Upload anime_object_detection/detection/censor.py with huggingface_hub

anime_object_detection/detection/censor.py

@@ -0,0 +1,35 @@
+import re
+from typing import List, Tuple
+
+from imgutils.data import ImageTyping
+from imgutils.detect.censor import detect_censors
+from imgutils.generic.yolo import _open_models_for_repo_id
+
+from .base import DeepGHSObjectDetection
+
+
+def _parse_model_name(model_name: str):
+    matching = re.fullmatch(r'^censor_detect_(?P<version>[\s\S]+?)_(?P<level>[\s\S]+?)$', model_name)
+    return matching.group('version'), matching.group('level')
+
+
+class CensorDetection(DeepGHSObjectDetection):
+    def __init__(self):
+        DeepGHSObjectDetection.__init__(self, repo_id='deepghs/anime_censor_detection')
+
+    def _get_default_model(self) -> str:
+        return 'censor_detect_v1.0_s'
+
+    def _get_default_iou_and_score(self, model_name: str) -> Tuple[float, float]:
+        return 0.7, 0.3
+
+    def _get_labels(self, model_name: str) -> List[str]:
+        _, _, labels = _open_models_for_repo_id(self._repo_id)._open_model(model_name)
+        return labels
+
+    def detect(self, image: ImageTyping, model_name: str,
+               iou_threshold: float = 0.7, score_threshold: float = 0.25) \
+            -> List[Tuple[Tuple[float, float, float, float], str, float]]:
+        version, level = _parse_model_name(model_name)
+        return detect_censors(image, level=level, version=version,
+                              conf_threshold=score_threshold, iou_threshold=iou_threshold)