https://github.com/yashksaini-coder/landmark-detection
Landmark Detection detects popular natural and human-made structures within an image.
https://github.com/yashksaini-coder/landmark-detection
collaborate contribution flask hacktoberfest
Last synced: 2 months ago
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Landmark Detection detects popular natural and human-made structures within an image.
- Host: GitHub
- URL: https://github.com/yashksaini-coder/landmark-detection
- Owner: yashksaini-coder
- License: apache-2.0
- Created: 2024-09-23T15:52:47.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-11-22T16:34:33.000Z (7 months ago)
- Last Synced: 2025-03-25T10:51:17.976Z (3 months ago)
- Topics: collaborate, contribution, flask, hacktoberfest
- Language: Jupyter Notebook
- Homepage:
- Size: 411 KB
- Stars: 17
- Watchers: 1
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# Landmark-Detection
Landmark Detection detects popular natural and human-made structures within an image.
## Project Description
The Landmark Detection application is designed to identify and classify popular natural and human-made structures within an image. It uses a TensorFlow model to perform the classification and provides a user-friendly interface for uploading images and viewing the classification results.
## Installation Instructions
To set up the environment and install the necessary dependencies, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/yashksaini-coder/Landmark-Detection.git
cd Landmark-Detection
```
2. Create a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. Install the dependencies:
```bash
pip install -r requirements.txt
```
## Usage Instructions
To use the Landmark Detection application, follow these steps:
1. Run the Streamlit app:
```bash
streamlit run app.py
```
2. Open your web browser and go to `http://localhost:8501`.
3. Upload an image by clicking on the "Choose an image..." button.
4. Once the image is uploaded, click on the "Classify Image" button to classify the image and view the results.
## Model Information
The Landmark Detection application uses a TensorFlow model hosted on TensorFlow Hub. The model URL is:
`https://tfhub.dev/google/on_device_vision/classifier/landmarks_classifier_asia_V1/1`
The label map used for classification is available at:
`https://www.gstatic.com/aihub/tfhub/labelmaps/landmarks_classifier_asia_V1_label_map.csv`
## Contributing
We welcome contributions to the Landmark Detection project! Please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for guidelines on how to contribute.
## License
This project is licensed under the terms of the Apache License 2.0. See the [LICENSE](LICENSE) file for details.
## Contact
For further assistance or inquiries, please contact us at [[email protected]] or visit our [GitHub repository](https://github.com/yashksaini-coder/Landmark-Detection).
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