London tree dataset

Summary

This is a dataset of 132 images (1024x1024) of 13944 trees at 33 locations and around the London area.

Functions included (london_trees.ipynb)

Download
Tree count
Convert JSONS to CSVs
Example image with annotations
Generate GT points map
Generate GT gaussian map
Normalisation (calculate dataset mean and stdev for RGB channels)
Train test split
Generate file summary
Generate lat-lon of each tree

Tree location data

Included is a csv file in the /data folder which contains the latitude and longitude coordinate of every tree.

Other files

Pytorch dataset configuration files as used in C^3
Gaussian kernel functions gaussian_functions.py
Train and test jsons for pytorch dataset files

How to get dataset

Images

To build the images, you will need:

A GCP account, and a Google Maps Services Static Map API Key (instructions on how to get these available
in the repo below)
GMapLoader python package
Use the 'Download images' section within the notebook to download the images
Approximate cost is £1 - £1.50 in Google Maps API fees

JSONS

Available here (Google Drive Link)

Ground truth point x,y coordinate .csv files

These are provided in the repo under /gt_points

Ground truth Map .h5 files

Use code 'Generate GT Map' provided in notebook

How to change labels

Images were labeled using labelMe. To alter the labels:

Create an empty folder
Move both the image and JSON for the image into this folder (filenames should be the same apart from the extension)
use python -m labelme to open labelMe
Use the 'Open Dir' function in label me to point to the directory with the images and JSONS in
Images should appear in the bottom right window, select the one you want to change, labels will show