Updated docs

Author: dpascualhe

docs/_pages/v2/usage.md

@@ -44,6 +44,8 @@ Options:
   --dataset_fname FILE            Parquet dataset file
   --dataset_dir DIRECTORY         Dataset directory (used for 'Rellis3D'
                                   format)
+  --split_dir DIRECTORY           Directory containing .lst split files (used
+                                  for 'Rellis3D' format)
   --train_dataset_dir DIRECTORY   Train dataset directory (used for 'GOOSE'
                                   and 'Generic' formats)
   --val_dataset_dir DIRECTORY     Validation dataset directory (used for
@@ -108,12 +110,13 @@ dataset:
     format: gaia  # Dataset format (e.g., gaia, rellis3d, goose, generic)
     fname: "/path/to/dataset.parquet"  # (For Gaia) Path to the dataset Parquet file
     dir: "/path/to/dataset_directory"  # (For Rellis3D) Path to the dataset directory
+    split_dir: "/path/to/split_directory"  # (For Rellis3D) Path to the directory containing .lst split files
     train_dir: "/path/to/train_dataset_directory"  # (For Goose/Generic) Train directory
     val_dir: "/path/to/val_dataset_directory"  # (For Goose/Generic) Validation directory
     test_dir: "/path/to/test_dataset_directory"  # (For Goose/Generic) Test directory
     data_suffix: "_image.jpg"  # (For Generic) Data suffix
     label_suffix: "_label.png"  # (For Generic) Label suffix
-    ontology: "/path/to/dataset_ontology.json"  # (For Generic) Path to dataset ontology
+    ontology: "/path/to/dataset_ontology.json"  # (For Rellis3D/Generic) Path to dataset ontology
     split: test  # Dataset split to evaluate (e.g., train, val, test)
   - id: "another_dataset_id"
     # ...

docs/py_docs/_build/doctrees/detectionmetrics.cli.doctree

@@ -81,7 +81,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Link to this headi
 <span id="detectionmetrics-cli-evaluate-module"></span><h2>detectionmetrics.cli.evaluate module<a class="headerlink" href="#module-detectionmetrics.cli.evaluate" title="Link to this heading"></a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="detectionmetrics.cli.evaluate.get_dataset">
-<span class="sig-prename descclassname"><span class="pre">detectionmetrics.cli.evaluate.</span></span><span class="sig-name descname"><span class="pre">get_dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_type</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset_format</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset_fname</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_suffix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label_suffix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ontology</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">split</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#detectionmetrics.cli.evaluate.get_dataset" title="Link to this definition"></a></dt>
+<span class="sig-prename descclassname"><span class="pre">detectionmetrics.cli.evaluate.</span></span><span class="sig-name descname"><span class="pre">get_dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_type</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset_format</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset_fname</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">split_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_dataset_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_suffix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">label_suffix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ontology</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">split</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#detectionmetrics.cli.evaluate.get_dataset" title="Link to this definition"></a></dt>
 <dd></dd></dl>
 
 <dl class="py function">

docs/py_docs/_build/doctrees/detectionmetrics.utils.doctree

@@ -215,9 +215,10 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Link to this hea
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="detectionmetrics.utils.html#module-detectionmetrics.utils.metrics">detectionmetrics.utils.metrics module</a><ul>
-<li class="toctree-l3"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.Accuracy"><code class="docutils literal notranslate"><span class="pre">Accuracy</span></code></a><ul>
-<li class="toctree-l4"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.Accuracy.compute"><code class="docutils literal notranslate"><span class="pre">Accuracy.compute()</span></code></a></li>
-<li class="toctree-l4"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.Accuracy.update"><code class="docutils literal notranslate"><span class="pre">Accuracy.update()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.ConfusionMatrix"><code class="docutils literal notranslate"><span class="pre">ConfusionMatrix</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.ConfusionMatrix.compute"><code class="docutils literal notranslate"><span class="pre">ConfusionMatrix.compute()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.ConfusionMatrix.get_accuracy"><code class="docutils literal notranslate"><span class="pre">ConfusionMatrix.get_accuracy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.ConfusionMatrix.update"><code class="docutils literal notranslate"><span class="pre">ConfusionMatrix.update()</span></code></a></li>
 </ul>
 </li>
 <li class="toctree-l3"><a class="reference internal" href="detectionmetrics.utils.html#detectionmetrics.utils.metrics.IoU"><code class="docutils literal notranslate"><span class="pre">IoU</span></code></a><ul>

docs/py_docs/_build/doctrees/environment.pickle

@@ -276,48 +276,63 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Link to this headi
 <section id="module-detectionmetrics.utils.metrics">
 <span id="detectionmetrics-utils-metrics-module"></span><h2>detectionmetrics.utils.metrics module<a class="headerlink" href="#module-detectionmetrics.utils.metrics" title="Link to this heading"></a></h2>
 <dl class="py class">
-<dt class="sig sig-object py" id="detectionmetrics.utils.metrics.Accuracy">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">detectionmetrics.utils.metrics.</span></span><span class="sig-name descname"><span class="pre">Accuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_classes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#detectionmetrics.utils.metrics.Accuracy" title="Link to this definition"></a></dt>
-<dd><p>Bases: <a class="reference internal" href="#detectionmetrics.utils.metrics.Metric" title="detectionmetrics.utils.metrics.Metric"><code class="xref py py-class docutils literal notranslate"><span class="pre">Metric</span></code></a></p>
-<p>Compute accuracy as:</p>
-<div class="math notranslate nohighlight">
-\[\text{Accuracy} = \frac{1}{N}\sum_i^N 1(y_i = \hat{y}_i)\]</div>
-<p>Accuracy per sample and class is accumulated and then the average per class is
-computed.</p>
+<dt class="sig sig-object py" id="detectionmetrics.utils.metrics.ConfusionMatrix">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">detectionmetrics.utils.metrics.</span></span><span class="sig-name descname"><span class="pre">ConfusionMatrix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_classes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#detectionmetrics.utils.metrics.ConfusionMatrix" title="Link to this definition"></a></dt>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
+<p>Class to compute and store the confusion matrix, as well as related metrics
+(e.g. accuracy, precision, recall, etc.)</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>n_classes</strong> (<em>int</em>) – Number of classes to evaluate</p>
 </dd>
 </dl>
 <dl class="py method">
-<dt class="sig sig-object py" id="detectionmetrics.utils.metrics.Accuracy.compute">
-<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#detectionmetrics.utils.metrics.Accuracy.compute" title="Link to this definition"></a></dt>
-<dd><p>Get accuracy (global and per class)</p>
+<dt class="sig sig-object py" id="detectionmetrics.utils.metrics.ConfusionMatrix.compute">
+<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="headerlink" href="#detectionmetrics.utils.metrics.ConfusionMatrix.compute" title="Link to this definition"></a></dt>
+<dd><p>Get confusion matrix</p>
+<dl class="field-list simple">
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
+<dd class="field-odd"><p>confusion matrix</p>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p>np.ndarray</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="detectionmetrics.utils.metrics.ConfusionMatrix.get_accuracy">
+<span class="sig-name descname"><span class="pre">get_accuracy</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#detectionmetrics.utils.metrics.ConfusionMatrix.get_accuracy" title="Link to this definition"></a></dt>
+<dd><p>Compute accuracy from confusion matrix as:</p>
+<div class="math notranslate nohighlight">
+\[\text{Accuracy} = \frac{1}{N}\sum_i^N 1(y_i = \hat{y}_i)\]</div>
 <dl class="field-list simple">
 <dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>per class accuracy, and global accuracy</p>
 </dd>
 <dt class="field-even">Return type<span class="colon">:</span></dt>
-<dd class="field-even"><p>Tuple[float, np.ndarray]</p>
+<dd class="field-even"><p>Tuple[np.ndarray, float]</p>
 </dd>
 </dl>
 </dd></dl>
 
 <dl class="py method">
-<dt class="sig sig-object py" id="detectionmetrics.utils.metrics.Accuracy.update">
-<span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pred</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">valid_mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#detectionmetrics.utils.metrics.Accuracy.update" title="Link to this definition"></a></dt>
-<dd><p>Accumulate accuracy values for a new set of samples</p>
+<dt class="sig sig-object py" id="detectionmetrics.utils.metrics.ConfusionMatrix.update">
+<span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pred</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">valid_mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="headerlink" href="#detectionmetrics.utils.metrics.ConfusionMatrix.update" title="Link to this definition"></a></dt>
+<dd><p>Update the confusion matrix with new predictions and ground truth</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>pred</strong> (<em>np.ndarray</em>) – label encoded prediction array (batch, width, height)</p></li>
-<li><p><strong>gt</strong> (<em>np.ndarray</em>) – label encoded ground truth array (batch, width, height)</p></li>
-<li><p><strong>valid_mask</strong> – Binary mask where False elements will be igonred, defaults</p></li>
+<li><p><strong>pred</strong> (<em>np.ndarray</em>) – Array containing prediction</p></li>
+<li><p><strong>gt</strong> (<em>np.ndarray</em>) – Array containing ground truth</p></li>
+<li><p><strong>valid_mask</strong> – Binary mask where False elements will be ignored, defaults</p></li>
 </ul>
 </dd>
 </dl>
 <p>to None
-:type valid_mask: Optional[np.ndarray], optional</p>
+:type valid_mask: Optional[np.ndarray], optional
+:return: Updated confusion matrix
+:rtype: np.ndarray</p>
 </dd></dl>
 
 </dd></dl>
@@ -336,10 +351,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Link to this headi
 <dl class="py method">
 <dt class="sig sig-object py" id="detectionmetrics.utils.metrics.IoU.compute">
 <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="headerlink" href="#detectionmetrics.utils.metrics.IoU.compute" title="Link to this definition"></a></dt>
-<dd><p>Get IoU (global and per class)</p>
+<dd><p>Get IoU (per class and mIoU)</p>
 <dl class="field-list simple">
 <dt class="field-odd">Returns<span class="colon">:</span></dt>
-<dd class="field-odd"><p>per class IoU, and global IoU</p>
+<dd class="field-odd"><p>per class IoU, and mean IoU</p>
 </dd>
 <dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>Tuple[float, np.ndarray]</p>