https://github.com/joseruiz01/nontextualdataextraction
Application of CBIR in a real-world domain
https://github.com/joseruiz01/nontextualdataextraction
cbir distance-measures features-extraction image-matching
Last synced: 2 months ago
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Application of CBIR in a real-world domain
- Host: GitHub
- URL: https://github.com/joseruiz01/nontextualdataextraction
- Owner: JoseRuiz01
- Created: 2025-02-26T12:53:52.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-03-13T16:19:53.000Z (3 months ago)
- Last Synced: 2025-03-13T17:39:49.941Z (3 months ago)
- Topics: cbir, distance-measures, features-extraction, image-matching
- Language: Python
- Homepage:
- Size: 21.4 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: readme.md
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README
# Guide to Using the CBIR System
To use the CBIR system for finding similar car's images to your car photo, follow these simplified steps:
#### Step 1: Install Required Software
1. **Install Python**: Make sure Python is installed on your computer. You can download it from https://www.python.org/.
2. **Install Necessary Libraries**: Open your terminal or command prompt and run:
pip install opencv-python numpy matplotlib
#### Step 2: Prepare Your Image Dataset
1. **Organize Your Images**: Create a directory and place all your JPG images in this directory. You can use the Standford cars dataset : https://www.kaggle.com/datasets/jessicali9530/stanford-cars-dataset
#### Step 3: Generate ORB Descriptors
1. **Open Terminal or Command Prompt**: Navigate to the directory containing the `descriptorsGenerator.py` script.
2. **Run the Descriptors Generator**: Execute the following command to generate ORB descriptors:
python descriptorsGenerator.py --dataset path_to_image_dataset --output path_to_output_directory
- Replace `path_to_image_dataset` with the path to your image directory.
- Replace `path_to_output_directory` with the path where you want to save the descriptor files.
#### Step 4: Generate the Output Image with Matches
1. **Run the CBIR Script**: Use the `CBIR.py` script to generate an output image with matches. You will need to specify the query image and the dataset directory.
2. **Command to Run**:
python CBIR.py --query path_to_query_image --dataset path_to_image_dataset
- Replace `path_to_query_image` with the path to your query image.
- Replace `path_to_image_dataset` with the path to your image dataset directory.
By following these steps, you can generate an output image that shows the matches for your query image using the CBIR system.