Changes made by Lihang

.gitignore

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+.venv/
+.vscode/
+__pycache__/
+dataset/
+gradient_maps/
+models/
+transform/
+weights/
+logs/
+work/

README.md

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+# DifferNet
+This project is used for experiment to train and test models on various datasets. The core function has been packaged as "[differnet-zerobox](https://github.com/zerobox-ai/pydiffernet)". Pleaser refer to the [readme](https://github.com/zerobox-ai/pydiffernet/blob/master/README.md) for how to use the package.
+
+If you need more information about DifferNet, please reference to the official repository. 
+
+**Differnet Officical repository**
+The [official repository](https://github.com/marco-rudolph/differnet) to the WACV 2021 paper "[Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows](
+https://arxiv.org/abs/2008.12577)" by Marco Rudolph, Bastian Wandt and Bodo Rosenhahn.
+
+## Getting Started
+
+The project has been upgraded to python 3.9. Please setup python 3.9 virtual environment then do the following.
+
+### Install torch and torch vision
+In order to have proper torch and torch vision to use either GPU or CPU please follow [pytorch.org](https://pytorch.org/get-started/locally/) to install torch and torch vision
+
+## Install rest packages with:
+
+```
+$ pip install -r requirements.txt
+```
+
+## Configure and Run
+
+All configuration has default values from package differnet(from package differnet-zerobox).
+The project can have dict based configuration to overwrite any default value.
+
+
+Common settings
+```
+#conf/settings.conf
+"differnet_work_dir": "./work", #work folder
+"device": "cuda",  # cuda or cpu
+"device_id": 0,  # the device you want to use. depends on how many GPU or CPU you have. 
+"verbose": True, # Set to true, when you do experiments.
+"meta_epochs": 10,  # traing loop
+"sub_epochs": 8,  # sub-loop of traing
+"test_anormaly_target": 10, # threshold when run testing model to identify if a given image is good or bad
+
+```
+
+Traing
+
+```
+python training.py
+```
+
+Run test cases
+```
+python  -m pytest -s
+```
+
+## Prepare new dataset
+The data structure under work folder looks like this. The model folder will save trained model.
+For experiment purpose, you would like to give test and validate folder with proper labled data. While, for zerobox 
+it only requires train folder and data. The minimum images is 16 based on the differnet paper.
+
+```
+pink1/
+├── model
+├── test
+│   ├── defect
+│   └── good
+├─── validate
+│    ├── defect
+│    └── good
+└── train
+    └── good
+        ├── 01.jpg
+        ├── 02.jpg
+        ├── 03.jpg
+        ├── 04.jpg
+        ├── 05.jpg
+        ├── 06.jpg
+        ├── 07.jpg
+        ├── 08.jpg
+        ├── 09.jpg
+        ├── 10.jpg
+        ├── 11.jpg
+        ├── 12.jpg
+        ├── 13.jpg
+        ├── 14.jpg
+        ├── 15.jpg
+        └── 16.jpg
+```
+

conf/settings.py

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+DIFFERNET_CONF = {
+    # common settings
+    "differnet_work_dir": "./work",
+    "device": "cuda",  # cuda or cpu
+    "device_id": 5,
+    "verbose": True,
+    "meta_epochs": 5,
+    "sub_epochs": 8,
+    "test_anormaly_target": 10,
+    # other settings
+    # "img_size": [448, 448],
+    # "img_dims": [3, 448, 448],
+    # "add_img_noise": 0.01,
+    # # transformation settings
+    # "transf_rotations": False,
+    # "transf_brightness": 0.5,
+    # "transf_contrast": 0.5,
+    # "transf_saturation": 0.5,
+    # "norm_mean": [0.485, 0.456, 0.406],
+    # "norm_std": [0.229, 0.224, 0.225],
+    # "rotation_degree": 0,
+    # "crop_top": 0.10,
+    # "crop_left": 0.10,
+    # "crop_bottom": 0.10,
+    # "crop_right": 0.10,
+    # network hyperparameters
+    # number of scales at which features are extracted, img_size is the highest - others are //2, //4,...
+    # "n_scales": 3,
+    # "clamp_alpha": 3,  # see paper equation 2 for explanation
+    # "n_coupling_blocks": 8,
+    # # fc_internal : 2048 # number of neurons in hidden layers of s-t-networks
+    # "fc_internal": 1536,  # number of neurons in hidden layers of s-t-networks
+    # "dropout": 0.0,  # dropout in s-t-networks
+    # "lr_init": 2e-4,
+    # "n_feat": 256 * 3,  # do not change except you change the feature extractor
+    # # dataloader parameters
+    # "n_transforms": 4,  # number of transformations per sample in training
+    # "n_transforms_test": 1,  # number of transformations per sample in testing
+    # # actual batch size is this value multiplied by n_transforms(_test)
+    # "batch_size": 4,
+    # "batch_size_test": 1,
+    # total epochs : meta_epochs * sub_epochs
+    # evaluation after <sub_epochs> epochs
+    # output settings
+    # "grad_map_viz": True,
+    # "hide_tqdm_bar": True,
+    # "save_model": True,
+    # "save_transformed_image": True,
+    # "visualization": False,
+    # "frame_name_is_given": False,
+    # "target_tpr": 0.85,
+}
+
+
+LOGGING = {
+    "version": 1,
+    "disable_existing_loggers": False,
+    "formatters": {
+        "verbose": {
+            "format": "%(levelname)s %(asctime)s %(module)s "
+            "%(process)d %(thread)d %(message)s"
+        }
+    },
+    "handlers": {
+        "console": {
+            # "level": "DEBUG",
+            "class": "logging.StreamHandler",
+            "formatter": "verbose",
+        },
+        # "file": {
+        #     # 'level': 'DEBUG',
+        #     "class": "logging.handlers.RotatingFileHandler",
+        #     "filename": "logs/app.log",
+        #     "formatter": "verbose",
+        #     "maxBytes": 1024 * 1024 * 1,  # 10MB
+        #     "backupCount": 5,
+        #     "formatter": "verbose",
+        # },
+    },
+    "loggers": {
+        "differnet": {
+            "handlers": ["console"],
+            "level": "DEBUG",
+            "propagate": False,
+        },
+    },
+    "root": {"level": "INFO", "handlers": ["console"]},
+}