Update README.md

README.md

@@ -10,4 +10,55 @@ pinned: false
 license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+
+
+## Project File Structure
+
+```
+KB-VQA
+├── Files: Various files required for the demo such as samples images,..etc.
+├── models
+|   ├── deformable-detr-detic: DETIC Object Detection Model.
+|   ├── yolov5: YOLOv5 Object Detection Model.baseline)
+├── my_model
+|   ├── KBVQA.py : This module is the central component for implementing the designed model architecture for the Knowledge-Based Visual Question Answering (KB-VQA) project.
+|   ├── state_manager.py: Manages the user interface and session state to facilitate the Run Inference tool of the Streamlit demo app.
+│   ├── LLAMA2
+│   │   ├── LLAMA2_model.py: Used for loading LLaMA-2 model to be fine-tuned.
+│   ├── captioner
+│   │   ├── image_captioning.py: Provides functionality for generating captions for images.
+|   ├── detector
+│   │   ├── object_detection.py: Used to detect objects in images using object detection models.
+|   ├── fine_tuner
+│   │   ├── fine_tuner.py: Main Fine-Tuning Script for LLaMa-2 Chat models.
+│   │   ├── fine_tuning_data_handler.py: Handles and prepares the data for fine-tuning LLaMA-2 Chat models.
+│   │   ├── fine_tuning_data
+│   │   │   ├──fine_tuning_data_detic.csv: Fine-tuning data prepared by the prompt engineering module using DETIC detector. 
+│   │   │   ├──fine_tuning_data_yolov5.csv: Fine-tuning data prepared by the prompt engineering module using YOLOv5. detector. 
+|   ├── results
+│   │   ├── Demo_Images: Contains a pool of images used for the demo app. 
+│   │   ├── evaluation.py: Provides a comprehensive framework for evaluating the KB-VQA model.
+│   │   ├── demo.py: Provides a comprehensive framework for visualizing and demonstrating the results of the KB-VQA evaluation.
+│   │   ├── evaluation_results.xlsx : This file contains all the evaluation results based on the evaluation data.
+|   ├── tabs
+│   │   ├── home.py: Displays an introduction to the application with brief background along with the demo tools decription.
+│   │   ├── results.py: Manages the interactive Streamlit demo for visualizing model evaluation results and analysis.
+│   │   ├── run_inference.py: Responsible for the 'run inference' tool to test and use the fine-tuned models. 
+│   │   ├── model_arch.py: Displays the model architecture and accompanying abstract and design details
+│   │   ├── dataset_analysis.py: Provides tools for visualizing dataset analyses.
+|   ├── utilities 
+│   │   ├── ui_manager.py: Manages the user interface for the Streamlit application, handling the creation and navigation of various tabs.
+│   │   ├── gen_utilities.py: Provides a collection of utility functions and classes commonly used across various parts
+|   ├── config (All Configurations files are kept separated and stored as ".py" for easy reading - this will change after the project submission.)
+│   │   ├── kbvqa_config.py: Configuration parameters for the main KB-VQA model.
+│   │   ├── LLAMA2_config.py: Configuration parameters for LLaMA-2 model.
+│   │   ├── captioning_config.py : Configuration parameters for the captioning model (InstructBLIP).
+│   │   ├── dataset_config.py: Configuration parameters for the dataset processing.
+│   │   ├── evaluation_config.py: Configuration parameters for the KB-VQA model evaluation.
+│   │   ├── fine_tuning_config.py: Configurable parameters for the fine-tuning nodule.
+│   │   ├── inference_config.py: Configurable parameters for the Run Inference tool in the demo app.
+├── app.py: main entry point for streamlit - first page in the streamlit app)
+├── README.md (readme - this file)
+├── requirements.txt: Requirements file for the whole project that includes all the requirements for running the demo app on the HuggingFace space environment.
+```