Introduction

Computer Vision Project for USD class Computer Vision CSC 752 -UT1

The project details can be found at : https://github.com/robinnarsinghranabhat/Data-Efficient-Cropland-Segmentation-with-Pseudo-labels/blob/main/CV_Report.pdf

Downloading the Sentinel-2 Images

You need to login to Google Earth Engine Explorer, and use the JS files in : ./gee/

1. ee.js prepares the Export Files to be downloaded. We have two 27-channel image files on a provided region. Note : For a larger region, multiple files are downloaded into google drive which must be merged.

2. You can select the region of your choice, or use the coordinates used in ./gee/final_roi.js

Notebooks

Refer

• segmentation_v1.ipynb : train the baseline model
• segmentation_unet_dic.ipynb : train Unet model with dice loss
• segmentation_unet_bce.ipynb : train Unet model with Binary cross entropy loss
• inference.ipynb : Compares different trained models againts each other

Results

Generating False Labels

Performance of different variants

IOU Score comparisons