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2320sharon committed Jul 11, 2023
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![](https://user-images.githubusercontent.com/3596509/194389595-82ade668-daf0-4d24-b1a0-6ecf897f40fe.gif)

![separate_seg_controls_demo (1)](https://github.com/Doodleverse/seg2map/assets/61564689/d527fe8c-c3f2-4c62-b448-e581162e8475)


## Overview:
* Seg2Map facilitates application of Deep Learning-based image segmentation models and apply them to high-resolution (~1m or less spatial footprint) geospatial imagery, in order to make high-resolution label maps. Please see our [wiki](https://github.com/Doodleverse/seg2map/wiki) for more information.

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First, you need to request access to Google Earth Engine at https://signup.earthengine.google.com/. It takes about 1 day for Google to approve requests.

2. Authenticate with earthengine

Once your request has been approved, with the `seg2map` environment activated, run the following command on the Anaconda Prompt(or terminal) to link your environment to the GEE server:
``` bash
earthengine authenticate
```
A web browser will open, login with a gmail account and accept the terms and conditions. Then copy the authorization code into the Anaconda terminal. In the latest version of the earthengine-api, the authentication is done with gcloud. If an error is raised about gcloud missing, go to https://cloud.google.com/sdk/docs/install and install gcloud. After you have installed it, close the Anaconda Prompt and restart it, then activate the environment before running earthengine authenticate again.


3. Activate your conda environment
2. Activate your conda environment

```bash
conda activate seg2map
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- If you have successfully activated seg2map you should see that your terminal's command line prompt should now start with `(seg2map)`.
4. Install the seg2map from PyPi
3. Install the seg2map from PyPi
```bash
cd <location you downloaded seg2map>
ex: cd C:\1_repos\seg2map
```
5. Launch Jupyter Lab
4. Launch Jupyter Lab
- make you run this command in the seg2map directory so you can choose a notebook to use.
```bash
jupyter lab
```
## Features
### 1. Download Imagery from Google Earth Engine
Use google earth engine to download multiple years worth of imagery.
![download_imagery_demo](https://github.com/Doodleverse/seg2map/assets/61564689/a36421de-e6d2-4a3f-8c08-2e47be99e3e0)
### You can download multiple ROIs and years of data at lighting speeds 🌩️
![download_imagery_demo_multi_roi](https://github.com/Doodleverse/seg2map/assets/61564689/46219ca8-beed-46e0-a28f-0d5ceab6d474)
### 2. Apply Models to Imagery
![apply_model_demo](https://github.com/Doodleverse/seg2map/assets/61564689/75c55659-56f4-46f3-892d-6bebdcd6a653)
### 3. Load Segmented Imagery onto the Map
![load_segmentation_demo](https://github.com/Doodleverse/seg2map/assets/61564689/d6bbf3ba-a8a9-4e90-b47a-61c9c2fe4799)
## Generic workflow:
* Provide a web map for navigation to a location, and draw a bounding box
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