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Update my_model/tabs/readme.txt
Browse files- my_model/tabs/readme.txt +4 -0
my_model/tabs/readme.txt
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Directory Overview: This directory contains all the atreamlit application pages:
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################################################################################################################################
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## 1. home.py
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the `home.py` displays an introduction to the application with brief background and description of the application tools.
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################################################################################################################################
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## 2. results.py
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The `results.py` module manages the interactive Streamlit demo for visualizing model evaluation results and analysis.
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It provides an interface for users to explore different aspects of model performance and evaluation samples.
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The `run_demo` function relies on the ResultDemonstrator class to generate plots and display results.
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################################################################################################################################
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## 3. run_inference.py
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The `run_inference.py` is responsible for the running inference to test and use the fine-tuned models.
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It manages the user interface and interactions for a Streamlit-based Knowledge-Based Visual Question
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Knowledge-Based Visual Question Answering (KB-VQA) model.
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################################################################################################################################
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## 5. dataset_analysis.py
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The dataset_analysis.py module provides tools for analyzing and visualizing distributions of question types
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within given question datasets for Knowledge-Based Visual Question Answering (KBVQA). It supports operations
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Directory Overview: This directory contains all the atreamlit application pages:
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################################################################################################################################
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## 1. home.py
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the `home.py` displays an introduction to the application with brief background and description of the application tools.
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################################################################################################################################
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+
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## 2. results.py
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The `results.py` module manages the interactive Streamlit demo for visualizing model evaluation results and analysis.
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It provides an interface for users to explore different aspects of model performance and evaluation samples.
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The `run_demo` function relies on the ResultDemonstrator class to generate plots and display results.
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################################################################################################################################
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## 3. run_inference.py
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The `run_inference.py` is responsible for the running inference to test and use the fine-tuned models.
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It manages the user interface and interactions for a Streamlit-based Knowledge-Based Visual Question
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Knowledge-Based Visual Question Answering (KB-VQA) model.
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################################################################################################################################
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## 5. dataset_analysis.py
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The dataset_analysis.py module provides tools for analyzing and visualizing distributions of question types
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within given question datasets for Knowledge-Based Visual Question Answering (KBVQA). It supports operations
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