=100" width="100px;" alt="Marcelo Rovai"><br><sub><b>Marcelo Rovai</b></sub></a><br>
 </td>
 <td align="center" valign="top" width="20%">
-<a href="https://github.com/mpstewart1"><img src="https://avatars.githubusercontent.com/mpstewart1?s=100" width="100px;" alt="Matthew Stewart"><br><sub><b>Matthew Stewart</b></sub></a><br>
+<a href="https://github.com/jaysonzlin"><img src="https://avatars.githubusercontent.com/jaysonzlin?s=100" width="100px;" alt="Jayson Lin"><br><sub><b>Jayson Lin</b></sub></a><br>
 </td>
 <td align="center" valign="top" width="20%">
-<a href="https://github.com/jaysonzlin"><img src="https://avatars.githubusercontent.com/jaysonzlin?s=100" width="100px;" alt="Jayson Lin"><br><sub><b>Jayson Lin</b></sub></a><br>
+<a href="https://github.com/mpstewart1"><img src="https://avatars.githubusercontent.com/mpstewart1?s=100" width="100px;" alt="Matthew Stewart"><br><sub><b>Matthew Stewart</b></sub></a><br>
 </td>
 <td align="center" valign="top" width="20%">
 <a href="https://github.com/18jeffreyma"><img src="https://avatars.githubusercontent.com/18jeffreyma?s=100" width="100px;" alt="Jeffrey Ma"><br><sub><b>Jeffrey Ma</b></sub></a><br>

docs/contents/frameworks/frameworks.html

@@ -1579,7 +1579,7 @@ <h3 data-number="6.8.3" class="anchored" data-anchor-id="library"><span class="h
 <section id="choosing-the-right-framework" class="level2" data-number="6.9">
 <h2 data-number="6.9" class="anchored" data-anchor-id="choosing-the-right-framework"><span class="header-section-number">6.9</span> Choosing the Right Framework</h2>
 <p>Choosing the right machine learning framework for a given application requires carefully evaluating models, hardware, and software considerations. By analyzing these three aspects—models, hardware, and software—ML engineers can select the optimal framework and customize it as needed for efficient and performant on-device ML applications. The goal is to balance model complexity, hardware limitations, and software integration to design a tailored ML pipeline for embedded and edge devices.</p>
-<div id="fig-tf-comparison" class="quarto-figure quarto-figure-center quarto-float anchored" data-caption="TensorFlow Framework Comparison - General" data-align="center">
+<div id="fig-tf-comparison" class="quarto-figure quarto-figure-center quarto-float anchored" data-align="center" data-caption="TensorFlow Framework Comparison - General">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-tf-comparison-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image4.png" style="width:100.0%" data-align="center" data-caption="TensorFlow Framework Comparison - General" class="figure-img">
@@ -1595,7 +1595,7 @@ <h3 data-number="6.9.1" class="anchored" data-anchor-id="model"><span class="hea
 </section>
 <section id="software" class="level3" data-number="6.9.2">
 <h3 data-number="6.9.2" class="anchored" data-anchor-id="software"><span class="header-section-number">6.9.2</span> Software</h3>
-<div id="fig-tf-sw-comparison" class="quarto-figure quarto-figure-center quarto-float anchored" data-caption="TensorFlow Framework Comparison - Model" data-align="center">
+<div id="fig-tf-sw-comparison" class="quarto-figure quarto-figure-center quarto-float anchored" data-align="center" data-caption="TensorFlow Framework Comparison - Model">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-tf-sw-comparison-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image5.png" style="width:100.0%" data-align="center" data-caption="TensorFlow Framework Comparison - Model" class="figure-img">
@@ -1609,7 +1609,7 @@ <h3 data-number="6.9.2" class="anchored" data-anchor-id="software"><span class="
 </section>
 <section id="hardware" class="level3" data-number="6.9.3">
 <h3 data-number="6.9.3" class="anchored" data-anchor-id="hardware"><span class="header-section-number">6.9.3</span> Hardware</h3>
-<div id="fig-tf-hw-comparison" class="quarto-figure quarto-figure-center quarto-float anchored" data-caption="TensorFlow Framework Comparison - Hardware" data-align="center">
+<div id="fig-tf-hw-comparison" class="quarto-figure quarto-figure-center quarto-float anchored" data-align="center" data-caption="TensorFlow Framework Comparison - Hardware">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-tf-hw-comparison-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image3.png" style="width:100.0%" data-align="center" data-caption="TensorFlow Framework Comparison - Hardware" class="figure-img">
@@ -1656,7 +1656,7 @@ <h2 data-number="6.10" class="anchored" data-anchor-id="future-trends-in-ml-fram
 <section id="decomposition" class="level3" data-number="6.10.1">
 <h3 data-number="6.10.1" class="anchored" data-anchor-id="decomposition"><span class="header-section-number">6.10.1</span> Decomposition</h3>
 <p>Currently, the ML system stack consists of four abstractions as shown in <a href="#fig-mlsys-stack" class="quarto-xref">Figure&nbsp;<span>6.10</span></a>, namely (1) computational graphs, (2) tensor programs, (3) libraries and runtimes, and (4) hardware primitives.</p>
-<div id="fig-mlsys-stack" class="quarto-figure quarto-figure-center quarto-float anchored" data-caption="Four Abstractions in Current ML System Stack" data-align="center">
+<div id="fig-mlsys-stack" class="quarto-figure quarto-figure-center quarto-float anchored" data-align="center" data-caption="Four Abstractions in Current ML System Stack">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-mlsys-stack-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image8.png" class="img-fluid figure-img" data-align="center" data-caption="Four Abstractions in Current ML System Stack">

docs/contents/labs/arduino/nicla_vision/image_classification/image_classification.html

@@ -660,6 +660,7 @@ <h2 id="toc-title">Table of contents</h2>
   </ul></li>
   <li><a href="#image-classification-non-official-benchmark" id="toc-image-classification-non-official-benchmark" class="nav-link" data-scroll-target="#image-classification-non-official-benchmark">Image Classification (non-official) Benchmark</a></li>
   <li><a href="#conclusion" id="toc-conclusion" class="nav-link" data-scroll-target="#conclusion">Conclusion</a></li>
+  <li><a href="#resources" id="toc-resources" class="nav-link" data-scroll-target="#resources">Resources</a></li>
   </ul>
 <div class="toc-actions"><ul><li><a href="https://github.com/harvard-edge/cs249r_book/edit/main/contents/labs/arduino/nicla_vision/image_classification/image_classification.qmd" class="toc-action"><i class="bi bi-github"></i>Edit this page</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/issues/new" class="toc-action"><i class="bi empty"></i>Report an issue</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/blob/main/contents/labs/arduino/nicla_vision/image_classification/image_classification.qmd" class="toc-action"><i class="bi empty"></i>View source</a></li></ul></div></nav>
     </div>
@@ -1275,6 +1276,14 @@ <h2 class="anchored" data-anchor-id="conclusion">Conclusion</h2>
 <li><p><strong>Gesture Recognition:</strong> For gaming, sign language translation, and human-machine interaction.</p></li>
 <li><p><strong>Content Recommendation:</strong> Image-based recommendation systems in e-commerce.</p></li>
 </ul>
+</section>
+<section id="resources" class="level2">
+<h2 class="anchored" data-anchor-id="resources">Resources</h2>
+<ul>
+<li><p><a href="https://github.com/Mjrovai/Arduino_Nicla_Vision/tree/main/Micropython">Micropython codes</a></p></li>
+<li><p><a href="https://github.com/Mjrovai/Arduino_Nicla_Vision/tree/main/data">Dataset</a></p></li>
+<li><p><a href="https://studio.edgeimpulse.com/public/273858/latest">Edge Impulse Project</a></p></li>
+</ul>
 
 
 </section>

docs/contents/labs/arduino/nicla_vision/kws/kws.html

@@ -665,6 +665,7 @@ <h2 id="toc-title">Table of contents</h2>
   <li><a href="#deploy-and-inference" id="toc-deploy-and-inference" class="nav-link" data-scroll-target="#deploy-and-inference">Deploy and Inference</a></li>
   <li><a href="#post-processing" id="toc-post-processing" class="nav-link" data-scroll-target="#post-processing">Post-processing</a></li>
   <li><a href="#conclusion" id="toc-conclusion" class="nav-link" data-scroll-target="#conclusion">Conclusion</a></li>
+  <li><a href="#resources" id="toc-resources" class="nav-link" data-scroll-target="#resources">Resources</a></li>
   </ul>
 <div class="toc-actions"><ul><li><a href="https://github.com/harvard-edge/cs249r_book/edit/main/contents/labs/arduino/nicla_vision/kws/kws.qmd" class="toc-action"><i class="bi bi-github"></i>Edit this page</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/issues/new" class="toc-action"><i class="bi empty"></i>Report an issue</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/blob/main/contents/labs/arduino/nicla_vision/kws/kws.qmd" class="toc-action"><i class="bi empty"></i>View source</a></li></ul></div></nav>
     </div>
@@ -1088,6 +1089,22 @@ <h2 class="anchored" data-anchor-id="conclusion">Conclusion</h2>
 <li><strong>Medical</strong> (Snore, Cough, Pulmonary diseases)</li>
 <li><strong>Nature</strong> (Beehive control, insect sound, pouching mitigation)</li>
 </ul>
+</section>
+<section id="resources" class="level2">
+<h2 class="anchored" data-anchor-id="resources">Resources</h2>
+<ul>
+<li><p><a href="https://cdn.edgeimpulse.com/datasets/keywords2.zip">Subset of Google Speech Commands Dataset</a></p></li>
+<li><p><a href="https://colab.research.google.com/github/Mjrovai/Arduino_Nicla_Vision/blob/main/KWS/KWS_MFCC_Analysis.ipynb">KWS_MFCC_Analysis Colab Notebook</a></p></li>
+<li><p><a href="https://colab.research.google.com/github/Mjrovai/Arduino_Nicla_Vision/blob/main/KWS/KWS_CNN_training.ipynb">KWS_CNN_training Colab Notebook</a></p></li>
+<li><p><a href="https://github.com/Mjrovai/Arduino_Nicla_Vision/tree/main/KWS/nicla_vision_microphone_continuous_LED">Arduino post-processing code</a></p></li>
+<li><p><a href="https://studio.edgeimpulse.com/public/292418/latest">Edge Impulse Project</a></p></li>
+</ul>
+<p><strong>Motion Classification and Anomaly Detection)</strong></p>
+<ul>
+<li><p><a href="https://github.com/Mjrovai/Arduino_Nicla_Vision/tree/main/Motion_Classification/Niclav_Acc_Data_Capture">Arduino Code</a></p></li>
+<li><p><a href="https://colab.research.google.com/github/Mjrovai/Arduino_Nicla_Vision/blob/main/Motion_Classification/Edge_Impulse_Spectral_Features_Block.ipynb">Edge_Impulse_Spectral_Features_Block Colab Notebook</a></p></li>
+<li><p><a href="https://studio.edgeimpulse.com/public/302078/latest">Edge Impulse Project</a></p></li>
+</ul>
 
 
 </section>

docs/contents/labs/arduino/nicla_vision/object_detection/object_detection.html

@@ -659,6 +659,7 @@ <h2 id="toc-title">Table of contents</h2>
   </ul></li>
   <li><a href="#deploying-the-model" id="toc-deploying-the-model" class="nav-link" data-scroll-target="#deploying-the-model">Deploying the Model</a></li>
   <li><a href="#conclusion" id="toc-conclusion" class="nav-link" data-scroll-target="#conclusion">Conclusion</a></li>
+  <li><a href="#resources" id="toc-resources" class="nav-link" data-scroll-target="#resources">Resources</a></li>
   </ul>
 <div class="toc-actions"><ul><li><a href="https://github.com/harvard-edge/cs249r_book/edit/main/contents/labs/arduino/nicla_vision/object_detection/object_detection.qmd" class="toc-action"><i class="bi bi-github"></i>Edit this page</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/issues/new" class="toc-action"><i class="bi empty"></i>Report an issue</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/blob/main/contents/labs/arduino/nicla_vision/object_detection/object_detection.qmd" class="toc-action"><i class="bi empty"></i>View source</a></li></ul></div></nav>
     </div>
@@ -1053,6 +1054,12 @@ <h2 class="anchored" data-anchor-id="conclusion">Conclusion</h2>
 <p><img src="images/jpg/img_28.jpg" class="img-fluid quarto-figure quarto-figure-center figure-img" width="624"></p>
 </figure>
 </div>
+</section>
+<section id="resources" class="level2">
+<h2 class="anchored" data-anchor-id="resources">Resources</h2>
+<ul>
+<li><a href="https://studio.edgeimpulse.com/public/292737/latest">Edge Impulse Project</a></li>
+</ul>
 
 
 </section>

docs/contents/labs/arduino/nicla_vision/setup/setup.html

@@ -651,6 +651,7 @@ <h2 id="toc-title">Table of contents</h2>
   <li><a href="#connecting-the-nicla-vision-to-edge-impulse-studio" id="toc-connecting-the-nicla-vision-to-edge-impulse-studio" class="nav-link" data-scroll-target="#connecting-the-nicla-vision-to-edge-impulse-studio">Connecting the Nicla Vision to Edge Impulse Studio</a></li>
   <li><a href="#expanding-the-nicla-vision-board-optional" id="toc-expanding-the-nicla-vision-board-optional" class="nav-link" data-scroll-target="#expanding-the-nicla-vision-board-optional">Expanding the Nicla Vision Board (optional)</a></li>
   <li><a href="#conclusion" id="toc-conclusion" class="nav-link" data-scroll-target="#conclusion">Conclusion</a></li>
+  <li><a href="#resources" id="toc-resources" class="nav-link" data-scroll-target="#resources">Resources</a></li>
   </ul>
 <div class="toc-actions"><ul><li><a href="https://github.com/harvard-edge/cs249r_book/edit/main/contents/labs/arduino/nicla_vision/setup/setup.qmd" class="toc-action"><i class="bi bi-github"></i>Edit this page</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/issues/new" class="toc-action"><i class="bi empty"></i>Report an issue</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/blob/main/contents/labs/arduino/nicla_vision/setup/setup.qmd" class="toc-action"><i class="bi empty"></i>View source</a></li></ul></div></nav>
     </div>
@@ -1027,6 +1028,13 @@ <h2 class="anchored" data-anchor-id="conclusion">Conclusion</h2>
 <blockquote class="blockquote">
 <p>On the <a href="https://github.com/Mjrovai/Arduino_Nicla_Vision/tree/main">GitHub repository,</a> you will find the last version of all the codes used or commented on in this hands-on exercise.</p>
 </blockquote>
+</section>
+<section id="resources" class="level2">
+<h2 class="anchored" data-anchor-id="resources">Resources</h2>
+<ul>
+<li><p><a href="https://github.com/Mjrovai/Arduino_Nicla_Vision/tree/main/Micropython">Micropython codes</a></p></li>
+<li><p><a href="https://github.com/Mjrovai/Arduino_Nicla_Vision/tree/main/Arduino-IDE">Arduino Codes</a></p></li>
+</ul>
 
 
 </section>

docs/contents/labs/getting_started.html

@@ -659,18 +659,26 @@ <h2 class="anchored" data-anchor-id="software-requirements">Software Requirement
 <ol type="1">
 <li><strong>Arduino IDE</strong>
 <ul>
-<li>Download and install the <a href="https://www.arduino.cc/en/software">Arduino IDE</a> for your operating system.</li>
+<li>Download and install
+<ul>
+<li>Install <a href="https://www.arduino.cc/en/software">Arduino IDE</a></li>
+<li><a href="https://arduino.github.io/arduino-cli/1.0/">Arduino CLI</a></li>
+</ul></li>
+<li><strong>Edge Impulse Studio</strong>
+<ul>
 <li>Follow the <a href="https://docs.arduino.cc/software/ide-v1/tutorials/Windows">installation guide</a> for your specific OS.</li>
 <li>Configure the Arduino IDE for the <a href="https://docs.arduino.cc/software/ide-v1/tutorials/getting-started/cores/arduino-mbed_nicla">Arduino Nicla Vision</a> and <a href="https://wiki.seeedstudio.com/xiao_esp32s3_getting_started/#software-setup">XIAO ESP32S3 Sense</a> boards.</li>
 </ul></li>
+</ul></li>
 <li><strong>OpenMV IDE (optional)</strong>
 <ul>
 <li>Download and install the <a href="https://openmv.io/pages/download">OpenMV IDE</a> for your operating system.</li>
-<li>Configure the OpenMV IDE for the <a href="https://docs.arduino.cc/tutorials/nicla-vision/getting-started/">Arduino Nicla Vision</a>).</li>
+<li>Configure the OpenMV IDE for the <a href="https://docs.arduino.cc/tutorials/nicla-vision/getting-started/">Arduino Nicla Vision</a>.</li>
 </ul></li>
 <li><strong>Edge Impulse Studio</strong>
 <ul>
 <li>Sign up for a free account on the <a href="https://studio.edgeimpulse.com/login">Edge Impulse Studio</a>.</li>
+<li>Install <a href="https://docs.edgeimpulse.com/docs/tools/edge-impulse-cli/cli-installation">Edge Impulse CLI</a></li>
 <li>Follow the guides to connect your <a href="https://docs.edgeimpulse.com/docs/edge-ai-hardware/mcu/arduino-nicla-vision">Arduino Nicla Vision</a> and <a href="https://docs.edgeimpulse.com/docs/edge-ai-hardware/mcu/seeed-xiao-esp32s3-sense">XIAO ESP32S3 Sense</a> boards to Edge Impulse Studio.</li>
 </ul></li>
 </ol>
@@ -679,8 +687,8 @@ <h2 class="anchored" data-anchor-id="software-requirements">Software Requirement
 <h2 class="anchored" data-anchor-id="network-connectivity">Network Connectivity</h2>
 <p>Some projects may require internet connectivity for data collection or model deployment. Ensure that your development environment has a stable internet connection, either through Wi-Fi or Ethernet.</p>
 <ul>
-<li>For the Arduino Nicla Vision, you can use the onboard Wi-Fi module to connect to a wireless network.</li>
-<li>For the XIAO ESP32S3 Sense, you can use the onboard Wi-Fi module or connect an external Wi-Fi or Ethernet module using the available pins.</li>
+<li><p>For the Arduino Nicla Vision, you can use the onboard Wi-Fi module to connect to a wireless network.</p></li>
+<li><p>For the XIAO ESP32S3 Sense, you can use the onboard Wi-Fi module or connect an external Wi-Fi or Ethernet module using the available pins.</p></li>
 </ul>
 </section>
 <section id="conclusion" class="level2">

docs/contents/labs/seeed/xiao_esp32s3/image_classification/image_classification.html

@@ -650,6 +650,7 @@ <h2 id="toc-title">Table of contents</h2>
   <li><a href="#testing-with-a-bigger-model" id="toc-testing-with-a-bigger-model" class="nav-link" data-scroll-target="#testing-with-a-bigger-model">Testing with a Bigger Model</a></li>
   <li><a href="#running-inference-on-the-sensecraft-web-toolkit" id="toc-running-inference-on-the-sensecraft-web-toolkit" class="nav-link" data-scroll-target="#running-inference-on-the-sensecraft-web-toolkit">Running inference on the SenseCraft-Web-Toolkit</a></li>
   <li><a href="#conclusion" id="toc-conclusion" class="nav-link" data-scroll-target="#conclusion">Conclusion</a></li>
+  <li><a href="#resources" id="toc-resources" class="nav-link" data-scroll-target="#resources">Resources</a></li>
   </ul>
 <div class="toc-actions"><ul><li><a href="https://github.com/harvard-edge/cs249r_book/edit/main/contents/labs/seeed/xiao_esp32s3/image_classification/image_classification.qmd" class="toc-action"><i class="bi bi-github"></i>Edit this page</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/issues/new" class="toc-action"><i class="bi empty"></i>Report an issue</a></li><li><a href="https://github.com/harvard-edge/cs249r_book/blob/main/contents/labs/seeed/xiao_esp32s3/image_classification/image_classification.qmd" class="toc-action"><i class="bi empty"></i>View source</a></li></ul></div></nav>
     </div>
@@ -925,6 +926,14 @@ <h2 class="anchored" data-anchor-id="running-inference-on-the-sensecraft-web-too
 <h2 class="anchored" data-anchor-id="conclusion">Conclusion</h2>
 <p>The XIAO ESP32S3 Sense is very flexible, inexpensive, and easy to program. The project proves the potential of TinyML. Memory is not an issue; the device can handle many post-processing tasks, including communication.</p>
 <p>You will find the last version of the codes on the GitHub repository: <a href="https://github.com/Mjrovai/XIAO-ESP32S3-Sense">XIAO-ESP32S3-Sense.</a></p>
+</section>
+<section id="resources" class="level2">
+<h2 class="anchored" data-anchor-id="resources">Resources</h2>
+<ul>
+<li><p><a href="https://github.com/Mjrovai/XIAO-ESP32S3-Sense">XIAO ESP32S3 Codes</a></p></li>
+<li><p><a href="https://www.kaggle.com/kritikseth/fruit-and-vegetable-image-recognition">Dataset</a></p></li>
+<li><p><a href="https://studio.edgeimpulse.com/public/228516/live">Edge Impulse Project</a></p></li>
+</ul>
 
 
 </section>