This depository contains the following files: 
 
“Final_Results.xlsx”: A spreadsheet containing all the data obtained by running the different photo-matching algorithms on the datasets of Kenyan and 	Zimbabwean African wild dogs. 

“mega_detector_results.xls”: A spreadsheet containing the results of using the MegaDetector to automatically crop African wild dogs from images. 

“Analysis_Photo_Matching_Software.R” is an R-script which contains the code used to analyse the results of the excel file “Final_Results.xlsx”. It shows how we compared the performance of different software packages with Mixed Effects Logistic Regressions, and how I compared Hotspotter’s performance on the Kenyan and Zimbabwean dataset.

“Analysis_Aspect_Ratios.R” is an R script which reads in the aspect ratio of images, used to calculate the range of aspect ratios of crops suitable for identification. 

“background_removal_code.rtf” contains he code used to remove the background from images of African wild dogs in an Anaconda Prompt. 

“mega_detector_batch_cropping” contains the code used to automatically crop animals from animals, using Spyder. 

“standing_sitting_model_script.pdf” is a jupyter notebook containing the code used to made the Convolutional Neural Net that separates standing and sitting individuals.

“Standing_sitting_model.zip” is a compressed folder containing the classifier produced by the script “standing_sitting_model_script.pdf”. 

“flank_model_script.pdf” is a jupyter notebook containing the code used to made the Convolutional Neural Net that separates left and right flanks.

“left_right_flank_model” is a compressed folder containing the classifier produced by the script “flank_model_script.pdf”.