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Code Issues Projects Releases Wiki Activity

Various fixes (#17411)

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* Remove initial requirement for history

* Clenaup conf

* Handle symlinks
This commit is contained in:
Nicolas Mowen 2025-03-27 08:28:09 -06:00 committed by GitHub
parent 1233bc3a42
commit a35146ab61
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3 changed files with 16 additions and 9 deletions
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17
docker/tensorrt/Dockerfile.base
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@ -20,8 +20,21 @@ RUN --mount=type=bind,source=docker/tensorrt/detector/tensorrt_libyolo.sh,target
# COPY required individual CUDA deps
RUN mkdir -p /usr/local/cuda-deps
RUN if [ "$TARGETARCH" = "amd64" ]; then \
cp /usr/local/cuda-12.3/targets/x86_64-linux/lib/libcurand.s* /usr/local/cuda-deps/ && \
cp /usr/local/cuda-12.3/targets/x86_64-linux/lib/libnvrtc.s* /usr/local/cuda-deps/ ; \
cp /usr/local/cuda-12.3/targets/x86_64-linux/lib/libcurand.so.* /usr/local/cuda-deps/ && \
cp /usr/local/cuda-12.3/targets/x86_64-linux/lib/libnvrtc.so.* /usr/local/cuda-deps/ && \
cd /usr/local/cuda-deps/ && \
for lib in libnvrtc.so.*; do \
if [[ "$lib" =~ libnvrtc.so\.([0-9]+\.[0-9]+\.[0-9]+) ]]; then \
version="${BASH_REMATCH[1]}"; \
ln -sf "libnvrtc.so.$version" libnvrtc.so; \
fi; \
done && \
for lib in libcurand.so.*; do \
if [[ "$lib" =~ libcurand.so\.([0-9]+\.[0-9]+\.[0-9]+\.[0-9]+) ]]; then \
version="${BASH_REMATCH[1]}"; \
ln -sf "libcurand.so.$version" libcurand.so; \
fi; \
done; \
fi
# Frigate w/ TensorRT Support as separate image

3
docker/tensorrt/detector/rootfs/etc/ld.so.conf.d/cuda_tensorrt.conf
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@ -1,8 +1,7 @@
/usr/local/lib
/usr/local/cuda
/usr/local/lib/python3.11/dist-packages/tensorrt
/usr/local/lib/python3.11/dist-packages/nvidia/cudnn/lib
/usr/local/lib/python3.11/dist-packages/nvidia/cuda_runtime/lib
/usr/local/lib/python3.11/dist-packages/nvidia/cublas/lib
/usr/local/lib/python3.11/dist-packages/nvidia/cuda_nvrtc/lib
/usr/local/lib/python3.11/dist-packages/tensorrt
/usr/local/lib/python3.11/dist-packages/nvidia/cufft/lib

5
frigate/data_processing/real_time/face.py
View File

@ -390,11 +390,6 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
self.person_face_history.pop(object_id)
def weighted_average_by_area(self, results_list: list[tuple[str, float, int]]):
min_faces = 1 if self.requires_face_detection else 3
if len(results_list) < min_faces:
return "unknown", 0.0
score_count = {}
weighted_scores = {}
total_face_areas = {}