message: Samples DNN: tf_text_graph_sd.py loads box coder variance and box NMS params from config file
diff: @@ -283,6 +283,9 @@ def createSSDGraph(modelPath, configPath, outputPath):
  # Add layers that generate anchors (bounding boxes proposals).
  priorBoxes = []
  + boxCoder = config['box_coder'][0]
  + fasterRcnnBoxCoder = boxCoder['faster_rcnn_box_coder'][0]
  + boxCoderVariance = [1.0/float(fasterRcnnBoxCoder['x_scale'][0]), 1.0/float(fasterRcnnBoxCoder['y_scale'][0]), 1.0/float(fasterRcnnBoxCoder['width_scale'][0]), 1.0/float(fasterRcnnBoxCoder['height_scale'][0])]
  for i in range(num_layers):
  priorBox = NodeDef()
  priorBox.name = 'PriorBox_%d' % i
  @@ -303,7 +306,7 @@ def createSSDGraph(modelPath, configPath, outputPath):
  priorBox.addAttr('width', widths)
  priorBox.addAttr('height', heights)
  - priorBox.addAttr('variance', [0.1, 0.1, 0.2, 0.2])
  + priorBox.addAttr('variance', boxCoderVariance)
  graph_def.node.extend([priorBox])
  priorBoxes.append(priorBox.name)
  @@ -336,11 +339,31 @@ def createSSDGraph(modelPath, configPath, outputPath):
  detectionOut.addAttr('num_classes', num_classes + 1)
  detectionOut.addAttr('share_location', True)
  detectionOut.addAttr('background_label_id', 0)
  +
  + postProcessing = config['post_processing'][0]
  + batchNMS = postProcessing['batch_non_max_suppression'][0]
  +
  + if 'iou_threshold' in batchNMS:
  + detectionOut.addAttr('nms_threshold', float(batchNMS['iou_threshold'][0]))
  + else:
  detectionOut.addAttr('nms_threshold', 0.6)
  +
  + if 'score_threshold' in batchNMS:
  + detectionOut.addAttr('confidence_threshold', float(batchNMS['score_threshold'][0]))
  + else:
  + detectionOut.addAttr('confidence_threshold', 0.01)
  +
  + if 'max_detections_per_class' in batchNMS:
  + detectionOut.addAttr('top_k', int(batchNMS['max_detections_per_class'][0]))
  + else:
  detectionOut.addAttr('top_k', 100)
  - detectionOut.addAttr('code_type', "CENTER_SIZE")
  +
  + if 'max_total_detections' in batchNMS:
  + detectionOut.addAttr('keep_top_k', int(batchNMS['max_total_detections'][0]))
  + else:
  detectionOut.addAttr('keep_top_k', 100)
  - detectionOut.addAttr('confidence_threshold', 0.01)
  +
  + detectionOut.addAttr('code_type', "CENTER_SIZE")
  graph_def.node.extend([detectionOut])
  