SpeciesClassification/demo/README.MD

# Species Classification API Demo


## Overview

This demo uses the AI for Earth Species Classification API, which identifies over 5,000 plant and animal species. Visit the [API home page](https://www.microsoft.com/en-us/ai/ai-for-earth-apis) for more information or to request an API key.  The code used to train our model is available [here](https://github.com/Microsoft/SpeciesClassification).

You can view the demo at [aka.ms/speciesclassification](http://aka.ms/speciesclassification).


## Setup Instructions

The demo was tested on an Azure VM with the following configuration:
* Operating system: Linux (Ubuntu 18.04)
* Size: Standard B2ms (2 CPUs, 8 GB memory)


### Clone the repository and update the config file

- Clone the repository and copy the folder `demo` to your local machine or server
- Open the demo folder and update the following variables inside the `config.py` file (demo/config.py):
   - Replace`ROOT_PATH` with the path to the demo on your local machine or server (e.g `/home/.../demo`)
   - Update `BASE_URL` with the base URL for the API (e.g `https://[api-base-url]/`). Refer to the API documentation for          information 
   - Update`SUBSCRIPTION_KEY` with your product / API key. Visit the [API home page](https://www.microsoft.com/en-us/ai/ai-for-earth-apis) for more information on how to request an API key.


### Add the sample images

* Navigate to the folder `demo/static` and create a directory called `animals`

* Inside the newly created directory `animals` add the sample images that you would like to be displayed in the demo site.
   The directory structure for the sample images should be as follows `animal_name > image.ext` as shown in the example below.  A minimum of 8 valid images (jpg or png) is required for the demo to work.
   
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<img src="sample_images_dir_structure.jpg" alt="sample images directory structure"/></p>
  
* Run `demo/setup_sample_images.py`.  This script does the following:
  - Renames the files/directories to remove invalid characters.
  - Creates a csv index file called `demo/static/data/updated_animal_list.csv`, which contains the file paths and      corresponding animal names (extracted from the directory names).
  - Creates a thumbnails folder from the provided images. Thumbnails are resized images from the `animals` folder; these are the images
  that are displayed on the site.  While predicting, the site will look up the corresponding image in the `animals` folder.

### Run the demo

* Install the required packages by running the commands listed below:

```
pip install Flask==1.1.1
pip install requests==2.22.0
pip install urllib3==1.25.3
pip install pandas==0.24.2
pip install Pillow==6.1.0
```

- To start the demo, run `demo/app.py`
- In a browser, navigate to `http://<your VM address>:5000`