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https://github.com/spidy20/landmark_detection

Landmarks Recogntion Web application using Streamlit.
https://github.com/spidy20/landmark_detection

landmark-detection landmark-recognition python streamlit

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Landmarks Recogntion Web application using Streamlit.

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# Landmark Recognition Web-App using Streamlit

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)
[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)

## [Watch Tutorial for this project](https://youtu.be/Jq9iVoir55g)

## Source
- Trained model [`landmarks_classifier_asia_V1/1`](https://tfhub.dev/google/on_device_vision/classifier/landmarks_classifier_asia_V1/1) is taken from the Tensorflow-Hub
- There are total `98961` classes supported, in which Asia's most of the famous Landmark is covered.
- This model was trained on [`Google Landmarks Dataset V2`](https://ai.googleblog.com/2019/05/announcing-google-landmarks-v2-improved.html).

## Features
- Simple repsonsive UI.
- It will give you the full address of Landmark
- It will provide you the `Latitude` & `Longitude` of predicted landmark.
- It will plot the predicted landmark on the Map.

## Usage

- Clone my repository.
- Open CMD in working directory.
- Run following command.

```
pip install -r requirements.txt
```
- `LM_Detection.py` is the main Python file of Streamlit Web-Application.
- To run app, write following command in CMD. or use any IDE.

```
streamlit run LM_Detection.py
```

- For more explanation of this project see the tutorial on Machine Learning Hub YouTube channel.

## Screenshots


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