xml update the modeler

htlm_webpage.py

@@ -65,7 +65,7 @@ def display_bpmn_xml(bpmn_xml):
         <div id="button-container">
             <button id="save-button">Save as BPMN</button>
             <button id="download-button">Save as XML</button>
-            <button id="download-button">Save as Vizi (not available for now)</button>
+            <button id="save-button">Save as Method&Style (not available now)</button>
         </div>
         <div id="canvas-container">
             <div id="canvas"></div>
@@ -103,15 +103,20 @@ def display_bpmn_xml(bpmn_xml):
             }}
 
             async function downloadXML() {{
-                const xml = `{bpmn_xml}`;
-                const blob = new Blob([xml], {{ type: 'text/xml' }});
-                const url = URL.createObjectURL(blob);
-                const a = document.createElement('a');
-                a.href = url;
-                a.download = 'diagram.xml';
-                document.body.appendChild(a);
-                a.click();
-                document.body.removeChild(a);
+                try {{
+                    const result = await bpmnModeler.saveXML({{ format: true }});
+                    const xml = result.xml;
+                    const blob = new Blob([xml], {{ type: 'text/xml' }});
+                    const url = URL.createObjectURL(blob);
+                    const a = document.createElement('a');
+                    a.href = url;
+                    a.download = 'diagram.xml';
+                    document.body.appendChild(a);
+                    a.click();
+                    document.body.removeChild(a);
+                }} catch (err) {{
+                    console.error('Error downloading XML', err);
+                }}
             }}
 
             document.getElementById('save-button').addEventListener('click', saveDiagram);
@@ -137,5 +142,4 @@ def display_bpmn_xml(bpmn_xml):
     </html>
     """
     
-    
-    components.html(html_template, height=1000, width=1500)
+    components.html(html_template, height=1000, width=1500)

train.py

@@ -44,7 +44,7 @@ def get_arrow_model(num_classes, num_keypoints=2):
     if device == torch.device('cuda'):
         model = keypointrcnn_resnet50_fpn(weights=KeypointRCNN_ResNet50_FPN_Weights.COCO_V1)
     else:
-        model = keypointrcnn_resnet50_fpn(weights=False)
+        model = keypointrcnn_resnet50_fpn(weights=None)
 
     # Get the number of input features for the classifier in the box predictor.
     in_features = model.roi_heads.box_predictor.cls_score.in_features