refactor: 🛠 remove redundant logging imports and centralize logger configuration (#1214)

Author: onuralpszr

.github/workflows/mmdet.yml

@@ -106,7 +106,7 @@ jobs:
       - name: Run MMDet tests
         run: |
           source .venv/bin/activate
-          pytest tests/test_mmdetectionmodel.py -n auto
+          pytest tests/test_mmdetection_model.py -n auto
           # Run MMDet-related tests from test_predict.py
           pytest tests/test_predict.py::test_get_prediction_mmdet -n auto
           pytest tests/test_predict.py::test_get_sliced_prediction_mmdet -n auto

sahi/annotation.py

@@ -2,7 +2,6 @@
 # Code written by Fatih C Akyon, 2020.
 
 import copy
-import logging
 from dataclasses import dataclass
 from typing import Dict, List, Optional, Tuple, Union
 
@@ -16,8 +15,6 @@
 )
 from sahi.utils.shapely import ShapelyAnnotation
 
-logger = logging.getLogger(__name__)
-
 
 @dataclass(frozen=True)
 class BoundingBox:

sahi/logger.py

@@ -0,0 +1,37 @@
+import logging
+import os
+
+
+class SahiLoggerFormatter(logging.Formatter):
+    grey = "\x1b[38;20m"
+    yellow = "\x1b[33;20m"
+    red = "\x1b[31;20m"
+    bold_red = "\x1b[31;1m"
+    reset = "\x1b[0m"
+    format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s (%(filename)s:%(lineno)d)"
+
+    FORMATS = {
+        logging.DEBUG: grey + format + reset,
+        logging.INFO: grey + format + reset,
+        logging.WARNING: yellow + format + reset,
+        logging.ERROR: red + format + reset,
+        logging.CRITICAL: bold_red + format + reset,
+    }
+
+    def format(self, record):
+        log_fmt = self.FORMATS.get(record.levelno)
+        formatter = logging.Formatter(log_fmt)
+        return formatter.format(record)
+
+
+logger = logging.getLogger("sahi")
+if os.environ.get("SAHI_DEBUG"):
+    logger.setLevel(logging.DEBUG)
+    console_handler = logging.StreamHandler()
+    console_handler.setLevel(logging.DEBUG)
+else:
+    logger.setLevel(logging.INFO)
+    console_handler = logging.StreamHandler()
+    console_handler.setLevel(logging.INFO)
+console_handler.setFormatter(SahiLoggerFormatter())
+logger.addHandler(console_handler)

sahi/models/base.py

@@ -1,16 +1,14 @@
 # OBSS SAHI Tool
 # Code written by Fatih C Akyon, 2020.
 
-import logging
 from typing import Any, Dict, List, Optional
 
 import numpy as np
 
+from sahi.logger import logger
 from sahi.prediction import ObjectPrediction
 from sahi.utils.torch import empty_cuda_cache, has_torch, select_device
 
-logger = logging.getLogger(__name__)
-
 
 class DetectionModel:
     def __init__(

sahi/models/detectron2.py

@@ -1,18 +1,16 @@
 # OBSS SAHI Tool
 # Code written by Fatih C Akyon, 2020.
 
-import logging
 from typing import List, Optional
 
 import numpy as np
 
+from sahi.logger import logger
 from sahi.models.base import DetectionModel
 from sahi.prediction import ObjectPrediction
 from sahi.utils.cv import get_bbox_from_bool_mask, get_coco_segmentation_from_bool_mask
 from sahi.utils.import_utils import check_requirements
 
-logger = logging.getLogger(__name__)
-
 
 class Detectron2DetectionModel(DetectionModel):
     def check_dependencies(self):

sahi/models/huggingface.py

@@ -1,7 +1,6 @@
 # OBSS SAHI Tool
 # Code written by Fatih C Akyon and Devrim Cavusoglu, 2022.
 
-import logging
 import os
 from typing import Any, Dict, List, Optional, Tuple, Union
 
@@ -13,8 +12,6 @@
 from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list
 from sahi.utils.import_utils import check_requirements, ensure_package_minimum_version
 
-logger = logging.getLogger(__name__)
-
 
 class HuggingfaceDetectionModel(DetectionModel):
     def __init__(

sahi/models/mmdet.py

@@ -1,20 +1,17 @@
 # OBSS SAHI Tool
 # Code written by Fatih C Akyon, 2020.
 
-import logging
 from typing import Any, Dict, List, Optional, Union
 
 import numpy as np
 
+from sahi.logger import logger
 from sahi.models.base import DetectionModel
 from sahi.prediction import ObjectPrediction
 from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list
 from sahi.utils.cv import get_bbox_from_bool_mask, get_coco_segmentation_from_bool_mask
 from sahi.utils.import_utils import check_requirements
 
-logger = logging.getLogger(__name__)
-
-
 try:
     check_requirements(["torch", "mmdet", "mmcv", "mmengine"])
 

sahi/models/roboflow.py

@@ -1,4 +1,3 @@
-import logging
 from typing import Any, Dict, List, Optional
 
 import numpy as np
@@ -8,8 +7,6 @@
 from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list
 from sahi.utils.import_utils import check_requirements
 
-logger = logging.getLogger(__name__)
-
 
 class RoboflowDetectionModel(DetectionModel):
     def __init__(

sahi/models/rtdetr.py

@@ -1,13 +1,10 @@
 # OBSS SAHI Tool
 # Code written by AnNT, 2023.
 
-import logging
 
 from sahi.models.ultralytics import UltralyticsDetectionModel
 from sahi.utils.import_utils import check_requirements
 
-logger = logging.getLogger(__name__)
-
 
 class RTDetrDetectionModel(UltralyticsDetectionModel):
     def check_dependencies(self) -> None:

sahi/models/torchvision.py

@@ -1,18 +1,16 @@
 # OBSS SAHI Tool
 # Code written by Fatih C Akyon and Kadir Nar, 2021.
 
-import logging
 from typing import Any, List, Optional
 
 import numpy as np
 
+from sahi.logger import logger
 from sahi.models.base import DetectionModel
 from sahi.prediction import ObjectPrediction
 from sahi.utils.cv import get_coco_segmentation_from_bool_mask
 from sahi.utils.import_utils import check_requirements
 
-logger = logging.getLogger(__name__)
-
 
 class TorchVisionDetectionModel(DetectionModel):
     def check_dependencies(self) -> None: