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<a href="#training-a-yolox-model-for-autoware_traffic_light_fine_detector" class="md-nav__link">
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Training a YOLOX model for autoware_traffic_light_fine_detector
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📦 Example Dataset (VOC Format)
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Training a YOLOX model for autoware_traffic_light_fine_detector
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📦 Example Dataset (VOC Format)
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<p>In order to assist you with your training process, we have also included an example dataset in the TIER IV dataset format.</p>
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<p>This dataset contains 600 lidar frames and covers 5 classes, including 6905 cars, 3951 pedestrians, 75 cyclists, 162 buses, and 326 trucks.</p>
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<p>You can utilize this example dataset to facilitate your training efforts.</p>
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<h2 id="training-a-yolox-model-for-autoware_traffic_light_fine_detector">Training a YOLOX model for <code>autoware_traffic_light_fine_detector</code><a class="headerlink" href="#training-a-yolox-model-for-autoware_traffic_light_fine_detector" title="Permanent link">#</a></h2>
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<p>To train a custom YOLOX model for use with the <strong>Autoware Traffic Light Fine Detector</strong>, please refer to the official YOLOX and Autoware training guides listed below. These documents provide the required setup, data preparation steps, and export instructions.</p>
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<details class="abstract" open="open">
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<summary>Relevant documentation</summary>
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<p><strong>Autoware traffic_light_fine_detector README</strong></p>
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<p>Training overview, model requirements, and ONNX export details:
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<a href="https://github.com/autowarefoundation/autoware_universe/tree/main/perception/autoware_traffic_light_fine_detector/README.md">autoware_universe/perception/autoware_traffic_light_fine_detector/README.md</a></p>
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<p><strong>YOLOX Custom Dataset Training Guide</strong></p>
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<p>Instructions for preparing datasets, configuring experiments, and launching training:
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<a href="https://github.com/Megvii-BaseDetection/YOLOX/blob/main/docs/train_custom_data.md">YOLOX/train_custom_data.md</a></p>
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<h3 id="example-dataset-voc-format">📦 Example Dataset (VOC Format)<a class="headerlink" href="#example-dataset-voc-format" title="Permanent link">#</a></h3>
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<p>To assist with training, an example dataset containing <strong>1062 cropped traffic-light images with Pascal VOC annotations</strong> is available here:</p>
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<p><a class="md-button" href="https://autoware-files.s3.us-west-2.amazonaws.com/dataset/traffic_light_detection_sample_dataset.tar.gz"><i class="fa-solid fa-cloud-arrow-down"></i> Download the sample traffic light dataset (3 MB)</a></p>
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<li>Use the YOLOX documentation to set up your environment and prepare your dataset (VOC or COCO).</li>
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<li>Train a YOLOX model using your custom traffic-light data or the provided sample dataset.</li>
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<li>After training, export the model to <strong>ONNX</strong> following the instructions in the Autoware <code>traffic_light_fine_detector</code> README.</li>
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<li>Replace or integrate the exported ONNX model within the Autoware package for deployment.</li>
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