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<a href='#section-0'>#</a>
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<h1>Utility functions for <a href="index.html">stable diffusion</a></h1>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">11</span><span></span><span class="kn">import</span> <span class="nn">os</span>
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<span class="lineno">12</span><span class="kn">import</span> <span class="nn">random</span>
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<span class="lineno">13</span><span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
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<span class="lineno">14</span>
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<span class="lineno">15</span><span class="kn">import</span> <span class="nn">PIL</span>
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<span class="lineno">16</span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
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<span class="lineno">17</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">18</span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
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<span class="lineno">19</span>
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<span class="lineno">20</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">monit</span>
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<span class="lineno">21</span><span class="kn">from</span> <span class="nn">labml.logger</span> <span class="kn">import</span> <span class="n">inspect</span>
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<span class="lineno">22</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.latent_diffusion</span> <span class="kn">import</span> <span class="n">LatentDiffusion</span>
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<span class="lineno">23</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.autoencoder</span> <span class="kn">import</span> <span class="n">Encoder</span><span class="p">,</span> <span class="n">Decoder</span><span class="p">,</span> <span class="n">Autoencoder</span>
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<span class="lineno">24</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.clip_embedder</span> <span class="kn">import</span> <span class="n">CLIPTextEmbedder</span>
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<span class="lineno">25</span><span class="kn">from</span> <span class="nn">labml_nn.diffusion.stable_diffusion.model.unet</span> <span class="kn">import</span> <span class="n">UNetModel</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-1'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-1'>#</a>
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</div>
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<h3>Set random seeds</h3>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">28</span><span class="k">def</span> <span class="nf">set_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-2'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-2'>#</a>
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</div>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">32</span> <span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
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<span class="lineno">33</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
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<span class="lineno">34</span> <span class="n">torch</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
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<span class="lineno">35</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">manual_seed_all</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-3'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-3'>#</a>
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</div>
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<h3>Load <a href="latent_diffusion.html"><code class="highlight"><span></span><span class="n">LatentDiffusion</span></code>
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model</a></h3>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">38</span><span class="k">def</span> <span class="nf">load_model</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="n">Path</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-></span> <span class="n">LatentDiffusion</span><span class="p">:</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-4'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-4'>#</a>
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</div>
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<p>Initialize the autoencoder </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">44</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize autoencoder'</span><span class="p">):</span>
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<span class="lineno">45</span> <span class="n">encoder</span> <span class="o">=</span> <span class="n">Encoder</span><span class="p">(</span><span class="n">z_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
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<span class="lineno">46</span> <span class="n">in_channels</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
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<span class="lineno">47</span> <span class="n">channels</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span>
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<span class="lineno">48</span> <span class="n">channel_multipliers</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span>
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<span class="lineno">49</span> <span class="n">n_resnet_blocks</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
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<span class="lineno">50</span>
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<span class="lineno">51</span> <span class="n">decoder</span> <span class="o">=</span> <span class="n">Decoder</span><span class="p">(</span><span class="n">out_channels</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
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<span class="lineno">52</span> <span class="n">z_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
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<span class="lineno">53</span> <span class="n">channels</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span>
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<span class="lineno">54</span> <span class="n">channel_multipliers</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span>
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<span class="lineno">55</span> <span class="n">n_resnet_blocks</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
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<span class="lineno">56</span>
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<span class="lineno">57</span> <span class="n">autoencoder</span> <span class="o">=</span> <span class="n">Autoencoder</span><span class="p">(</span><span class="n">emb_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
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<span class="lineno">58</span> <span class="n">encoder</span><span class="o">=</span><span class="n">encoder</span><span class="p">,</span>
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<span class="lineno">59</span> <span class="n">decoder</span><span class="o">=</span><span class="n">decoder</span><span class="p">,</span>
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<span class="lineno">60</span> <span class="n">z_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-5'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-5'>#</a>
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</div>
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<p>Initialize the CLIP text embedder </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">63</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize CLIP Embedder'</span><span class="p">):</span>
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<span class="lineno">64</span> <span class="n">clip_text_embedder</span> <span class="o">=</span> <span class="n">CLIPTextEmbedder</span><span class="p">()</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-6'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-6'>#</a>
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</div>
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<p>Initialize the U-Net </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">67</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize U-Net'</span><span class="p">):</span>
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<span class="lineno">68</span> <span class="n">unet_model</span> <span class="o">=</span> <span class="n">UNetModel</span><span class="p">(</span><span class="n">in_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
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<span class="lineno">69</span> <span class="n">out_channels</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
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<span class="lineno">70</span> <span class="n">channels</span><span class="o">=</span><span class="mi">320</span><span class="p">,</span>
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<span class="lineno">71</span> <span class="n">attention_levels</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span>
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<span class="lineno">72</span> <span class="n">n_res_blocks</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
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<span class="lineno">73</span> <span class="n">channel_multipliers</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span>
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<span class="lineno">74</span> <span class="n">n_heads</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span>
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<span class="lineno">75</span> <span class="n">tf_layers</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
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<span class="lineno">76</span> <span class="n">d_cond</span><span class="o">=</span><span class="mi">768</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-7'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-7'>#</a>
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</div>
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<p>Initialize the Latent Diffusion model </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">79</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Initialize Latent Diffusion model'</span><span class="p">):</span>
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<span class="lineno">80</span> <span class="n">model</span> <span class="o">=</span> <span class="n">LatentDiffusion</span><span class="p">(</span><span class="n">linear_start</span><span class="o">=</span><span class="mf">0.00085</span><span class="p">,</span>
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<span class="lineno">81</span> <span class="n">linear_end</span><span class="o">=</span><span class="mf">0.0120</span><span class="p">,</span>
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<span class="lineno">82</span> <span class="n">n_steps</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span>
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<span class="lineno">83</span> <span class="n">latent_scaling_factor</span><span class="o">=</span><span class="mf">0.18215</span><span class="p">,</span>
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<span class="lineno">84</span>
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<span class="lineno">85</span> <span class="n">autoencoder</span><span class="o">=</span><span class="n">autoencoder</span><span class="p">,</span>
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<span class="lineno">86</span> <span class="n">clip_embedder</span><span class="o">=</span><span class="n">clip_text_embedder</span><span class="p">,</span>
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<span class="lineno">87</span> <span class="n">unet_model</span><span class="o">=</span><span class="n">unet_model</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-8'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
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</div>
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<p>Load the checkpoint </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">90</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loading model from </span><span class="si">{</span><span class="n">path</span><span class="si">}</span><span class="s2">"</span><span class="p">):</span>
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<span class="lineno">91</span> <span class="n">checkpoint</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">map_location</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-9'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-9'>#</a>
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</div>
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<p>Set model state </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">94</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Load state'</span><span class="p">):</span>
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<span class="lineno">95</span> <span class="n">missing_keys</span><span class="p">,</span> <span class="n">extra_keys</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s2">"state_dict"</span><span class="p">],</span> <span class="n">strict</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-10'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-10'>#</a>
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</div>
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<p>Debugging output </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">98</span> <span class="n">inspect</span><span class="p">(</span><span class="n">global_step</span><span class="o">=</span><span class="n">checkpoint</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'global_step'</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="n">missing_keys</span><span class="o">=</span><span class="n">missing_keys</span><span class="p">,</span> <span class="n">extra_keys</span><span class="o">=</span><span class="n">extra_keys</span><span class="p">,</span>
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<span class="lineno">99</span> <span class="n">_expand</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-11'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-11'>#</a>
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</div>
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<p> </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">102</span> <span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
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<span class="lineno">103</span> <span class="k">return</span> <span class="n">model</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-12'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-12'>#</a>
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</div>
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<h3>Load an image</h3>
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<p>This loads an image from a file and returns a PyTorch tensor.</p>
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<ul><li><code class="highlight"><span></span><span class="n">path</span></code>
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is the path of the image</li></ul>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">106</span><span class="k">def</span> <span class="nf">load_img</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-13'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-13'>#</a>
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</div>
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<p>Open Image </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">115</span> <span class="n">image</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">path</span><span class="p">)</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s2">"RGB"</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-14'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-14'>#</a>
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</div>
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<p>Get image size </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">117</span> <span class="n">w</span><span class="p">,</span> <span class="n">h</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">size</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-15'>
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<div class='docs'>
|
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<div class='section-link'>
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<a href='#section-15'>#</a>
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</div>
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<p>Resize to a multiple of 32 </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">119</span> <span class="n">w</span> <span class="o">=</span> <span class="n">w</span> <span class="o">-</span> <span class="n">w</span> <span class="o">%</span> <span class="mi">32</span>
|
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<span class="lineno">120</span> <span class="n">h</span> <span class="o">=</span> <span class="n">h</span> <span class="o">-</span> <span class="n">h</span> <span class="o">%</span> <span class="mi">32</span>
|
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<span class="lineno">121</span> <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="n">w</span><span class="p">,</span> <span class="n">h</span><span class="p">),</span> <span class="n">resample</span><span class="o">=</span><span class="n">PIL</span><span class="o">.</span><span class="n">Image</span><span class="o">.</span><span class="n">LANCZOS</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-16'>
|
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<div class='docs'>
|
|
<div class='section-link'>
|
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<a href='#section-16'>#</a>
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</div>
|
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<p>Convert to numpy and map to <code class="highlight"><span></span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span></code>
|
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for <code class="highlight"><span></span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">]</span></code>
|
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</p>
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</div>
|
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<div class='code'>
|
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<div class="highlight"><pre><span class="lineno">123</span> <span class="n">image</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">image</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="mf">2.</span> <span class="o">/</span> <span class="mf">255.0</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span></pre></div>
|
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</div>
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</div>
|
|
<div class='section' id='section-17'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-17'>#</a>
|
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</div>
|
|
<p>Transpose to shape <code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">channels</span><span class="p">,</span> <span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">]</span></code>
|
|
</p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">125</span> <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="p">[</span><span class="kc">None</span><span class="p">]</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-18'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-18'>#</a>
|
|
</div>
|
|
<p>Convert to torch </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">127</span> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">image</span><span class="p">)</span></pre></div>
|
|
</div>
|
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</div>
|
|
<div class='section' id='section-19'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-19'>#</a>
|
|
</div>
|
|
<h3>Save a images</h3>
|
|
<ul><li><code class="highlight"><span></span><span class="n">images</span></code>
|
|
is the tensor with images of shape <code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">channels</span><span class="p">,</span> <span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">]</span></code>
|
|
</li>
|
|
<li><code class="highlight"><span></span><span class="n">dest_path</span></code>
|
|
is the folder to save images in </li>
|
|
<li><code class="highlight"><span></span><span class="n">prefix</span></code>
|
|
is the prefix to add to file names </li>
|
|
<li><code class="highlight"><span></span><span class="n">img_format</span></code>
|
|
is the image format</li></ul>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">130</span><span class="k">def</span> <span class="nf">save_images</span><span class="p">(</span><span class="n">images</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">dest_path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">prefix</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">''</span><span class="p">,</span> <span class="n">img_format</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">'jpeg'</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-20'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-20'>#</a>
|
|
</div>
|
|
<p>Create the destination folder </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">141</span> <span class="n">os</span><span class="o">.</span><span class="n">makedirs</span><span class="p">(</span><span class="n">dest_path</span><span class="p">,</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-21'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-21'>#</a>
|
|
</div>
|
|
<p>Map images to <code class="highlight"><span></span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span></code>
|
|
space and clip </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">144</span> <span class="n">images</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">clamp</span><span class="p">((</span><span class="n">images</span> <span class="o">+</span> <span class="mf">1.0</span><span class="p">)</span> <span class="o">/</span> <span class="mf">2.0</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mf">1.0</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-22'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-22'>#</a>
|
|
</div>
|
|
<p>Transpose to <code class="highlight"><span></span><span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">,</span> <span class="n">channels</span><span class="p">]</span></code>
|
|
and convert to numpy </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">146</span> <span class="n">images</span> <span class="o">=</span> <span class="n">images</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">permute</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-23'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-23'>#</a>
|
|
</div>
|
|
<p>Save images </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">149</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">img</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">images</span><span class="p">):</span>
|
|
<span class="lineno">150</span> <span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">fromarray</span><span class="p">((</span><span class="mf">255.</span> <span class="o">*</span> <span class="n">img</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">))</span>
|
|
<span class="lineno">151</span> <span class="n">img</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">dest_path</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">prefix</span><span class="si">}{</span><span class="n">i</span><span class="si">:</span><span class="s2">05</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">img_format</span><span class="si">}</span><span class="s2">"</span><span class="p">),</span> <span class="nb">format</span><span class="o">=</span><span class="n">img_format</span><span class="p">)</span></pre></div>
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