Tobacco Aerial Dataset
Description
A new aerial tobacco weed dataset with various field conditions. We have acquired a new tobacco-weed dataset using a Mavic Mini drone. Eight fields of tobacco crops are captured in Mardan, Khyber Pakhtunkhwa, Pakistan. At different growth stages, these eight fields are captured at a crop age of 15 to 40 days approximately. Images are captured at 1920 × 1080-pixel resolution; due to system memory limitations, we have cropped non-overlapping images of resolution 480 × 352 for processing. This image patch cropping is implemented using a code that reads images and creates non-overlapping tile images using two nested loops; the respective annotation images are also cropped simultaneously. Dataset is captured at an average altitude of 4 m with a ground sampling distance of 0.1 cm/ pixel. Images are labeled manually; background, crop, and weed have label values of 0, 1, and 2, respectively. Citation Request: if you use these datasets in your research or projects by any means, please cite following publications 1) Patch-wise weeds coarse segmentation mask from aerial imagery of sesame crop (Published in Computers and Electronics in Agriculture 2022, HEC Recognized W category, Impact factor 6.757, Q1) 2) Towards automated weed detection through two-stage semantic segmentation of tobacco and weed pixels in aerial Imagery (Published in Smart Agricultural Technology (A companion journal of Computers and Electronics in Agriculture)) 3) A Patch-Image Based Classification Approach for Detection of Weeds in Sugar Beet Crop (Published in IEEE Access, Impact factor 3.1, Q1) Acknowledgement Request This work is funded by the Higher Education Commission of Pakistan and the National center for Robotics and Automation (DF-1009–31). We thank Pakistan Tobacco Company for helping us find farms for data collection. Steps to Access Mendeley datasets 1. Click on the link 2. The link with ask you to sign in or register with institutional email. 3. Use your institutional/organization email to register and then sign in. 4. Once sign in, dataset will be visible in compressed folders 5. Download and unzip/umcompress folder 6. Use dataset in your research as you see fit (folders contains original images, and their labeled groundtruths, along with binary vegetation masks. In groundtruths background have label value of 0, crop have label 1 and weeds have label of 2. maskref subfolders shows labelled data for visualization)
Files
Steps to reproduce
The dataset contains a master folder there are 8 subfolders which contains data from eight different fields these 8 folders contains original images, and their labeled groundtruths, along with binary vegetation masks. in groundtruths background have label value of 0, crop have label 1 and weeds have label of 2. maskref shows original labelled data for visualization.