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docs/exercises/canopy_cover.html

@@ -849,19 +849,19 @@ <h1 class="title"><span class="chapter-number">77</span>&nbsp; <span class="chap
 
 <p>In this exercise we will learn how to quantify the percent of green canopy cover from downward-facing digital images collected using a point-and-shoot camera or mobile device.</p>
 <p>The classification technique uses information in the Red, Green, and Blue (RGB) bands of the image. Each band consists of a 2D matrix of <em>m</em> rows by <em>n</em> columns.</p>
-<div class="cell" data-execution_count="2">
+<div class="cell" data-execution_count="1">
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Import modules</span></span>
 <span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
-<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> matplotlib.pyplot <span class="im">as</span> plt</span>
-<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> matplotlib.image <span class="im">as</span> mpimg</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> matplotlib.pyplot <span class="im">as</span> plt</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <section id="read-and-process-a-single-image" class="level2">
 <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and process a single image</h2>
-<div class="cell" data-execution_count="3">
+<div class="cell" data-execution_count="2">
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Read example image</span></span>
-<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a>rgb <span class="op">=</span> mpimg.imread(<span class="st">'../datasets/images/grassland.jpg'</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a>rgb <span class="op">=</span> plt.imread(<span class="st">'../datasets/images/grassland.jpg'</span>)</span>
+<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>                 </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div class="cell" data-execution_count="4">
+<div class="cell" data-execution_count="3">
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Display image</span></span>
 <span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>plt.imshow(rgb)</span>
 <span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a>plt.axis(<span class="st">'off'</span>)</span>
@@ -870,7 +870,7 @@ <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and p
 <p><img src="canopy_cover_files/figure-html/cell-4-output-1.png" class="img-fluid"></p>
 </div>
 </div>
-<div class="cell" data-execution_count="5">
+<div class="cell" data-execution_count="4">
 <div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Inspect shape</span></span>
 <span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(rgb.shape)</span>
 <span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(rgb.dtype)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -880,20 +880,20 @@ <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and p
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 <p>Images are often represented as unsigned integers of 8 bits. This means that each pixel in each band can only hold one of 256 integer values. Because the range is zero-index, the pixel values can range from 0 to 255. The color of a pixel is repreented by triplet, for example the triplet (0,0,0) represents black, while (255,255,255) represents white. Similarly, the triplet (255,0,0) represents red and (255,220,75) represents a shade of yellow.</p>
-<div class="cell" data-execution_count="6">
+<div class="cell" data-execution_count="5">
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Extract data in separate variable for easier manipulation.</span></span>
 <span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>red <span class="op">=</span> rgb[:, :, <span class="dv">0</span>] <span class="co">#Extract matrix of red pixel values (m by n matrix)</span></span>
 <span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>green <span class="op">=</span> rgb[:, :, <span class="dv">1</span>] <span class="co">#Extract matrix of green pixel values</span></span>
 <span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a>blue <span class="op">=</span> rgb[:, :, <span class="dv">2</span>] <span class="co">#Extract matrix of blue pixel values</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div class="cell" data-execution_count="7">
+<div class="cell" data-execution_count="6">
 <div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Compare shape with original image</span></span>
 <span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(red.shape)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
 <pre><code>(512, 512)</code></pre>
 </div>
 </div>
-<div class="cell" data-execution_count="8">
+<div class="cell" data-execution_count="7">
 <div class="sourceCode cell-code" id="cb9"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Show information in single bands</span></span>
 <span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a>plt.figure(figsize<span class="op">=</span>(<span class="dv">12</span>,<span class="dv">8</span>))</span>
 <span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a></span>
@@ -924,7 +924,7 @@ <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and p
 </div>
 </div>
 <p>Find out more about all the different methods for generating hsitogram bins <a href="https://www.wikiwand.com/en/Histogram">here</a></p>
-<div class="cell" data-execution_count="9">
+<div class="cell" data-execution_count="8">
 <div class="sourceCode cell-code" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Calculate red to green ratio for each pixel. The result is an m x n array.</span></span>
 <span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a>red_green_ratio <span class="op">=</span> red<span class="op">/</span>green</span>
 <span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a></span>
@@ -934,7 +934,7 @@ <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and p
 <span id="cb10-7"><a href="#cb10-7" aria-hidden="true" tabindex="-1"></a><span class="co"># Excess green</span></span>
 <span id="cb10-8"><a href="#cb10-8" aria-hidden="true" tabindex="-1"></a>ExG <span class="op">=</span> <span class="dv">2</span><span class="op">*</span>green <span class="op">-</span> red <span class="op">-</span> blue</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div class="cell" data-execution_count="10">
+<div class="cell" data-execution_count="9">
 <div class="sourceCode cell-code" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Let's check the resulting data type of the previous computation</span></span>
 <span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(red_green_ratio.shape)</span>
 <span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(blue_green_ratio.dtype)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -944,7 +944,7 @@ <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and p
 </div>
 </div>
 <p>The size of the array remains unchanged, but Python automatically changes the data type from <em>uint8</em> to <em>float64</em>. This is great because we need to make use of a continuous numerical scale to classify our green pixels. By generating the color ratios our scale also changes. Let’s look a this using a histogram.</p>
-<div class="cell" data-execution_count="11">
+<div class="cell" data-execution_count="10">
 <div class="sourceCode cell-code" id="cb13"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Plot histogram</span></span>
 <span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a>plt.figure()</span>
 <span id="cb13-3"><a href="#cb13-3" aria-hidden="true" tabindex="-1"></a>plt.hist(red_green_ratio.flatten(), bins<span class="op">=</span><span class="st">'scott'</span>)</span>
@@ -954,11 +954,11 @@ <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and p
 <p><img src="canopy_cover_files/figure-html/cell-11-output-1.png" class="img-fluid"></p>
 </div>
 </div>
-<div class="cell" data-execution_count="12">
+<div class="cell" data-execution_count="11">
 <div class="sourceCode cell-code" id="cb14"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Classification of green pixels</span></span>
-<span id="cb14-2"><a href="#cb14-2" aria-hidden="true" tabindex="-1"></a>bw <span class="op">=</span> np.logical_and(red_green_ratio<span class="op">&lt;</span><span class="fl">0.95</span>, blue_green_ratio<span class="op">&lt;</span><span class="fl">0.95</span>, ExG<span class="op">&gt;</span><span class="dv">20</span>) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<span id="cb14-2"><a href="#cb14-2" aria-hidden="true" tabindex="-1"></a>bw <span class="op">=</span> (red_green_ratio<span class="op">&lt;</span><span class="fl">0.95</span>) <span class="op">&amp;</span> (blue_green_ratio<span class="op">&lt;</span><span class="fl">0.95</span>) <span class="op">&amp;</span> (ExG<span class="op">*</span><span class="dv">255</span><span class="op">&gt;</span><span class="dv">20</span>) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div class="cell" data-execution_count="13">
+<div class="cell" data-execution_count="12">
 <div class="sourceCode cell-code" id="cb15"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(bw.shape)</span>
 <span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(bw.dtype)</span>
 <span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(bw.size)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -969,15 +969,15 @@ <h2 class="anchored" data-anchor-id="read-and-process-a-single-image">Read and p
 </div>
 </div>
 <p>See that we started with an m x n x 3 (original image) and we finished with and m x n x 2 (binary or classified image)</p>
-<div class="cell" data-execution_count="14">
+<div class="cell" data-execution_count="13">
 <div class="sourceCode cell-code" id="cb17"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Compute percent green canopy cover</span></span>
 <span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a>canopy_cover <span class="op">=</span> np.<span class="bu">sum</span>(bw) <span class="op">/</span> np.size(bw) <span class="op">*</span> <span class="dv">100</span> </span>
 <span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="st">'Green canopy cover:'</span>,<span class="bu">round</span>(canopy_cover,<span class="dv">2</span>),<span class="st">' %'</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code>Green canopy cover: 56.64  %</code></pre>
+<pre><code>Green canopy cover: 55.96  %</code></pre>
 </div>
 </div>
-<div class="cell" data-execution_count="15">
+<div class="cell" data-execution_count="14">
 <div class="sourceCode cell-code" id="cb19"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a>plt.figure(figsize<span class="op">=</span>(<span class="dv">12</span>,<span class="dv">4</span>))</span>
 <span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Original image</span></span>