.. include:: /keyword.rst

========================
Visualizing AI Models
========================

This section describes how to use the visualization tool `Netron <https://github.com/lutzroeder/netron>`_ and the command-line tool ``ncc-tflite`` to inspect model structures and tensor information.

.. figure:: /_asset/ai-workflow-overview-step2.png
   :align: center
   :width: 80%

.. raw:: html

   <br><br>

Current Neuron Runtime versions on |IOT-YOCTO| do not support embedding or reading model metadata during the Deep Learning Archive (DLA) compilation. Consequently, developers must manually verify model details to ensure correct inference implementation.

Inspecting Models with Netron
-----------------------------

Netron provides a graphical interface to explore model architectures. The following examples use the ``yolov5s_int8`` model, which is available on the :doc:`Model Zoo-YOLOv5s </ai_hub/model_zoo/litert_analytical/YOLOv5s>`.

* **Full Graph View**
  
  Opening a model in Netron displays the entire network graph, including layer connections and flow.

  .. figure:: /_asset/sw_yocto_ml-guide_neuron-sdk_neuron-dev-flow_model-visualization_netron-vis.png
      :align: center
      :height: 800px

      Full view of ``YOLOv5s``

  .. note::
      Netron supports multiple frameworks, including **TensorFlow Lite (TFLite)**, **ONNX**, **Caffe**, and **Keras**.

* **Tensor Details**
  
  Selecting a specific node or tensor reveals its properties. For example, the input tensor ``Preprocessor/sub`` shows a 3-channel image of size 300 x 300 with quantization parameters (``zero_point: 128``, ``scale: 0.0078``).

  .. figure:: /_asset/sw_yocto_ml-guide_neuron-sdk_neuron-dev-flow_model-visualization_tensor-info.png
      :align: center
      :height: 600px

      Detailed information for a specific tensor in Netron

Using ncc-tflite for Visualization
----------------------------------

The Neuron Compiler (``ncc-tflite``) offers a command-line interface to extract model information directly.

* **List Input and Output Tensors**
  
  Developers can use the ``--show-io-info`` flag to view the input and output configurations of a TFLite model.

  .. code-block:: bash

      $ ncc-tflite --show-io-info yolov5s_int8.tflite
      
      # of input tensors: 1
      [0]: Preprocessor/sub
      ├ Type: kTfLiteUInt8
      ├ Shape: {1,300,300,3}
      ├ Scale: 0.00787402
      ├ ZeroPoint: 128
      └ Bytes: 270000
      
      # of output tensors: 2
      [0]: concat_1
      ├ Type: kTfLiteUInt8
      ├ Shape: {1,1917,21}
      ├ Scale: 0.141151
      ├ ZeroPoint: 159
      └ Bytes: 40257
      [1]: Squeeze
      ├ Type: kTfLiteUInt8
      ├ Shape: {1,1917,4}
      ├ Scale: 0.06461
      ├ ZeroPoint: 173
      └ Bytes: 7668

* **Show All Tensors and Nodes**
  
  The ``--show-tflite`` flag displays the full list of internal tensors and operation nodes.

  .. code-block:: bash

      $ ncc-tflite --show-tflite yolov5s_int8.tflite
      
      Tensors:
      [0]: BoxPredictor_0/BoxEncodingPredictor/BiasAdd
      ├ Type: kTfLiteUInt8
      ├ Shape: {1,19,19,12}
      ├ Scale: 0.06461
      ├ ZeroPoint: 173
      └ Bytes: 4332
      [1]: BoxPredictor_0/BoxEncodingPredictor/Conv2D_bias
      ├ Type: kTfLiteInt32
      ├ Shape: {12}
      ├ Scale: 7.66586e-05
      ├ ZeroPoint: 0
      └ Bytes: 48
      
      ...

.. note::
    For comprehensive documentation on ``ncc-tflite`` parameters, please refer to the **NeuroPilot Official Site** - `Neuron Compiler Section <https://neuropilot.mediatek.com/sphinx/neuropilot-8-basic-gai-full/html/l1_developer_tools/l2_model_development/l3_neuron_sdk/neuron_tools.html#neuron-compiler-ncc-tflite>`_.