How To Submit - Konnsy/REAML2022-hackathon GitHub Wiki
For all submissions:
- Submit the code that can be used directly, i.e. test code. We will not train your models but execute it in the evaluation mode!
- Submit all needed files. Do not forget to include the trained model weights (if you trained anything).
- A submission must be packed into in a .zip file (no loose files).
- Give the files that you want to submit unique names (name of your team or team members and time of submission).
- You may submit multiple times, but make sure to specify the new submission time.
- We will take the score of your latest submission.
Pay attention to the time limits
- Finish the first task before 17:00
- Finish the second task before 20:00
- Finish the third task before 22:00
Submission for Task 1:
- Your system has to predict a confidence score (<0.5: only background, >0.5: particle) for each given block of raw images.
- Submit your final version of Task 1 before working on Task 2. This makes it easier to point out problems with the submission at an early stage.
Submission for Task 2:
- Your system has to predict a number of particles that it detects in a whole dataset given by its folder path.
Submission for Task 3:
- Same as in Task 2 with the restriction to be executable on one of the Odroid devices
- If you want to be safe: show us the used device and we copy its SD card to have an exact copy of the system
Submission formats
Submission format of "test_results.txt" for task 1
Please submit a file where each line contains an entry <final result (bool)>, <positive cases (int)>, <negative cases(int)>,
An example would be
"False, 23, 123, test_set_B
True, 45, 2, test_set_F"
for two test sets "test_set_B" and "test_set_F" where the "final result"/first column is True if and only if there are more positive than negative cases.
Submission format of "test_results.txt" for task 2
Please submit a file where each line contains an entry <number of particles (int)>, , <time to compute in seconds (float)>
An example would be
"123, test_set_C, 78.4
0, test_set_E, 87.5"
for two test sets " test_set_C" and " test_set_E"
Try to keep your models explainable so that a plausibility check is possible for your submission.