Inference + Visualization

anomalib/data/inference.py

@@ -63,5 +63,6 @@ def __getitem__(self, index: int) -> Any:
         image_filename = self.image_filenames[index]
         image = read_image(path=image_filename)
         pre_processed = self.pre_process(image=image)
+        pre_processed["image_path"] = image_filename
 
         return pre_processed

anomalib/deploy/inferencers/__init__.py

@@ -18,4 +18,4 @@
 from .openvino import OpenVINOInferencer
 from .torch import TorchInferencer
 
-__all__ = ["Inferencer", "TorchInferencer", "OpenVINOInferencer"]
+__all__ = ["Inferencer", "OpenVINOInferencer", "TorchInferencer"]

anomalib/models/cflow/config.yaml

@@ -46,12 +46,18 @@ metrics:
     pixel_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 0
   path: ./results
 
 logging:
-  log_images_to: ["local"] # options: [wandb, tensorboard, local]. Make sure you also set logger with using wandb or tensorboard.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/components/base/anomaly_module.py

@@ -108,7 +108,7 @@ def test_step(self, batch, _):  # pylint: disable=arguments-differ
           Dictionary containing images, features, true labels and masks.
           These are required in `validation_epoch_end` for feature concatenation.
         """
-        return self.validation_step(batch, _)
+        return self.predict_step(batch, _)
 
     def validation_step_end(self, val_step_outputs):  # pylint: disable=arguments-differ
         """Called at the end of each validation step."""

anomalib/models/dfkde/config.yaml

@@ -32,12 +32,18 @@ metrics:
     image_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 42
   path: ./results
 
 logging:
-  log_images_to: [] # Not available for classification-based models.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/dfm/config.yaml

@@ -34,12 +34,18 @@ metrics:
     image_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 42
   path: ./results
 
 logging:
-  log_images_to: [] # Not available for classification-based models.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/draem/config.yaml

@@ -42,12 +42,18 @@ metrics:
     pixel_default: 3
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 42
   path: ./results
 
 logging:
-  log_images_to: ["local"] # options: [wandb, tensorboard, local]. Make sure you also set logger with using wandb or tensorboard.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/fastflow/config.yaml

@@ -46,12 +46,18 @@ metrics:
     pixel_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 42
   path: ./results
 
 logging:
-  log_images_to: ["local"] # options: [wandb, tensorboard, local]. Make sure you also set logger with using wandb or tensorboard.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/ganomaly/config.yaml

@@ -50,12 +50,18 @@ metrics:
     image_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 42
   path: ./results
 
 logging:
-  log_images_to: [] # Not available for classification-based models.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/padim/config.yaml

@@ -41,12 +41,18 @@ metrics:
     pixel_default: 3
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 42
   path: ./results
 
 logging:
-  log_images_to: ["local"] # options: [wandb, tensorboard, local]. Make sure you also set logger with using wandb or tensorboard.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/patchcore/config.yaml

@@ -43,12 +43,18 @@ metrics:
     pixel_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 0
   path: ./results
 
 logging:
-  log_images_to: ["local"] # options: [wandb, tensorboard, local]. Make sure you also set logger with using wandb or tensorboard.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/reverse_distillation/config.yaml

@@ -50,12 +50,18 @@ metrics:
     pixel_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 42
   path: ./results
 
 logging:
-  log_images_to: ["local"] # options: [wandb, tensorboard, local]. Make sure you also set logger with using wandb or tensorboard.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.
 

anomalib/models/stfpm/config.yaml

@@ -49,12 +49,18 @@ metrics:
     pixel_default: 0
     adaptive: true
 
+visualization:
+  show_images: False # show images on the screen
+  save_images: True # save images to the file system
+  log_images: True # log images to the available loggers (if any)
+  image_save_path: null # path to which images will be saved
+  mode: full # options: ["full", "simple"]
+
 project:
   seed: 0
   path: ./results
 
 logging:
-  log_images_to: ["local"] # options: [wandb, tensorboard, local]. Make sure you also set logger with using wandb or tensorboard.
   logger: [] # options: [tensorboard, wandb, csv] or combinations.
   log_graph: false # Logs the model graph to respective logger.