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  62. <h1>Source code for ipfml.processing.reconstruction</h1><div class="highlight"><pre>
  63. <span></span><span class="sd">&quot;&quot;&quot;</span>
  64. <span class="sd">Functions for reconstruction process of image using reduction/compression methods</span>
  65. <span class="sd">&quot;&quot;&quot;</span>
  66. <span class="c1"># main imports</span>
  67. <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
  68. <span class="c1"># image processing imports</span>
  69. <span class="kn">from</span> <span class="nn">numpy.linalg</span> <span class="k">import</span> <span class="n">svd</span> <span class="k">as</span> <span class="n">np_svd</span>
  70. <span class="kn">from</span> <span class="nn">sklearn.decomposition</span> <span class="k">import</span> <span class="n">FastICA</span><span class="p">,</span> <span class="n">IncrementalPCA</span>
  71. <span class="c1"># ipfml imports</span>
  72. <span class="kn">from</span> <span class="nn">ipfml.processing</span> <span class="k">import</span> <span class="n">transform</span>
  73. <div class="viewcode-block" id="svd"><a class="viewcode-back" href="../../../ipfml/ipfml.processing.reconstruction.html#ipfml.processing.reconstruction.svd">[docs]</a><span class="k">def</span> <span class="nf">svd</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">interval</span><span class="p">):</span>
  74. <span class="sd">&quot;&quot;&quot;Reconstruct an image from SVD compression using specific interval of Singular Values</span>
  75. <span class="sd"> Args:</span>
  76. <span class="sd"> image: PIL Image, Numpy array or path of 3D image</span>
  77. <span class="sd"> interval: Interval used for reconstruction</span>
  78. <span class="sd"> Returns:</span>
  79. <span class="sd"> Reconstructed image</span>
  80. <span class="sd"> Example:</span>
  81. <span class="sd"> &gt;&gt;&gt; from PIL import Image</span>
  82. <span class="sd"> &gt;&gt;&gt; import numpy as np</span>
  83. <span class="sd"> &gt;&gt;&gt; from ipfml.processing import reconstruction</span>
  84. <span class="sd"> &gt;&gt;&gt; image_values = Image.open(&#39;./images/test_img.png&#39;)</span>
  85. <span class="sd"> &gt;&gt;&gt; reconstructed_image = reconstruction.svd(image_values, (100, 200))</span>
  86. <span class="sd"> &gt;&gt;&gt; reconstructed_image.shape</span>
  87. <span class="sd"> (200, 200)</span>
  88. <span class="sd"> &quot;&quot;&quot;</span>
  89. <span class="n">begin</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">interval</span>
  90. <span class="n">lab_img</span> <span class="o">=</span> <span class="n">transform</span><span class="o">.</span><span class="n">get_LAB_L</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>
  91. <span class="n">lab_img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">lab_img</span><span class="p">,</span> <span class="s1">&#39;uint8&#39;</span><span class="p">)</span>
  92. <span class="n">U</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">V</span> <span class="o">=</span> <span class="n">np_svd</span><span class="p">(</span><span class="n">lab_img</span><span class="p">,</span> <span class="n">full_matrices</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
  93. <span class="c1"># reconstruction using specific interval</span>
  94. <span class="n">smat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">end</span> <span class="o">-</span> <span class="n">begin</span><span class="p">,</span> <span class="n">end</span> <span class="o">-</span> <span class="n">begin</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">complex</span><span class="p">)</span>
  95. <span class="n">smat</span><span class="p">[:,</span> <span class="p">:]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">diag</span><span class="p">(</span><span class="n">s</span><span class="p">[</span><span class="n">begin</span><span class="p">:</span><span class="n">end</span><span class="p">])</span>
  96. <span class="n">output_img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">U</span><span class="p">[:,</span> <span class="n">begin</span><span class="p">:</span><span class="n">end</span><span class="p">],</span> <span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">smat</span><span class="p">,</span> <span class="n">V</span><span class="p">[</span><span class="n">begin</span><span class="p">:</span><span class="n">end</span><span class="p">,</span> <span class="p">:]))</span>
  97. <span class="k">return</span> <span class="n">output_img</span></div>
  98. <div class="viewcode-block" id="fast_ica"><a class="viewcode-back" href="../../../ipfml/ipfml.processing.reconstruction.html#ipfml.processing.reconstruction.fast_ica">[docs]</a><span class="k">def</span> <span class="nf">fast_ica</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">components</span><span class="p">):</span>
  99. <span class="sd">&quot;&quot;&quot;Reconstruct an image from Fast ICA compression using specific number of components to use</span>
  100. <span class="sd"> Args:</span>
  101. <span class="sd"> image: PIL Image, Numpy array or path of 3D image</span>
  102. <span class="sd"> components: Number of components used for reconstruction</span>
  103. <span class="sd"> Returns:</span>
  104. <span class="sd"> Reconstructed image</span>
  105. <span class="sd"> Example:</span>
  106. <span class="sd"> &gt;&gt;&gt; from PIL import Image</span>
  107. <span class="sd"> &gt;&gt;&gt; import numpy as np</span>
  108. <span class="sd"> &gt;&gt;&gt; from ipfml.processing import reconstruction</span>
  109. <span class="sd"> &gt;&gt;&gt; image_values = Image.open(&#39;./images/test_img.png&#39;)</span>
  110. <span class="sd"> &gt;&gt;&gt; reconstructed_image = reconstruction.fast_ica(image_values, 25)</span>
  111. <span class="sd"> &gt;&gt;&gt; reconstructed_image.shape</span>
  112. <span class="sd"> (200, 200)</span>
  113. <span class="sd"> &quot;&quot;&quot;</span>
  114. <span class="n">lab_img</span> <span class="o">=</span> <span class="n">transform</span><span class="o">.</span><span class="n">get_LAB_L</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>
  115. <span class="n">lab_img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">lab_img</span><span class="p">,</span> <span class="s1">&#39;uint8&#39;</span><span class="p">)</span>
  116. <span class="n">ica</span> <span class="o">=</span> <span class="n">FastICA</span><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="mi">50</span><span class="p">)</span>
  117. <span class="c1"># run ICA on image</span>
  118. <span class="n">ica</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">lab_img</span><span class="p">)</span>
  119. <span class="c1"># reconstruct image with independent components</span>
  120. <span class="n">image_ica</span> <span class="o">=</span> <span class="n">ica</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">lab_img</span><span class="p">)</span>
  121. <span class="n">restored_image</span> <span class="o">=</span> <span class="n">ica</span><span class="o">.</span><span class="n">inverse_transform</span><span class="p">(</span><span class="n">image_ica</span><span class="p">)</span>
  122. <span class="k">return</span> <span class="n">restored_image</span></div>
  123. <div class="viewcode-block" id="ipca"><a class="viewcode-back" href="../../../ipfml/ipfml.processing.reconstruction.html#ipfml.processing.reconstruction.ipca">[docs]</a><span class="k">def</span> <span class="nf">ipca</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">components</span><span class="p">,</span> <span class="n">_batch_size</span><span class="o">=</span><span class="mi">25</span><span class="p">):</span>
  124. <span class="sd">&quot;&quot;&quot;Reconstruct an image from IPCA compression using specific number of components to use and batch size</span>
  125. <span class="sd"> Args:</span>
  126. <span class="sd"> image: PIL Image, Numpy array or path of 3D image</span>
  127. <span class="sd"> components: Number of components used for reconstruction</span>
  128. <span class="sd"> batch_size: Batch size used for learn (default 25)</span>
  129. <span class="sd"> Returns:</span>
  130. <span class="sd"> Reconstructed image</span>
  131. <span class="sd"> Example:</span>
  132. <span class="sd"> &gt;&gt;&gt; from PIL import Image</span>
  133. <span class="sd"> &gt;&gt;&gt; import numpy as np</span>
  134. <span class="sd"> &gt;&gt;&gt; from ipfml.processing import reconstruction</span>
  135. <span class="sd"> &gt;&gt;&gt; image_values = Image.open(&#39;./images/test_img.png&#39;)</span>
  136. <span class="sd"> &gt;&gt;&gt; reconstructed_image = reconstruction.ipca(image_values, 20)</span>
  137. <span class="sd"> &gt;&gt;&gt; reconstructed_image.shape</span>
  138. <span class="sd"> (200, 200)</span>
  139. <span class="sd"> &quot;&quot;&quot;</span>
  140. <span class="n">lab_img</span> <span class="o">=</span> <span class="n">transform</span><span class="o">.</span><span class="n">get_LAB_L</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>
  141. <span class="n">lab_img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">lab_img</span><span class="p">,</span> <span class="s1">&#39;uint8&#39;</span><span class="p">)</span>
  142. <span class="n">transformer</span> <span class="o">=</span> <span class="n">IncrementalPCA</span><span class="p">(</span>
  143. <span class="n">n_components</span><span class="o">=</span><span class="n">components</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">_batch_size</span><span class="p">)</span>
  144. <span class="n">transformed_image</span> <span class="o">=</span> <span class="n">transformer</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">lab_img</span><span class="p">)</span>
  145. <span class="n">restored_image</span> <span class="o">=</span> <span class="n">transformer</span><span class="o">.</span><span class="n">inverse_transform</span><span class="p">(</span><span class="n">transformed_image</span><span class="p">)</span>
  146. <span class="k">return</span> <span class="n">restored_image</span></div>
  147. </pre></div>
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