occlusion-project
- pbs_script/: Scripts for running code on cluster with PBS.
- slurm_script/: Scripts for running code on cluster with slurm.
- data/: Data folder, including flickr, imagenet and PASCAL 3D+. Included in .gitignore.
- result/: Result of the experiments. Included in .gitignore.
- src/: Source code for current project. (A.ipynb → B.py: using A to generate B, and running B on cluster with PBS / slurm scripts.)
- Settings
- settings.py
- constant.py
- Prepare datasets
- dataset.ipynb → dataset.py: Generate training dataset and test dataset. Basically first 3 cells are used.
- Finetune
- finetune.ipynb → finetune.py: Create network files, finetune networks and visualize middle results.
- Test
- test_lmdb.ipynb → test.py: Generate test_{}_{}.prototxt for testing, and test model by reading images from lmdb.
- test.ipynb → test.py: Test model by reading images directly from the disk. [Deprecated]
- data_utility.ipynb: Some utilities to show and test selected images in datasets.
- Analyse
- img2vec.ipynb → img2vec.py: Extract feature vectors of images.
- visualize_finetune: Plot training loss, training accuracy and validation accuracy during finetuning.
- visualize_accuracy: Plot accuracy curves according to different occlusion levels.
- visualize_img2vec: Plot feature space, and accuracy improvement for each class.
- visualize_aperture: Plot results of aperture occlusion. [Deprecated]
- vec2accuracy_divide: Test results with divided test datasets to get variation. [Deprecated]
- heat_map.ipynb: Plot confidence heat maps of given images.
- Miscellaneous
- estimate_time.ipynb
- Settings
- legacy/: Legacy code related to visual concept, not used by current project.
- legacy/src_visual_concept/: Use visual concept to generate occluded images.
- legacy/src_cl/: Chen Liu's code of Picasso project, modified by Hao Wang.
- legacy/src_orignal/: Chen Liu's original code of Picasso project.