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Initial implementation of D-FINE model via ONNX (#16772)

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* initial implementation of D-FINE model

* revert docker-compose

* add docs for D-FINE

* remove weird auto-format issue
This commit is contained in:
Jason Hunter
2025-02-24 08:56:01 -07:00
committed by GitHub
parent 1d8f1bd7ae
commit 0de928703f
7 changed files with 172 additions and 12 deletions
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frigate/detectors/plugins/onnx.py
+16 -1
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@@ -9,7 +9,11 @@ from frigate.detectors.detector_config import (
BaseDetectorConfig,
ModelTypeEnum,
)
from frigate.util.model import get_ort_providers, post_process_yolov9
from frigate.util.model import (
get_ort_providers,
post_process_dfine,
post_process_yolov9,
)
logger = logging.getLogger(__name__)
@@ -41,6 +45,7 @@ class ONNXDetector(DetectionApi):
providers, options = get_ort_providers(
detector_config.device == "CPU", detector_config.device
)
self.model = ort.InferenceSession(
path, providers=providers, provider_options=options
)
@@ -55,6 +60,16 @@ class ONNXDetector(DetectionApi):
logger.info(f"ONNX: {path} loaded")
def detect_raw(self, tensor_input: np.ndarray):
if self.onnx_model_type == ModelTypeEnum.dfine:
tensor_output = self.model.run(
None,
{
"images": tensor_input,
"orig_target_sizes": np.array([[self.h, self.w]], dtype=np.int64),
},
)
return post_process_dfine(tensor_output, self.w, self.h)
model_input_name = self.model.get_inputs()[0].name
tensor_output = self.model.run(None, {model_input_name: tensor_input})