The issue

I developed a simple NodeJS app for object detection using @tensorflow/tfjs-node. Everything works fine on my development PC (Windows 10 Pro), but trying to execute on my Raspberry Pi 2B (Raspbian 10), I got the following error:

Overriding the gradient for 'Max'
Overriding the gradient for 'OneHot'
Overriding the gradient for 'PadV2'
Overriding the gradient for 'SpaceToBatchND'
Overriding the gradient for 'SplitV'
2020-07-31 11:25:12.068892: I tensorflow/cc/saved_model/reader.cc:31] Reading SavedModel from: ./assets/saved_model
2020-07-31 11:25:12.643852: I tensorflow/cc/saved_model/reader.cc:54] Reading meta graph with tags { serve }
2020-07-31 11:25:13.206821: I tensorflow/cc/saved_model/loader.cc:311] SavedModel load for tags { serve }; Status: fail. Took 1137915 microseconds.
Error: Failed to load SavedModel: Op type not registered 'NonMaxSuppressionV5' in binary running on raspberrypi. Make sure the Op and Kernel are registered in the binary running in this process. Note that if you are loading a saved graph which used ops from tf.contrib, accessing (e.g.) `tf.contrib.resampler` should be done before importing the graph, as contrib ops are lazily registered when the module is first accessed.
    at NodeJSKernelBackend.loadSavedModelMetaGraph (/home/pi/storage/tensorflow-test-node/node_modules/@tensorflow/tfjs-node/dist/nodejs_kernel_backend.js:1588:29)
    at Object.<anonymous> (/home/pi/storage/tensorflow-test-node/node_modules/@tensorflow/tfjs-node/dist/saved_model.js:429:45)
    at step (/home/pi/storage/tensorflow-test-node/node_modules/@tensorflow/tfjs-node/dist/saved_model.js:48:23)
    at Object.next (/home/pi/storage/tensorflow-test-node/node_modules/@tensorflow/tfjs-node/dist/saved_model.js:29:53)
    at fulfilled (/home/pi/storage/tensorflow-test-node/node_modules/@tensorflow/tfjs-node/dist/saved_model.js:20:58)

I can reproduce it with the following lines:

const tf = require('@tensorflow/tfjs-node');

// Native SavedModel: ./assets/saved_model/saved_model.pb
const objectDetectionModel = await tf.node.loadSavedModel('./assets/saved_model'); // Error

// ...

I supose that the error is related with the SavedModel version, but I don't know how convert it to use in the Rapsberry Pi or why the NodeJS app needs different SavedModel if I execute in Windows or Raspbian.

Details

Enviroment

• Development:
  • OS: Windows 10 Pro
  • NodeJS: v12.16.2
  • NPM: 6.11.3
• Target (Raspberry PI):
  • OS: Raspbian 10
  • NodeJS: v12.18.3
  • NPM: 6.14.6

NodeJS app

@tensorflow/tfjs-node@2.0.1 is the only dependency declared in the package.json.

Training

The model was trained on Python following this guide (TensorFlow version used was 1.15.2).

SavedModel

Details of SavedModel (command saved_model_cli show --dir saved_model --tag_set serve --signature_def serving_default executed):

The given SavedModel SignatureDef contains the following input(s):
  inputs['inputs'] tensor_info:
      dtype: DT_INT32
      shape: (-1, -1, -1, 3)
      name: image_tensor:0
The given SavedModel SignatureDef contains the following output(s):
  outputs['detection_boxes'] tensor_info:
      dtype: DT_FLOAT
      shape: (-1, 300, 4)
      name: detection_boxes:0
  outputs['detection_classes'] tensor_info:
      dtype: DT_FLOAT
      shape: (-1, 300)
      name: detection_classes:0
  outputs['detection_multiclass_scores'] tensor_info:
      dtype: DT_FLOAT
      shape: (-1, 300, 37)
      name: detection_multiclass_scores:0
  outputs['detection_scores'] tensor_info:
      dtype: DT_FLOAT
      shape: (-1, 300)
      name: detection_scores:0
  outputs['num_detections'] tensor_info:
      dtype: DT_FLOAT
      shape: (-1)
      name: num_detections:0
  outputs['raw_detection_boxes'] tensor_info:
      dtype: DT_FLOAT
      shape: (-1, 300, 4)
      name: raw_detection_boxes:0
  outputs['raw_detection_scores'] tensor_info:
      dtype: DT_FLOAT
      shape: (-1, 300, 37)
      name: raw_detection_scores:0
Method name is: tensorflow/serving/predict