First download all the required data from the source in Phase1/Data/ directory.
Use this comand to open the directory for phase 1:
cd usankar_p1/Phase1
To run the panorama stitching for Train Set 1:
python Wrapper.py --ImagesFolder Data/Train/Set1
To run the panorama stitching for Train Set 2:
python Wrapper.py --ImagesFolder Data/Train/Set2
To run the panorama stitching for Train Set 3:
python Wrapper.py --ImagesFolder Data/Train/Set3
To run the panorama stitching for Test Set 1:
python Wrapper.py --ImagesFolder Data/Test/TestSet1
To run the panorama stitching for Test Set 2:
python Wrapper.py --ImagesFolder Data/Test/TestSet2
To run the panorama stitching for Test Set 3:
python Wrapper.py --ImagesFolder Data/Test/TestSet3
To run the panorama stitching for Test Set 4:
python Wrapper.py --ImagesFolder Data/Test/TestSet4
All the results will be stored in the folder shown below:
./Results/
First download all the required data from the source in Phase2/Data/ directory. Also, add a Checkpoints folder in Phase2/ directory.
Generate data using data_generation file, while having the Train and Val images in Data, inside Phase2/ directory.
To train the supervised model, run python3 Train_supervised.py
To train the unsupervised model, run python3 Train_unsupervised.py
To test the supervised model, uncomment lines 16 and 28 in Test.py and run python3 Test.py
To test the unsupervised model, uncomment lines 17 and 29 in Test.py and run python3 Test.py