WEEK 1 run process:
TASK 1:
- Run "launch_dataset_analysis.m" to generate "train_features.txt" and "px_coordinates.txt".
TASK 2:
- Run "launch_dataset_balancing.m" to generate "train_dataset.txt" and "val_dataset.txt".
TASK 3:
-
Run "segmentation_values_v2.m" to train the system and generate "segmentation_values.txt".
-
Run "CandidateGenerationPixel_Color.m" to generate the output masks and save them in "candidate_mask" path.
TASK 4:
- Run "launch_system_evaluation.m" to generate "eval_results.txt".
WEEK 2 run process:
TASK 1:
- Change the directory of 'testImage' to the location of your image and run "compare_operators.m" to watch the result and difference of the operators and filters.
TASK 2:
- Run "compare_operators.m" to watch the computational efficiency.
TASK 3:
- Run "segmentation_values_v4.m" to train the system and generate "segmentation_values.txt"
- Run "CandidateGenerationPixel_v2.m" to generate the output masks and save them in "candidate_mask" path.
TASK 4:
- Run "launch_back_projection_segmentation"
WEEK 3 run process:
TASK 1:
- Change the directory of 'testImage' to the location of your image.
- Change the variable "method=?" to "method=1".
- Run "CandidateGenerationPixel_V3.m" to generate the output masks and save them in "candidate_mask" path.
TASK 2:
- Change the directory of 'testImage' to the location of your image.
- Change the variable "method=?" to "method=2".
- Run "CandidateGenerationPixel_V3.m" to generate the output masks and save them in "candidate_mask" path.
TASK 3:
- Change the directory of 'testImage' to the location of your image.
- Change the variable "method=?" to "method=3".
- Run "CandidateGenerationPixel_V3.m" to generate the output masks and save them in "candidate_mask" path.
TASK 4:
- Run "launch_system_evaluation"