From f39c2baa94d6d62d528e95df727bcdd82f255115 Mon Sep 17 00:00:00 2001
From: Sergey Krashevich <svk@svk.su>
Date: Mon, 8 May 2023 05:14:03 +0300
Subject: [PATCH] code formatiing

---
 frigate/detectors/plugins/mediapipe.py | 29 +++++++++++++++-----------
 1 file changed, 17 insertions(+), 12 deletions(-)

diff --git a/frigate/detectors/plugins/mediapipe.py b/frigate/detectors/plugins/mediapipe.py
index c1e9f9dbb..15c160288 100644
--- a/frigate/detectors/plugins/mediapipe.py
+++ b/frigate/detectors/plugins/mediapipe.py
@@ -16,24 +16,28 @@ logger = logging.getLogger(__name__)
 
 DETECTOR_KEY = "mediapipe"
 
+
 class MediapipeDetectorConfig(BaseDetectorConfig):
     type: Literal[DETECTOR_KEY]
-    #num_threads: int = Field(default=3, title="Number of detection threads")
+
 
 class Mediapipe(DetectionApi):
     type_key = DETECTOR_KEY
 
     def __init__(self, detector_config: MediapipeDetectorConfig):
         base_options = python.BaseOptions(model_asset_path=detector_config.model.path)
-        options = vision.ObjectDetectorOptions(base_options=base_options,
-                                            score_threshold=0.5)
+        options = vision.ObjectDetectorOptions(
+            base_options=base_options, score_threshold=0.5
+        )
         self.detector = vision.ObjectDetector.create_from_options(options)
         self.labels = detector_config.model.merged_labelmap
 
         self.h = detector_config.model.height
         self.w = detector_config.model.width
-        logger.debug(f"Detection started. Model: {detector_config.model.path}, h: {self.h}, w: {self.w}")
-        
+        logger.debug(
+            f"Detection started. Model: {detector_config.model.path}, h: {self.h}, w: {self.w}"
+        )
+
     def get_label_index(self, label_value):
         if label_value.lower() == "truck":
             label_value = "car"
@@ -41,7 +45,7 @@ class Mediapipe(DetectionApi):
             if value == label_value.lower():
                 return index
         return -1
-    
+
     def detect_raw(self, tensor_input):
         # STEP 3: Load the input image.
         image_data = np.squeeze(tensor_input).astype(np.uint8)
@@ -56,8 +60,10 @@ class Mediapipe(DetectionApi):
         for i, detection in enumerate(results.detections):
             if i == 20:
                 break
-            
-            bbox = detection.bounding_box # left, upper, right, and lower pixel coordinate.
+
+            bbox = (
+                detection.bounding_box
+            )  # left, upper, right, and lower pixel coordinate.
             category = detection.categories[0]
             label = self.get_label_index(category.category_name)
             if label < 0:
@@ -68,10 +74,9 @@ class Mediapipe(DetectionApi):
                 round(category.score, 2),
                 bbox.origin_y / self.h,
                 bbox.origin_x / self.w,
-                (bbox.origin_y+bbox.height) / self.h,
-                (bbox.origin_x+bbox.width) / self.w,
+                (bbox.origin_y + bbox.height) / self.h,
+                (bbox.origin_x + bbox.width) / self.w,
             ]
             logger.debug(f"Detection: raw: {detection} result: {detections[i]}")
 
-            
-        return detections
\ No newline at end of file
+        return detections