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[Update] Update synaptics detector coding format

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This commit is contained in:
GaryHuang-ASUS 2025-09-26 12:15:50 +08:00
parent f2df550a2a
commit 7a575a90bf
1 changed files with 7 additions and 15 deletions
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22
frigate/detectors/plugins/synaptics.py
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@ -1,19 +1,18 @@
import os
import logging import logging
import os
from typing_extensions import Literal
import numpy as np import numpy as np
from synap import Network from synap import Network
from synap.types import Shape, Layout
from synap.preprocessor import Preprocessor
from synap.postprocessor import Detector from synap.postprocessor import Detector
from synap.preprocessor import Preprocessor
from synap.types import Layout, Shape
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import ( from frigate.detectors.detector_config import (
BaseDetectorConfig, BaseDetectorConfig,
ModelTypeEnum,
InputTensorEnum, InputTensorEnum,
ModelTypeEnum,
) )
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -43,7 +42,6 @@ class SynapDetector(DetectionApi):
logger.error(f"Failed to init Synap NPU: {e}") logger.error(f"Failed to init Synap NPU: {e}")
raise raise
self.width = detector_config.model.width self.width = detector_config.model.width
self.height = detector_config.model.height self.height = detector_config.model.height
self.model_type = detector_config.model.model_type self.model_type = detector_config.model.model_type
@ -62,7 +60,7 @@ class SynapDetector(DetectionApi):
if self.input_tensor_layout == InputTensorEnum.nhwc: if self.input_tensor_layout == InputTensorEnum.nhwc:
layout = Layout.nhwc layout = Layout.nhwc
postprocess_data = self.preprocessor.assign( postprocess_data = self.preprocessor.assign(
self.network.inputs, tensor_input, Shape(tensor_input.shape), layout self.network.inputs, tensor_input, Shape(tensor_input.shape), layout
) )
@ -75,15 +73,11 @@ class SynapDetector(DetectionApi):
break break
bb = item.bounding_box bb = item.bounding_box
# Convert corner coordinates to normalized [0,1] range # Convert corner coordinates to normalized [0,1] range
x1 = bb.origin.x / self.width # Top-left X x1 = bb.origin.x / self.width # Top-left X
y1 = bb.origin.y / self.height # Top-left Y y1 = bb.origin.y / self.height # Top-left Y
x2 = (bb.origin.x + bb.size.x) / self.width # Bottom-right X x2 = (bb.origin.x + bb.size.x) / self.width # Bottom-right X
y2 = (bb.origin.y + bb.size.y) / self.height # Bottom-right Y y2 = (bb.origin.y + bb.size.y) / self.height # Bottom-right Y
detections[i] = [ detections[i] = [
item.class_index, item.class_index,
float(item.confidence), float(item.confidence),
@ -94,6 +88,4 @@ class SynapDetector(DetectionApi):
] ]
else: else:
logger.error(f"Unsupported model type: {self.model_type}") logger.error(f"Unsupported model type: {self.model_type}")
return detections
return np.zeros((20, 6), np.float32)