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revert to hard-coded settings. use ModelTypeEnum directly

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This commit is contained in:
Dan Brown 2025-12-02 15:09:54 +01:00
parent 20f1e17637
commit d686b303ed
1 changed files with 2 additions and 12 deletions
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14
frigate/detectors/plugins/edgetpu_tfl.py
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@ -73,24 +73,14 @@ class EdgeTpuTfl(DetectionApi):
self.model_height = detector_config.model.height self.model_height = detector_config.model.height
self.min_score = 0.4 self.min_score = 0.4
try:
self.min_score = detector_config.model.min_score
except AttributeError:
pass
self.max_detections = 20 self.max_detections = 20
try:
self.max_detections = detector_config.model.max_detections
except AttributeError:
pass
model_type = detector_config.model.model_type model_type = detector_config.model.model_type
self.yolo_model = model_type == ModelTypeEnum.yologeneric
self.model_requires_int8 = self.tensor_input_details[0]["dtype"] == np.int8 self.model_requires_int8 = self.tensor_input_details[0]["dtype"] == np.int8
if self.model_requires_int8: if self.model_requires_int8:
logger.info("Detection model requires int8 format input") logger.info("Detection model requires int8 format input")
if self.yolo_model: if model_type == ModelTypeEnum.yologeneric
logger.info( logger.info(
f"Preparing YOLO postprocessing for {len(self.tensor_output_details)}-tensor output" f"Preparing YOLO postprocessing for {len(self.tensor_output_details)}-tensor output"
) )
@ -224,7 +214,7 @@ class EdgeTpuTfl(DetectionApi):
self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input) self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input)
self.interpreter.invoke() self.interpreter.invoke()
if self.yolo_model: if model_type == ModelTypeEnum.yologeneric
if len(self.tensor_output_details) == 1: if len(self.tensor_output_details) == 1:
# Single-tensor YOLO model # Single-tensor YOLO model
# model output is (1, NC+4, 2100) for 320x320 image size # model output is (1, NC+4, 2100) for 320x320 image size