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README.md

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+# 📸 Image Caption Generator
+
+![Python](https://img.shields.io/badge/Python-3.11.9-blue)
+![TensorFlow](https://img.shields.io/badge/TensorFlow-2.10-orange)
+![Gradio](https://img.shields.io/badge/Gradio-Deployed-green)
+
+A Generative AI project that automatically describes the content of an image using Deep Learning. It combines **Computer Vision (InceptionV3)** and **Natural Language Processing (LSTM)** to generate accurate, human-like captions.
+
+## 🚀 Live Demo
+The model is deployed and running live! You can test it with your own images here:
+**[👉 Click here to try the Live App on Hugging Face](https://huggingface.co/spaces/RupamG/Image_Captioning_System)**
+
+---
+
+## 🧠 Technical Architecture
+This project uses an **Encoder-Decoder** architecture:
+
+1.  **Image Encoder (InceptionV3):**
+    * We use a pre-trained InceptionV3 model (trained on ImageNet) to extract high-level visual features from images.
+    * The last classification layer is removed, leaving us with a feature vector of shape `(2048,)`.
+2.  **Sequence Decoder (LSTM):**
+    * The extracted image features are passed to an LSTM (Long Short-Term Memory) network.
+    * The LSTM learns to generate a sequence of words (caption) based on the image features and the previous words generated.
+
+**Model Pipeline:**
+`Input Image` ➡️ `InceptionV3` ➡️ `Feature Vector` ➡️ `LSTM` ➡️ `Predicted Caption`
+
+---
+
+## 📂 Dataset
+The model was trained on the **Flickr8k Dataset**, which consists of:
+* **8,000 images** (6,000 training, 1,000 val, 1,000 test).
+* **5 captions per image** (Total 40,000 captions).
+
+*> **Note:** Due to size constraints, the raw dataset is not included in this repository. You can download it from [Kaggle](https://www.kaggle.com/adityajn105/flickr8k) and place it in the `src/` folder.*
+
+---
+
+## 🛠️ Installation & Setup
+To run this project locally on your machine:
+
+1.  **Clone the repository:**
+    ```bash
+    git clone https://github.com/Marshal-GG/Advanced-Image-Captioning-System.git
+    cd Advanced-Image-Captioning-System
+    ```
+
+2.  **Install dependencies:**
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+3.  **Download the Data:**
+    * Download Flickr8k images and `Flickr8k.token.txt`.
+    * Place them in the `src/` folder (or update paths in the notebook).
+
+4.  **Run the Training Notebook:**
+    * Open `main.ipynb` to see the data preprocessing, model training, and evaluation steps.
+
+5.  **Run the App:**
+    ```bash
+    python app.py
+    ```
+
 ---
-title: Image Captioning System
-emoji: 😻
-colorFrom: blue
-colorTo: indigo
-sdk: gradio
-sdk_version: 6.2.0
-app_file: app.py
-pinned: false
-short_description: Built a Deep Learning model to generate descriptive captions
+
+## 📊 Results
+* **Metric:** The model effectiveness is evaluated using qualitative analysis (visual inspection).
+* **Sample Output:**
+    * *Input:* Image of a 2 dogs running on grass.
+    * ![App Screenshot](demo_screenshot.png)
+    * *Output:* "Two dogs are playing together in the grass"
+
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## 🤝 Connect
+If you have any questions about this project or want to discuss Generative AI, feel free to connect!
+* **LinkedIn:** [https://www.linkedin.com/in/rupam-g/]
+* **Email:** [marshalgcom@gmail.com]
+