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TensorImageUtils.html
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<div class="section" id="tensorimageutils">
<h1>TensorImageUtils<a class="headerlink" href="#tensorimageutils" title="Permalink to this headline">¶</a></h1>
<dl class="type">
<dt id="org.pytorch.torchvision.TensorImageUtils">
public final class <code class="sig-name descname">TensorImageUtils</code><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils" title="Permalink to this definition">¶</a></dt>
<dd><p>Contains utility functions for <a class="reference internal" href="Tensor.html#org.pytorch.Tensor" title="org.pytorch.Tensor"><code class="xref java java-ref docutils literal notranslate"><span class="pre">org.pytorch.Tensor</span></code></a> creation from <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.graphics.Bitmap</span></code> or <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.media.Image</span></code> source.</p>
</dd></dl>
<div class="section" id="fields">
<h2>Fields<a class="headerlink" href="#fields" title="Permalink to this headline">¶</a></h2>
<div class="section" id="torchvision-norm-mean-rgb">
<h3>TORCHVISION_NORM_MEAN_RGB<a class="headerlink" href="#torchvision-norm-mean-rgb" title="Permalink to this headline">¶</a></h3>
<dl class="field">
<dt id="org.pytorch.torchvision.TensorImageUtils.TORCHVISION_NORM_MEAN_RGB">
public static float[] <code class="sig-name descname">TORCHVISION_NORM_MEAN_RGB</code><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils.TORCHVISION_NORM_MEAN_RGB" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
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<div class="section" id="torchvision-norm-std-rgb">
<h3>TORCHVISION_NORM_STD_RGB<a class="headerlink" href="#torchvision-norm-std-rgb" title="Permalink to this headline">¶</a></h3>
<dl class="field">
<dt id="org.pytorch.torchvision.TensorImageUtils.TORCHVISION_NORM_STD_RGB">
public static float[] <code class="sig-name descname">TORCHVISION_NORM_STD_RGB</code><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils.TORCHVISION_NORM_STD_RGB" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</div>
</div>
<div class="section" id="methods">
<h2>Methods<a class="headerlink" href="#methods" title="Permalink to this headline">¶</a></h2>
<div class="section" id="bitmaptofloat32tensor">
<h3>bitmapToFloat32Tensor<a class="headerlink" href="#bitmaptofloat32tensor" title="Permalink to this headline">¶</a></h3>
<dl class="method">
<dt id="org.pytorch.torchvision.TensorImageUtils.bitmapToFloat32Tensor(Bitmap, float[], float[])">
public static <a class="reference internal" href="Tensor.html#org.pytorch.Tensor" title="org.pytorch.Tensor">Tensor</a> <code class="sig-name descname">bitmapToFloat32Tensor</code><span class="sig-paren">(</span>Bitmap<em> bitmap</em>, float[]<em> normMeanRGB</em>, float[]<em> normStdRGB</em><span class="sig-paren">)</span><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils.bitmapToFloat32Tensor(Bitmap, float[], float[])" title="Permalink to this definition">¶</a></dt>
<dd><p>Creates new <a class="reference internal" href="Tensor.html#org.pytorch.Tensor" title="org.pytorch.Tensor"><code class="xref java java-ref docutils literal notranslate"><span class="pre">org.pytorch.Tensor</span></code></a> from full <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.graphics.Bitmap</span></code>, normalized with specified in parameters mean and std.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>normMeanRGB</strong> – means for RGB channels normalization, length must equal 3, RGB order</p></li>
<li><p><strong>normStdRGB</strong> – standard deviation for RGB channels normalization, length must equal 3, RGB order</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</div>
<div class="section" id="id1">
<h3>bitmapToFloat32Tensor<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h3>
<dl class="method">
<dt id="org.pytorch.torchvision.TensorImageUtils.bitmapToFloat32Tensor(Bitmap, int, int, int, int, float[], float[])">
public static <a class="reference internal" href="Tensor.html#org.pytorch.Tensor" title="org.pytorch.Tensor">Tensor</a> <code class="sig-name descname">bitmapToFloat32Tensor</code><span class="sig-paren">(</span>Bitmap<em> bitmap</em>, int<em> x</em>, int<em> y</em>, int<em> width</em>, int<em> height</em>, float[]<em> normMeanRGB</em>, float[]<em> normStdRGB</em><span class="sig-paren">)</span><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils.bitmapToFloat32Tensor(Bitmap, int, int, int, int, float[], float[])" title="Permalink to this definition">¶</a></dt>
<dd><p>Creates new <a class="reference internal" href="Tensor.html#org.pytorch.Tensor" title="org.pytorch.Tensor"><code class="xref java java-ref docutils literal notranslate"><span class="pre">org.pytorch.Tensor</span></code></a> from specified area of <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.graphics.Bitmap</span></code>, normalized with specified in parameters mean and std.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bitmap</strong> – <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.graphics.Bitmap</span></code> as a source for Tensor data</p></li>
<li><p><strong>x</strong> – <ul>
<li><p>x coordinate of top left corner of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>y</strong> – <ul>
<li><p>y coordinate of top left corner of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>width</strong> – <ul>
<li><p>width of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>height</strong> – <ul>
<li><p>height of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>normMeanRGB</strong> – means for RGB channels normalization, length must equal 3, RGB order</p></li>
<li><p><strong>normStdRGB</strong> – standard deviation for RGB channels normalization, length must equal 3, RGB order</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</div>
<div class="section" id="bitmaptofloatbuffer">
<h3>bitmapToFloatBuffer<a class="headerlink" href="#bitmaptofloatbuffer" title="Permalink to this headline">¶</a></h3>
<dl class="method">
<dt id="org.pytorch.torchvision.TensorImageUtils.bitmapToFloatBuffer(Bitmap, int, int, int, int, float[], float[], FloatBuffer, int)">
public static void <code class="sig-name descname">bitmapToFloatBuffer</code><span class="sig-paren">(</span>Bitmap<em> bitmap</em>, int<em> x</em>, int<em> y</em>, int<em> width</em>, int<em> height</em>, float[]<em> normMeanRGB</em>, float[]<em> normStdRGB</em>, <a class="reference external" href="http://docs.oracle.com/javase/8/docs/api/java/nio/FloatBuffer.html" title="java.nio.FloatBuffer">FloatBuffer</a><em> outBuffer</em>, int<em> outBufferOffset</em><span class="sig-paren">)</span><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils.bitmapToFloatBuffer(Bitmap, int, int, int, int, float[], float[], FloatBuffer, int)" title="Permalink to this definition">¶</a></dt>
<dd><p>Writes tensor content from specified <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.graphics.Bitmap</span></code>, normalized with specified in parameters mean and std to specified <a class="reference external" href="http://docs.oracle.com/javase/8/docs/api/java/nio/FloatBuffer.html" title="java.nio.FloatBuffer"><code class="xref java java-ref docutils literal notranslate"><span class="pre">java.nio.FloatBuffer</span></code></a> with specified offset.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bitmap</strong> – <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.graphics.Bitmap</span></code> as a source for Tensor data</p></li>
<li><p><strong>x</strong> – <ul>
<li><p>x coordinate of top left corner of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>y</strong> – <ul>
<li><p>y coordinate of top left corner of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>width</strong> – <ul>
<li><p>width of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>height</strong> – <ul>
<li><p>height of bitmap’s area</p></li>
</ul>
</p></li>
<li><p><strong>normMeanRGB</strong> – means for RGB channels normalization, length must equal 3, RGB order</p></li>
<li><p><strong>normStdRGB</strong> – standard deviation for RGB channels normalization, length must equal 3, RGB order</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</div>
<div class="section" id="imageyuv420centercroptofloat32tensor">
<h3>imageYUV420CenterCropToFloat32Tensor<a class="headerlink" href="#imageyuv420centercroptofloat32tensor" title="Permalink to this headline">¶</a></h3>
<dl class="method">
<dt id="org.pytorch.torchvision.TensorImageUtils.imageYUV420CenterCropToFloat32Tensor(Image, int, int, int, float[], float[])">
public static <a class="reference internal" href="Tensor.html#org.pytorch.Tensor" title="org.pytorch.Tensor">Tensor</a> <code class="sig-name descname">imageYUV420CenterCropToFloat32Tensor</code><span class="sig-paren">(</span>Image<em> image</em>, int<em> rotateCWDegrees</em>, int<em> tensorWidth</em>, int<em> tensorHeight</em>, float[]<em> normMeanRGB</em>, float[]<em> normStdRGB</em><span class="sig-paren">)</span><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils.imageYUV420CenterCropToFloat32Tensor(Image, int, int, int, float[], float[])" title="Permalink to this definition">¶</a></dt>
<dd><p>Creates new <a class="reference internal" href="Tensor.html#org.pytorch.Tensor" title="org.pytorch.Tensor"><code class="xref java java-ref docutils literal notranslate"><span class="pre">org.pytorch.Tensor</span></code></a> from specified area of <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.media.Image</span></code>, doing optional rotation, scaling (nearest) and center cropping.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>image</strong> – <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.media.Image</span></code> as a source for Tensor data</p></li>
<li><p><strong>rotateCWDegrees</strong> – Clockwise angle through which the input image needs to be rotated to be upright. Range of valid values: 0, 90, 180, 270</p></li>
<li><p><strong>tensorWidth</strong> – return tensor width, must be positive</p></li>
<li><p><strong>tensorHeight</strong> – return tensor height, must be positive</p></li>
<li><p><strong>normMeanRGB</strong> – means for RGB channels normalization, length must equal 3, RGB order</p></li>
<li><p><strong>normStdRGB</strong> – standard deviation for RGB channels normalization, length must equal 3, RGB order</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</div>
<div class="section" id="imageyuv420centercroptofloatbuffer">
<h3>imageYUV420CenterCropToFloatBuffer<a class="headerlink" href="#imageyuv420centercroptofloatbuffer" title="Permalink to this headline">¶</a></h3>
<dl class="method">
<dt id="org.pytorch.torchvision.TensorImageUtils.imageYUV420CenterCropToFloatBuffer(Image, int, int, int, float[], float[], FloatBuffer, int)">
public static void <code class="sig-name descname">imageYUV420CenterCropToFloatBuffer</code><span class="sig-paren">(</span>Image<em> image</em>, int<em> rotateCWDegrees</em>, int<em> tensorWidth</em>, int<em> tensorHeight</em>, float[]<em> normMeanRGB</em>, float[]<em> normStdRGB</em>, <a class="reference external" href="http://docs.oracle.com/javase/8/docs/api/java/nio/FloatBuffer.html" title="java.nio.FloatBuffer">FloatBuffer</a><em> outBuffer</em>, int<em> outBufferOffset</em><span class="sig-paren">)</span><a class="headerlink" href="#org.pytorch.torchvision.TensorImageUtils.imageYUV420CenterCropToFloatBuffer(Image, int, int, int, float[], float[], FloatBuffer, int)" title="Permalink to this definition">¶</a></dt>
<dd><p>Writes tensor content from specified <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.media.Image</span></code>, doing optional rotation, scaling (nearest) and center cropping to specified <a class="reference external" href="http://docs.oracle.com/javase/8/docs/api/java/nio/FloatBuffer.html" title="java.nio.FloatBuffer"><code class="xref java java-ref docutils literal notranslate"><span class="pre">java.nio.FloatBuffer</span></code></a> with specified offset.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>image</strong> – <code class="xref java java-ref docutils literal notranslate"><span class="pre">android.media.Image</span></code> as a source for Tensor data</p></li>
<li><p><strong>rotateCWDegrees</strong> – Clockwise angle through which the input image needs to be rotated to be upright. Range of valid values: 0, 90, 180, 270</p></li>
<li><p><strong>tensorWidth</strong> – return tensor width, must be positive</p></li>
<li><p><strong>tensorHeight</strong> – return tensor height, must be positive</p></li>
<li><p><strong>normMeanRGB</strong> – means for RGB channels normalization, length must equal 3, RGB order</p></li>
<li><p><strong>normStdRGB</strong> – standard deviation for RGB channels normalization, length must equal 3, RGB order</p></li>
<li><p><strong>outBuffer</strong> – Output buffer, where tensor content will be written</p></li>
<li><p><strong>outBufferOffset</strong> – Output buffer offset with which tensor content will be written</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</div>
</div>
</div>
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<li><a class="reference internal" href="#fields">Fields</a><ul>
<li><a class="reference internal" href="#torchvision-norm-mean-rgb">TORCHVISION_NORM_MEAN_RGB</a></li>
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