# Furniture Classification and Recommendation Models

This repository contains three models for furniture classification and recommendation. Follow the instructions below to set up and use each model.

## Model 1: Furniture Type Classification

### Setup
1. **Organize Files**: Place the folder for Task 1 and the dataset in the same directory.
2. **Check Path**: Ensure the paths in the code are correct and adjust if necessary.

### Running the Model
1. **Open Jupyter Notebook**: Open the Jupyter Notebook for Task 1.
2. **Prepare Input Images**:
   - Create a folder named `Input_Furniture` in the same directory as the notebook.
   - Place all the images you want to classify in the `Input_Furniture` folder.
3. **Run Notebook**: Execute all the cells in the notebook.
4. **View Predictions**: The last cell of the notebook will predict the type of each image in the `Input_Furniture` folder.

## Model 2: Furniture Recommendation by Category

### Setup
1. **Google Colab**: Open Google Colab and upload the code for Model 2.
2. **Upload Dataset**: Upload the dataset to your Google Drive.

### Running the Model
1. **Mount Drive**: Mount your Google Drive in the Colab environment.
2. **View Dataset**: Use the folder icon in Colab to view the dataset and copy the path of the dataset you want to train the model with.
3. **Update Path**: Paste the copied path into the `data_dir` variable in the code to set the correct dataset path.
4. **Run Code**: Execute all the cells in the notebook.
5. **Upload Furniture Image**: In the last cell, click the upload button and choose the furniture image you want recommendations for.
6. **View Recommendations**: The model will display recommended furniture items based on the input image.

## Model 3: Furniture Recommendation by Category and Style

### Setup
1. **Google Colab**: Open Google Colab and upload the code for Model 3.
2. **Upload Dataset**: Upload the dataset to your Google Drive.

### Running the Model
1. **Mount Drive**: Mount your Google Drive in the Colab environment.
2. **View Dataset**: Use the folder icon in Colab to view the dataset and copy the path of the dataset you want to train the model with.
3. **Update Path**: Paste the copied path into the `data_dir` variable in the code to set the correct dataset path.
4. **Run Code**: Execute all the cells in the notebook.
5. **Upload Furniture Image**: In the last cell, click the upload button and choose the furniture image you want recommendations for.
6. **View Recommendations**: The model will display recommended furniture items based on the category and style of the input image.

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**Note**: Ensure that the paths in the code are correct and adjust them if needed.

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