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Author SHA1 Message Date
dependabot[bot]andGitHub b1769dac5e Bump node-forge from 1.3.3 to 1.4.0 in /docs
Bumps [node-forge](https://github.com/digitalbazaar/forge) from 1.3.3 to 1.4.0.
- [Changelog](https://github.com/digitalbazaar/forge/blob/main/CHANGELOG.md)
- [Commits](https://github.com/digitalbazaar/forge/compare/v1.3.3...v1.4.0)

---
updated-dependencies:
- dependency-name: node-forge
  dependency-version: 1.4.0
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-03-29 02:29:54 +00:00
3 changed files with 4 additions and 34 deletions
+3 -3
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@@ -15952,9 +15952,9 @@
}
},
"node_modules/node-forge": {
"version": "1.3.3",
"resolved": "https://registry.npmjs.org/node-forge/-/node-forge-1.3.3.tgz",
"integrity": "sha512-rLvcdSyRCyouf6jcOIPe/BgwG/d7hKjzMKOas33/pHEr6gbq18IK9zV7DiPvzsz0oBJPme6qr6H6kGZuI9/DZg==",
"version": "1.4.0",
"resolved": "https://registry.npmjs.org/node-forge/-/node-forge-1.4.0.tgz",
"integrity": "sha512-LarFH0+6VfriEhqMMcLX2F7SwSXeWwnEAJEsYm5QKWchiVYVvJyV9v7UDvUv+w5HO23ZpQTXDv/GxdDdMyOuoQ==",
"license": "(BSD-3-Clause OR GPL-2.0)",
"engines": {
"node": ">= 6.13.0"
-28
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@@ -8,8 +8,6 @@ from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detection_runners import get_optimized_runner
from frigate.detectors.detector_config import (
BaseDetectorConfig,
InputDTypeEnum,
InputTensorEnum,
ModelTypeEnum,
)
from frigate.util.model import (
@@ -61,34 +59,8 @@ class ONNXDetector(DetectionApi):
if self.onnx_model_type == ModelTypeEnum.yolox:
self.calculate_grids_strides()
self._warmup(detector_config)
logger.info(f"ONNX: {path} loaded")
def _warmup(self, detector_config: ONNXDetectorConfig) -> None:
"""Run a warmup inference to front-load one-time compilation costs.
Some GPU backends have a slow first inference: CUDA may need PTX JIT
compilation on newer architectures (e.g. NVIDIA 50-series / Blackwell),
and MIGraphX compiles the model graph on first run. Running it here
(during detector creation) keeps the watchdog start_time at 0.0 so the
process won't be killed.
"""
if detector_config.model.input_tensor == InputTensorEnum.nchw:
shape = (1, 3, detector_config.model.height, detector_config.model.width)
else:
shape = (1, detector_config.model.height, detector_config.model.width, 3)
if detector_config.model.input_dtype in (
InputDTypeEnum.float,
InputDTypeEnum.float_denorm,
):
dtype = np.float32
else:
dtype = np.uint8
logger.info("ONNX: warming up detector (may take a while on first run)...")
self.detect_raw(np.zeros(shape, dtype=dtype))
def detect_raw(self, tensor_input: np.ndarray):
if self.onnx_model_type == ModelTypeEnum.dfine:
tensor_output = self.runner.run(
@@ -601,9 +601,7 @@ function LibrarySelector({
const [confirmDelete, setConfirmDelete] = useState<string | null>(null);
const [renameClass, setRenameClass] = useState<string | null>(null);
const pageTitle = useMemo(() => {
if (pageToggle == "none") {
return t("details.none");
} else if (pageToggle != "train") {
if (pageToggle != "train") {
return pageToggle;
}