node-red-contrib-tfjs-pj1/index.html

custom Node-RED for classification

<!-- Node-RED UI Definition -->
<script type="text/html" data-template-name="tfjs-pj1-node">
    <div class="form-row">
      <label for="node-input-name"><i class="fa fa-tag"></i> Name</label>
      <input type="text" id="node-input-name" placeholder="Name">
    </div>
    <div class="form-row">
      <label for="node-input-modelUrl"><i class="fa fa-globe"></i> Model Url</label>
      <input type="text" id="node-input-modelUrl" placeholder="http://192.168.1.18:8080/model.json">
    </div>
    <div class="form-row">
      <label for="node-input-fromHub">Is TFHub?</label>
      <input type="checkbox" id="node-input-fromHub" checked>
    </div>
  </script>
  
  <!-- Node-RED JavaScript Registration Logic -->
  <script type="text/javascript">
    RED.nodes.registerType('tfjs-pj1-node', {
      category: 'machine learning',
      defaults: {
        name: { value: 'tfjs pj1 node' },
        modelUrl: { value: 'http://192.168.1.18:8080/model.json' },
        fromHub: { value: 'checked' }
      },
      inputs: 1,
      outputs: 1,
      paletteLabel: 'tfjs pj1 node',
      color: '#ff9100',
      label: function() {
        return this.name || 'tfjs pj1 node';
      }
    });
  </script>
  
  <!-- Node-RED Node Help Definition -->
  <script type="text/html" data-help-name="tfjs-pj1-node">
    <p>A TensorFlow.js node to run predictions for custom image classification.</p>
    <p>Provide a <strong>Model Url</strong> and indicate whether the URL points to a TFHub hosted model.</p>
    <p>The node accepts an image buffer and outputs a JSON prediction object with the detected class and its confidence score.</p>
  </script>