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1     Functions

Text and Image Query (MMC-TIQ):

Receives Textual part of query.
Image part of query.
Produces Text in response to Text and Image provides as input.

2     Reference Model

Figure 1 depicts the Reference Model of the Text and Image Query (MMC-TIQ) AIM.

Figure 1 – The Text and Image Query (MMC-TIQ) AIM Reference Model

3    Input/Output Data

Table 1 specifies the Input and Output Data of the Text and Image Query (MMC-TIQ) AIM.

Table 1 – I/O Data of the Text and Image Query (MMC-TIQ) AIM

Input Description
Text Object Text asking question about the Image.
Visual Object Image about which a question is asked.
Output Description
Text Object Response produced by Text and Image Query.

4     SubAIMs

Text and Image Query (MMC-TIQ) can be implemented as a Composite AIM whose Reference Model is depicted in Figure 2.

Figure 2 – Text and Image Query (MMC-TIQ) Composite AIM Reference Model

The AIMs and there JSON Metadata are specified in Table 2

Table 2 – AIMs and JSON Metadata of Text and Image Query (MMC-TIQ) Composite AIM

Acronym   AIM Name JSON
MMC-TIQ Text-and-Image Query X
OSD-VOI Visual Object Identification X
MMC-NLU Natural Language Understanding X
MMC-QAM Question Analysis Module X
MMC-AQM Answer to Question Module X

5     JSON Metadata

https://schemas.mpai.community/MMC/V2.2/AIMs/TextAndImageQuery.json

6     Profiles

No Profiles.

7. Reference Software

7.1 Disclaimers

  1. The purpose of this MMC-TIQ Reference Software is to provide a working Implementation of MMC-TIQ, not to provide a ready-to-use product.
  2. MPAI disclaims the suitability of the Software for any other purposes and does not guarantee that it is secure.
  3. Use of this Reference Software may require acceptance of licences from the respective repositories. Users shall verify that they have the right to use any third-party software required by this Reference Software.

7.2    Guide to the TIQ code

Note that the Reference software implements the Basic  MMC-TIQ AIM.

Use of this AI Module is for developers who are familiar with Python and downloading models from HuggingFace,

A wrapper for the BLIP NN Module:

  1. Manages input files and parameters: Text Object, Visual Object
  2. Executes the BLIP Module to perform the question answering on each individual pair of Text and Visual Object.
  3. Outputs Text Object as answer.

The OSD-TIQ Reference Software is found at the NNW gitlab site. It contains:

  1. The python code implementing the AIM.
  2. Required libraries are: pytorch and transformers (HuggingFace), PIL

7.3 Acknowledgements

This version of the MMC-TIQ Reference Software has been developed by the MPAI Neural Network Watermarking Development Committee (NNW-DC).

8. Conformance Testing

9. Performance Assessment

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