Bicycle Crowd evaluation Project. This is for the evaluation of the new crowd in the automotive dataset given at (https://www.a2d2.audi).
For the tasks there are 4 main task + presentation.
Now to make it easy have created 4 folders for each of the task.
Now the task1 is the folder for Task-1. This task has 4 sub parts.
-
Task1a:
- list the annotators for the bicycle dataset. Just run the file with command
python Task1a.py
to see the output.
- list the annotators for the bicycle dataset. Just run the file with command
-
Task1b:
- This is to get the annotations durations that is min, max duration times. Just run the file with command
python Task1b.py
to see the output.
- This is to get the annotations durations that is min, max duration times. Just run the file with command
-
Task1c:
- This is to get the difference between the annotations result. Just run the file with command
python Task1c.py
to see the output.
- This is to get the difference between the annotations result. Just run the file with command
-
Task1d:
- This is to give the annotators that disaggree the most. Just run the file with command
python Task1d.py
to see the output
- This is to give the annotators that disaggree the most. Just run the file with command
Now the task2 is the folder for Task-2.
- Task2:
- This task is to analyze the annotations with label corrupt and can't solve. Just run the file with command
python task2.py
to see the output
- This task is to analyze the annotations with label corrupt and can't solve. Just run the file with command
Now the task3 is the folder for Task-3.
- Task3:
- This task is to analyze whether the reference set is balanced or not. Just run the file with command
python task3.py
to see the output.
- This task is to analyze whether the reference set is balanced or not. Just run the file with command
Now the task4 is the folder for Task-4.
- Task4:
- This task is to analyze good and bad annotators for the given dataset. All plots are given. Just run the file with command
python task4.py
to see the output.
- This task is to analyze good and bad annotators for the given dataset. All plots are given. Just run the file with command
Now task 5 is presentation. This is there in the presentation folder. This gives the summary of the findings.