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| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/image/mnist.html">MNIST</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/data/datasets.html#Appendix:-Upgrading-from-Module-DataIter-to-Gluon-DataLoader">Appendix: Upgrading from Module <code class="docutils literal notranslate"><span class="pre">DataIter</span></code> to Gluon <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/image/mnist.html">Handwritten Digit Recognition</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/image/pretrained_models.html">Using pre-trained models in MXNet</a></li> |
| </ul> |
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| <li class="toctree-l4"><a class="reference internal" href="../../../../../tutorials/packages/gluon/loss/index.html">Losses</a><ul> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/loss/kl_divergence.html">Kullback-Leibler (KL) Divergence</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/loss/loss.html">Loss functions</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/text/gnmt.html">Google Neural Machine Translation</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/text/transformer.html">Machine Translation with Transformer</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/training/learning_rates/index.html">Learning Rates</a><ul> |
| <li class="toctree-l6"><a class="reference internal" href="../../../../../tutorials/packages/gluon/training/learning_rates/learning_rate_finder.html">Learning Rate Finder</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../../../tutorials/packages/gluon/training/learning_rates/learning_rate_schedules.html">Learning Rate Schedules</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../../../tutorials/packages/gluon/training/learning_rates/learning_rate_schedules_advanced.html">Advanced Learning Rate Schedules</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/training/normalization/index.html">Normalization Blocks</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="../../../../../tutorials/packages/ndarray/index.html">NDArray</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../../../tutorials/packages/ndarray/01-ndarray-intro.html">An Intro: Manipulate Data the MXNet Way with NDArray</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="../../../../../tutorials/packages/ndarray/gotchas_numpy_in_mxnet.html">Gotchas using NumPy in Apache MXNet</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/ndarray/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/ndarray/sparse/row_sparse.html">RowSparseNDArray - NDArray for Sparse Gradient Updates</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/ndarray/sparse/train.html">Train a Linear Regression Model with Sparse Symbols</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/ndarray/sparse/train_gluon.html">Sparse NDArrays with Gluon</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/data/datasets.html#Appendix:-Upgrading-from-Module-DataIter-to-Gluon-DataLoader">Appendix: Upgrading from Module <code class="docutils literal notranslate"><span class="pre">DataIter</span></code> to Gluon <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../../../../tutorials/packages/gluon/image/pretrained_models.html">Using pre-trained models in MXNet</a></li> |
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| <h1>Source code for mxnet.gluon.data.vision.datasets</h1><div class="highlight"><pre> |
| <span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span> |
| <span class="c1"># or more contributor license agreements. See the NOTICE file</span> |
| <span class="c1"># distributed with this work for additional information</span> |
| <span class="c1"># regarding copyright ownership. The ASF licenses this file</span> |
| <span class="c1"># to you under the Apache License, Version 2.0 (the</span> |
| <span class="c1"># "License"); you may not use this file except in compliance</span> |
| <span class="c1"># with the License. You may obtain a copy of the License at</span> |
| <span class="c1">#</span> |
| <span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span> |
| <span class="c1">#</span> |
| <span class="c1"># Unless required by applicable law or agreed to in writing,</span> |
| <span class="c1"># software distributed under the License is distributed on an</span> |
| <span class="c1"># "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span> |
| <span class="c1"># KIND, either express or implied. See the License for the</span> |
| <span class="c1"># specific language governing permissions and limitations</span> |
| <span class="c1"># under the License.</span> |
| |
| <span class="c1"># coding: utf-8</span> |
| <span class="c1"># pylint: disable=</span> |
| <span class="sd">"""Dataset container."""</span> |
| <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'MNIST'</span><span class="p">,</span> <span class="s1">'FashionMNIST'</span><span class="p">,</span> <span class="s1">'CIFAR10'</span><span class="p">,</span> <span class="s1">'CIFAR100'</span><span class="p">,</span> |
| <span class="s1">'ImageRecordDataset'</span><span class="p">,</span> <span class="s1">'ImageFolderDataset'</span><span class="p">]</span> |
| |
| <span class="kn">import</span> <span class="nn">os</span> |
| <span class="kn">import</span> <span class="nn">gzip</span> |
| <span class="kn">import</span> <span class="nn">tarfile</span> |
| <span class="kn">import</span> <span class="nn">struct</span> |
| <span class="kn">import</span> <span class="nn">warnings</span> |
| <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> |
| |
| <span class="kn">from</span> <span class="nn">..</span> <span class="kn">import</span> <span class="n">dataset</span> |
| <span class="kn">from</span> <span class="nn">...utils</span> <span class="kn">import</span> <span class="n">download</span><span class="p">,</span> <span class="n">check_sha1</span><span class="p">,</span> <span class="n">_get_repo_file_url</span> |
| <span class="kn">from</span> <span class="nn">....</span> <span class="kn">import</span> <span class="n">nd</span><span class="p">,</span> <span class="n">image</span><span class="p">,</span> <span class="n">recordio</span><span class="p">,</span> <span class="n">base</span> |
| <span class="kn">from</span> <span class="nn">....</span> <span class="kn">import</span> <span class="n">numpy</span> <span class="k">as</span> <span class="n">_mx_np</span> <span class="c1"># pylint: disable=reimported</span> |
| <span class="kn">from</span> <span class="nn">....util</span> <span class="kn">import</span> <span class="n">is_np_array</span> |
| |
| |
| <div class="viewcode-block" id="MNIST"><a class="viewcode-back" href="../../../../../api/gluon/data/vision/datasets/index.html#mxnet.gluon.data.vision.datasets.MNIST">[docs]</a><span class="k">class</span> <span class="nc">MNIST</span><span class="p">(</span><span class="n">dataset</span><span class="o">.</span><span class="n">_DownloadedDataset</span><span class="p">):</span> |
| <span class="sd">"""MNIST handwritten digits dataset from http://yann.lecun.com/exdb/mnist</span> |
| |
| <span class="sd"> Each sample is an image (in 3D NDArray) with shape (28, 28, 1).</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> root : str, default $MXNET_HOME/datasets/mnist</span> |
| <span class="sd"> Path to temp folder for storing data.</span> |
| <span class="sd"> train : bool, default True</span> |
| <span class="sd"> Whether to load the training or testing set.</span> |
| <span class="sd"> transform : function, default None</span> |
| <span class="sd"> A user defined callback that transforms each sample. For example::</span> |
| |
| <span class="sd"> transform=lambda data, label: (data.astype(np.float32)/255, label)</span> |
| |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">root</span><span class="o">=</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">base</span><span class="o">.</span><span class="n">data_dir</span><span class="p">(),</span> <span class="s1">'datasets'</span><span class="p">,</span> <span class="s1">'mnist'</span><span class="p">),</span> |
| <span class="n">train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train</span> <span class="o">=</span> <span class="n">train</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train_data</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'train-images-idx3-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'6c95f4b05d2bf285e1bfb0e7960c31bd3b3f8a7d'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train_label</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'train-labels-idx1-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'2a80914081dc54586dbdf242f9805a6b8d2a15fc'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_test_data</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'t10k-images-idx3-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'c3a25af1f52dad7f726cce8cacb138654b760d48'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_test_label</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'t10k-labels-idx1-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'763e7fa3757d93b0cdec073cef058b2004252c17'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_namespace</span> <span class="o">=</span> <span class="s1">'mnist'</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">MNIST</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">_get_data</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train</span><span class="p">:</span> |
| <span class="n">data</span><span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train_data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train_label</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">data</span><span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_test_data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_test_label</span> |
| |
| <span class="n">namespace</span> <span class="o">=</span> <span class="s1">'gluon/dataset/'</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">_namespace</span> |
| <span class="n">data_file</span> <span class="o">=</span> <span class="n">download</span><span class="p">(</span><span class="n">_get_repo_file_url</span><span class="p">(</span><span class="n">namespace</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> |
| <span class="n">path</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_root</span><span class="p">,</span> |
| <span class="n">sha1_hash</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> |
| <span class="n">label_file</span> <span class="o">=</span> <span class="n">download</span><span class="p">(</span><span class="n">_get_repo_file_url</span><span class="p">(</span><span class="n">namespace</span><span class="p">,</span> <span class="n">label</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> |
| <span class="n">path</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_root</span><span class="p">,</span> |
| <span class="n">sha1_hash</span><span class="o">=</span><span class="n">label</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> |
| |
| <span class="k">with</span> <span class="n">gzip</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">label_file</span><span class="p">,</span> <span class="s1">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">fin</span><span class="p">:</span> |
| <span class="n">struct</span><span class="o">.</span><span class="n">unpack</span><span class="p">(</span><span class="s2">">II"</span><span class="p">,</span> <span class="n">fin</span><span class="o">.</span><span class="n">read</span><span class="p">(</span><span class="mi">8</span><span class="p">))</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">frombuffer</span><span class="p">(</span><span class="n">fin</span><span class="o">.</span><span class="n">read</span><span class="p">(),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</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">int32</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">is_np_array</span><span class="p">():</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="n">_mx_np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">label</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">label</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> |
| |
| <span class="k">with</span> <span class="n">gzip</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">data_file</span><span class="p">,</span> <span class="s1">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">fin</span><span class="p">:</span> |
| <span class="n">struct</span><span class="o">.</span><span class="n">unpack</span><span class="p">(</span><span class="s2">">IIII"</span><span class="p">,</span> <span class="n">fin</span><span class="o">.</span><span class="n">read</span><span class="p">(</span><span class="mi">16</span><span class="p">))</span> |
| <span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">frombuffer</span><span class="p">(</span><span class="n">fin</span><span class="o">.</span><span class="n">read</span><span class="p">(),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span> |
| <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">label</span><span class="p">),</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span> |
| |
| <span class="n">array_fn</span> <span class="o">=</span> <span class="n">_mx_np</span><span class="o">.</span><span class="n">array</span> <span class="k">if</span> <span class="n">is_np_array</span><span class="p">()</span> <span class="k">else</span> <span class="n">nd</span><span class="o">.</span><span class="n">array</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_data</span> <span class="o">=</span> <span class="n">array_fn</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_label</span> <span class="o">=</span> <span class="n">label</span></div> |
| |
| |
| <div class="viewcode-block" id="FashionMNIST"><a class="viewcode-back" href="../../../../../api/gluon/data/vision/datasets/index.html#mxnet.gluon.data.vision.datasets.FashionMNIST">[docs]</a><span class="k">class</span> <span class="nc">FashionMNIST</span><span class="p">(</span><span class="n">MNIST</span><span class="p">):</span> |
| <span class="sd">"""A dataset of Zalando's article images consisting of fashion products,</span> |
| <span class="sd"> a drop-in replacement of the original MNIST dataset from</span> |
| <span class="sd"> https://github.com/zalandoresearch/fashion-mnist</span> |
| |
| <span class="sd"> Each sample is an image (in 3D NDArray) with shape (28, 28, 1).</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> root : str, default $MXNET_HOME/datasets/fashion-mnist'</span> |
| <span class="sd"> Path to temp folder for storing data.</span> |
| <span class="sd"> train : bool, default True</span> |
| <span class="sd"> Whether to load the training or testing set.</span> |
| <span class="sd"> transform : function, default None</span> |
| <span class="sd"> A user defined callback that transforms each sample. For example::</span> |
| |
| <span class="sd"> transform=lambda data, label: (data.astype(np.float32)/255, label)</span> |
| |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">root</span><span class="o">=</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">base</span><span class="o">.</span><span class="n">data_dir</span><span class="p">(),</span> <span class="s1">'datasets'</span><span class="p">,</span> <span class="s1">'fashion-mnist'</span><span class="p">),</span> |
| <span class="n">train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train</span> <span class="o">=</span> <span class="n">train</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train_data</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'train-images-idx3-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'0cf37b0d40ed5169c6b3aba31069a9770ac9043d'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train_label</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'train-labels-idx1-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'236021d52f1e40852b06a4c3008d8de8aef1e40b'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_test_data</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'t10k-images-idx3-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'626ed6a7c06dd17c0eec72fa3be1740f146a2863'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_test_label</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'t10k-labels-idx1-ubyte.gz'</span><span class="p">,</span> |
| <span class="s1">'17f9ab60e7257a1620f4ad76bbbaf857c3920701'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_namespace</span> <span class="o">=</span> <span class="s1">'fashion-mnist'</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">MNIST</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span> <span class="c1"># pylint: disable=bad-super-call</span></div> |
| |
| |
| <div class="viewcode-block" id="CIFAR10"><a class="viewcode-back" href="../../../../../api/gluon/data/vision/datasets/index.html#mxnet.gluon.data.vision.datasets.CIFAR10">[docs]</a><span class="k">class</span> <span class="nc">CIFAR10</span><span class="p">(</span><span class="n">dataset</span><span class="o">.</span><span class="n">_DownloadedDataset</span><span class="p">):</span> |
| <span class="sd">"""CIFAR10 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html</span> |
| |
| <span class="sd"> Each sample is an image (in 3D NDArray) with shape (32, 32, 3).</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> root : str, default $MXNET_HOME/datasets/cifar10</span> |
| <span class="sd"> Path to temp folder for storing data.</span> |
| <span class="sd"> train : bool, default True</span> |
| <span class="sd"> Whether to load the training or testing set.</span> |
| <span class="sd"> transform : function, default None</span> |
| <span class="sd"> A user defined callback that transforms each sample. For example::</span> |
| |
| <span class="sd"> transform=lambda data, label: (data.astype(np.float32)/255, label)</span> |
| |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">root</span><span class="o">=</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">base</span><span class="o">.</span><span class="n">data_dir</span><span class="p">(),</span> <span class="s1">'datasets'</span><span class="p">,</span> <span class="s1">'cifar10'</span><span class="p">),</span> |
| <span class="n">train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train</span> <span class="o">=</span> <span class="n">train</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_archive_file</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'cifar-10-binary.tar.gz'</span><span class="p">,</span> <span class="s1">'fab780a1e191a7eda0f345501ccd62d20f7ed891'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train_data</span> <span class="o">=</span> <span class="p">[(</span><span class="s1">'data_batch_1.bin'</span><span class="p">,</span> <span class="s1">'aadd24acce27caa71bf4b10992e9e7b2d74c2540'</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'data_batch_2.bin'</span><span class="p">,</span> <span class="s1">'c0ba65cce70568cd57b4e03e9ac8d2a5367c1795'</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'data_batch_3.bin'</span><span class="p">,</span> <span class="s1">'1dd00a74ab1d17a6e7d73e185b69dbf31242f295'</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'data_batch_4.bin'</span><span class="p">,</span> <span class="s1">'aab85764eb3584312d3c7f65fd2fd016e36a258e'</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'data_batch_5.bin'</span><span class="p">,</span> <span class="s1">'26e2849e66a845b7f1e4614ae70f4889ae604628'</span><span class="p">)]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_test_data</span> <span class="o">=</span> <span class="p">[(</span><span class="s1">'test_batch.bin'</span><span class="p">,</span> <span class="s1">'67eb016db431130d61cd03c7ad570b013799c88c'</span><span class="p">)]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_namespace</span> <span class="o">=</span> <span class="s1">'cifar10'</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">CIFAR10</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">_read_batch</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">):</span> |
| <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="s1">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">fin</span><span class="p">:</span> |
| <span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">frombuffer</span><span class="p">(</span><span class="n">fin</span><span class="o">.</span><span class="n">read</span><span class="p">(),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3072</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> |
| |
| <span class="k">return</span> <span class="n">data</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">:]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</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">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="n">data</span><span class="p">[:,</span> <span class="mi">0</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">int32</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">_get_data</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="n">path</span><span class="p">)</span> <span class="ow">or</span> <span class="ow">not</span> <span class="n">check_sha1</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">sha1</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">path</span><span class="p">,</span> <span class="n">sha1</span> <span class="ow">in</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="bp">self</span><span class="o">.</span><span class="n">_root</span><span class="p">,</span> <span class="n">name</span><span class="p">),</span> <span class="n">sha1</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sha1</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train_data</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">_test_data</span><span class="p">)):</span> |
| <span class="n">namespace</span> <span class="o">=</span> <span class="s1">'gluon/dataset/'</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">_namespace</span> |
| <span class="n">filename</span> <span class="o">=</span> <span class="n">download</span><span class="p">(</span><span class="n">_get_repo_file_url</span><span class="p">(</span><span class="n">namespace</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_archive_file</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> |
| <span class="n">path</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_root</span><span class="p">,</span> |
| <span class="n">sha1_hash</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_archive_file</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> |
| |
| <span class="k">with</span> <span class="n">tarfile</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">filename</span><span class="p">)</span> <span class="k">as</span> <span class="n">tar</span><span class="p">:</span> |
| <span class="n">tar</span><span class="o">.</span><span class="n">extractall</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_root</span><span class="p">)</span> |
| |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train</span><span class="p">:</span> |
| <span class="n">data_files</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train_data</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">data_files</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_test_data</span> |
| <span class="n">data</span><span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_read_batch</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="bp">self</span><span class="o">.</span><span class="n">_root</span><span class="p">,</span> <span class="n">name</span><span class="p">))</span> |
| <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">_</span> <span class="ow">in</span> <span class="n">data_files</span><span class="p">))</span> |
| <span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">label</span><span class="p">)</span> |
| |
| <span class="n">array_fn</span> <span class="o">=</span> <span class="n">_mx_np</span><span class="o">.</span><span class="n">array</span> <span class="k">if</span> <span class="n">is_np_array</span><span class="p">()</span> <span class="k">else</span> <span class="n">nd</span><span class="o">.</span><span class="n">array</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_data</span> <span class="o">=</span> <span class="n">array_fn</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_label</span> <span class="o">=</span> <span class="n">array_fn</span><span class="p">(</span><span class="n">label</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">label</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> <span class="k">if</span> <span class="n">is_np_array</span><span class="p">()</span> <span class="k">else</span> <span class="n">label</span></div> |
| |
| |
| <div class="viewcode-block" id="CIFAR100"><a class="viewcode-back" href="../../../../../api/gluon/data/vision/datasets/index.html#mxnet.gluon.data.vision.datasets.CIFAR100">[docs]</a><span class="k">class</span> <span class="nc">CIFAR100</span><span class="p">(</span><span class="n">CIFAR10</span><span class="p">):</span> |
| <span class="sd">"""CIFAR100 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html</span> |
| |
| <span class="sd"> Each sample is an image (in 3D NDArray) with shape (32, 32, 3).</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> root : str, default $MXNET_HOME/datasets/cifar100</span> |
| <span class="sd"> Path to temp folder for storing data.</span> |
| <span class="sd"> fine_label : bool, default False</span> |
| <span class="sd"> Whether to load the fine-grained (100 classes) or coarse-grained (20 super-classes) labels.</span> |
| <span class="sd"> train : bool, default True</span> |
| <span class="sd"> Whether to load the training or testing set.</span> |
| <span class="sd"> transform : function, default None</span> |
| <span class="sd"> A user defined callback that transforms each sample. For example::</span> |
| |
| <span class="sd"> transform=lambda data, label: (data.astype(np.float32)/255, label)</span> |
| |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">root</span><span class="o">=</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">base</span><span class="o">.</span><span class="n">data_dir</span><span class="p">(),</span> <span class="s1">'datasets'</span><span class="p">,</span> <span class="s1">'cifar100'</span><span class="p">),</span> |
| <span class="n">fine_label</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train</span> <span class="o">=</span> <span class="n">train</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_archive_file</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'cifar-100-binary.tar.gz'</span><span class="p">,</span> <span class="s1">'a0bb982c76b83111308126cc779a992fa506b90b'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_train_data</span> <span class="o">=</span> <span class="p">[(</span><span class="s1">'train.bin'</span><span class="p">,</span> <span class="s1">'e207cd2e05b73b1393c74c7f5e7bea451d63e08e'</span><span class="p">)]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_test_data</span> <span class="o">=</span> <span class="p">[(</span><span class="s1">'test.bin'</span><span class="p">,</span> <span class="s1">'8fb6623e830365ff53cf14adec797474f5478006'</span><span class="p">)]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_fine_label</span> <span class="o">=</span> <span class="n">fine_label</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_namespace</span> <span class="o">=</span> <span class="s1">'cifar100'</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">CIFAR10</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span> <span class="c1"># pylint: disable=bad-super-call</span> |
| |
| <span class="k">def</span> <span class="nf">_read_batch</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">):</span> |
| <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="s1">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">fin</span><span class="p">:</span> |
| <span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">frombuffer</span><span class="p">(</span><span class="n">fin</span><span class="o">.</span><span class="n">read</span><span class="p">(),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3072</span><span class="o">+</span><span class="mi">2</span><span class="p">)</span> |
| |
| <span class="k">return</span> <span class="n">data</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">:]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</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">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="n">data</span><span class="p">[:,</span> <span class="mi">0</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">_fine_label</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">int32</span><span class="p">)</span></div> |
| |
| |
| <div class="viewcode-block" id="ImageRecordDataset"><a class="viewcode-back" href="../../../../../api/gluon/data/vision/datasets/index.html#mxnet.gluon.data.vision.datasets.ImageRecordDataset">[docs]</a><span class="k">class</span> <span class="nc">ImageRecordDataset</span><span class="p">(</span><span class="n">dataset</span><span class="o">.</span><span class="n">RecordFileDataset</span><span class="p">):</span> |
| <span class="sd">"""A dataset wrapping over a RecordIO file containing images.</span> |
| |
| <span class="sd"> Each sample is an image and its corresponding label.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> filename : str</span> |
| <span class="sd"> Path to rec file.</span> |
| <span class="sd"> flag : {0, 1}, default 1</span> |
| <span class="sd"> If 0, always convert images to greyscale. \</span> |
| <span class="sd"> If 1, always convert images to colored (RGB).</span> |
| <span class="sd"> transform : function, default None</span> |
| <span class="sd"> A user defined callback that transforms each sample. For example::</span> |
| |
| <span class="sd"> transform=lambda data, label: (data.astype(np.float32)/255, label)</span> |
| |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">,</span> <span class="n">flag</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">ImageRecordDataset</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">filename</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_flag</span> <span class="o">=</span> <span class="n">flag</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="n">transform</span> |
| |
| <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">idx</span><span class="p">):</span> |
| <span class="n">record</span> <span class="o">=</span> <span class="nb">super</span><span class="p">(</span><span class="n">ImageRecordDataset</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__getitem__</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span> |
| <span class="n">header</span><span class="p">,</span> <span class="n">img</span> <span class="o">=</span> <span class="n">recordio</span><span class="o">.</span><span class="n">unpack</span><span class="p">(</span><span class="n">record</span><span class="p">)</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span><span class="p">(</span><span class="n">image</span><span class="o">.</span><span class="n">imdecode</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_flag</span><span class="p">),</span> <span class="n">header</span><span class="o">.</span><span class="n">label</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">image</span><span class="o">.</span><span class="n">imdecode</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_flag</span><span class="p">),</span> <span class="n">header</span><span class="o">.</span><span class="n">label</span></div> |
| |
| |
| <div class="viewcode-block" id="ImageFolderDataset"><a class="viewcode-back" href="../../../../../api/gluon/data/vision/datasets/index.html#mxnet.gluon.data.vision.datasets.ImageFolderDataset">[docs]</a><span class="k">class</span> <span class="nc">ImageFolderDataset</span><span class="p">(</span><span class="n">dataset</span><span class="o">.</span><span class="n">Dataset</span><span class="p">):</span> |
| <span class="sd">"""A dataset for loading image files stored in a folder structure.</span> |
| |
| <span class="sd"> like::</span> |
| |
| <span class="sd"> root/car/0001.jpg</span> |
| <span class="sd"> root/car/xxxa.jpg</span> |
| <span class="sd"> root/car/yyyb.jpg</span> |
| <span class="sd"> root/bus/123.jpg</span> |
| <span class="sd"> root/bus/023.jpg</span> |
| <span class="sd"> root/bus/wwww.jpg</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> root : str</span> |
| <span class="sd"> Path to root directory.</span> |
| <span class="sd"> flag : {0, 1}, default 1</span> |
| <span class="sd"> If 0, always convert loaded images to greyscale (1 channel).</span> |
| <span class="sd"> If 1, always convert loaded images to colored (3 channels).</span> |
| <span class="sd"> transform : callable, default None</span> |
| <span class="sd"> A function that takes data and label and transforms them::</span> |
| |
| <span class="sd"> transform = lambda data, label: (data.astype(np.float32)/255, label)</span> |
| |
| <span class="sd"> Attributes</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> synsets : list</span> |
| <span class="sd"> List of class names. `synsets[i]` is the name for the integer label `i`</span> |
| <span class="sd"> items : list of tuples</span> |
| <span class="sd"> List of all images in (filename, label) pairs.</span> |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">root</span><span class="p">,</span> <span class="n">flag</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_root</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">expanduser</span><span class="p">(</span><span class="n">root</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_flag</span> <span class="o">=</span> <span class="n">flag</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="n">transform</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_exts</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'.jpg'</span><span class="p">,</span> <span class="s1">'.jpeg'</span><span class="p">,</span> <span class="s1">'.png'</span><span class="p">]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_list_images</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_root</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">_list_images</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">root</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">synsets</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">items</span> <span class="o">=</span> <span class="p">[]</span> |
| |
| <span class="k">for</span> <span class="n">folder</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">listdir</span><span class="p">(</span><span class="n">root</span><span class="p">)):</span> |
| <span class="n">path</span> <span class="o">=</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">root</span><span class="p">,</span> <span class="n">folder</span><span class="p">)</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">isdir</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">'Ignoring </span><span class="si">%s</span><span class="s1">, which is not a directory.'</span><span class="o">%</span><span class="n">path</span><span class="p">,</span> <span class="n">stacklevel</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span> |
| <span class="k">continue</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">synsets</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">synsets</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">folder</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">filename</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">listdir</span><span class="p">(</span><span class="n">path</span><span class="p">)):</span> |
| <span class="n">filename</span> <span class="o">=</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">path</span><span class="p">,</span> <span class="n">filename</span><span class="p">)</span> |
| <span class="n">ext</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">splitext</span><span class="p">(</span><span class="n">filename</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span> |
| <span class="k">if</span> <span class="n">ext</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_exts</span><span class="p">:</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">'Ignoring </span><span class="si">%s</span><span class="s1"> of type </span><span class="si">%s</span><span class="s1">. Only support </span><span class="si">%s</span><span class="s1">'</span><span class="o">%</span><span class="p">(</span> |
| <span class="n">filename</span><span class="p">,</span> <span class="n">ext</span><span class="p">,</span> <span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_exts</span><span class="p">)))</span> |
| <span class="k">continue</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">items</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">filename</span><span class="p">,</span> <span class="n">label</span><span class="p">))</span> |
| |
| <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">idx</span><span class="p">):</span> |
| <span class="n">img</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">items</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="mi">0</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">_flag</span><span class="p">)</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">items</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">label</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">img</span><span class="p">,</span> <span class="n">label</span> |
| |
| <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">items</span><span class="p">)</span></div> |
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