This code is a refactored version of https://github.com/Cartucho/mAP

put your ground-truth and detections into src/measure/input

• Create a separate ground-truth text file for each image.
• Use matching names for the files (e.g. image: "image_1.jpg", ground-truth: "image_1.txt").
• In these files, each line should be in the following format:

  <class_name> <left> <top> <right> <bottom>
  

• E.g. "image_1.txt":

  tvmonitor 2 10 173 238
  book 439 157 556 241
  book 437 246 518 351 difficult
  pottedplant 272 190 316 259
  

• Create a separate detection-results text file for each image.
• Use matching names for the files (e.g. image: "image_1.jpg", detection-results: "image_1.txt").
• In these files, each line should be in the following format:

  <class_name> <confidence> <left> <top> <right> <bottom>
  

• E.g. "image_1.txt":

  tvmonitor 0.471781 0 13 174 244
  cup 0.414941 274 226 301 265
  book 0.460851 429 219 528 247
  chair 0.292345 0 199 88 436
  book 0.269833 433 260 506 336
  
  

you can run code in src/measure/measurer.py and it will show you the metrics calculation dependencies.