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ultralytics 8.2.42 NVIDIA TensorRT 10 default (#13943)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: DeepDiver <zhaoxu1015@gmail.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
This commit is contained in:
Glenn Jocher 2024-06-24 21:05:09 +02:00 • committed by GitHub
parent 1d7eeae325
commit 3bb0c5afa3
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10 changed files with 23 additions and 22 deletions
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4
docker/Dockerfile
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@ -20,7 +20,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
# g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
# libsm6 required by libqxcb to create QT-based windows for visualization; set 'QT_DEBUG_PLUGINS=1' to test in docker # libsm6 required by libqxcb to create QT-based windows for visualization; set 'QT_DEBUG_PLUGINS=1' to test in docker
RUN apt update \ RUN apt update \
&& apt install --no-install-recommends -y gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 libsm6 && apt install --no-install-recommends -y gcc git zip unzip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 libsm6
# Security updates # Security updates
# https://security.snyk.io/vuln/SNYK-UBUNTU1804-OPENSSL-3314796 # https://security.snyk.io/vuln/SNYK-UBUNTU1804-OPENSSL-3314796
@ -62,7 +62,7 @@ RUN rm -rf tmp
# t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus '"device=2,3"' $t # t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus '"device=2,3"' $t
# Pull and Run with local directory access # Pull and Run with local directory access
# t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/datasets:/usr/src/datasets $t # t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/shared/datasets:/usr/src/datasets $t
# Kill all # Kill all
# sudo docker kill $(sudo docker ps -q) # sudo docker kill $(sudo docker ps -q)

4
docker/Dockerfile-arm64
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@ -18,7 +18,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
# g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
# pkg-config and libhdf5-dev (not included) are needed to build 'h5py==3.11.0' aarch64 wheel required by 'tensorflow' # pkg-config and libhdf5-dev (not included) are needed to build 'h5py==3.11.0' aarch64 wheel required by 'tensorflow'
RUN apt update \ RUN apt update \
&& apt install --no-install-recommends -y python3-pip git zip curl htop gcc libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 && apt install --no-install-recommends -y python3-pip git zip unzip curl htop gcc libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
# Create working directory # Create working directory
WORKDIR $APP_HOME WORKDIR $APP_HOME
@ -52,4 +52,4 @@ RUN ln -sf /usr/bin/python3 /usr/bin/python
# t=ultralytics/ultralytics:latest-arm64 && sudo docker pull $t && sudo docker run -it --ipc=host $t # t=ultralytics/ultralytics:latest-arm64 && sudo docker pull $t && sudo docker run -it --ipc=host $t
# Pull and Run with local volume mounted # Pull and Run with local volume mounted
# t=ultralytics/ultralytics:latest-arm64 && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t # t=ultralytics/ultralytics:latest-arm64 && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/shared/datasets:/usr/src/datasets $t

4
docker/Dockerfile-conda
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@ -22,7 +22,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt .
RUN conda config --set solver libmamba && \ RUN conda config --set solver libmamba && \
conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia && \ conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia && \
conda install -c conda-forge ultralytics mkl conda install -c conda-forge ultralytics mkl
# conda install -c pytorch -c nvidia -c conda-forge pytorch torchvision pytorch-cuda=11.8 ultralytics mkl # conda install -c pytorch -c nvidia -c conda-forge pytorch torchvision pytorch-cuda=12.1 ultralytics mkl
# Usage Examples ------------------------------------------------------------------------------------------------------- # Usage Examples -------------------------------------------------------------------------------------------------------
@ -37,4 +37,4 @@ RUN conda config --set solver libmamba && \
# t=ultralytics/ultralytics:latest-conda && sudo docker pull $t && sudo docker run -it --ipc=host $t # t=ultralytics/ultralytics:latest-conda && sudo docker pull $t && sudo docker run -it --ipc=host $t
# Pull and Run with local volume mounted # Pull and Run with local volume mounted
# t=ultralytics/ultralytics:latest-conda && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t # t=ultralytics/ultralytics:latest-conda && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/shared/datasets:/usr/src/datasets $t

4
docker/Dockerfile-cpu
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@ -16,7 +16,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
# Install linux packages # Install linux packages
# g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
RUN apt update \ RUN apt update \
&& apt install --no-install-recommends -y python3-pip git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 && apt install --no-install-recommends -y python3-pip git zip unzip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
# Create working directory # Create working directory
WORKDIR $APP_HOME WORKDIR $APP_HOME
@ -57,4 +57,4 @@ RUN ln -sf /usr/bin/python3 /usr/bin/python
# t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host --name NAME $t # t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host --name NAME $t
# Pull and Run with local volume mounted # Pull and Run with local volume mounted
# t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t # t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/shared/datasets:/usr/src/datasets $t

2
docker/Dockerfile-jetson-jetpack5
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@ -18,7 +18,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
# libusb-1.0-0 required for 'tflite_support' package when exporting to TFLite # libusb-1.0-0 required for 'tflite_support' package when exporting to TFLite
# pkg-config and libhdf5-dev (not included) are needed to build 'h5py==3.11.0' aarch64 wheel required by 'tensorflow' # pkg-config and libhdf5-dev (not included) are needed to build 'h5py==3.11.0' aarch64 wheel required by 'tensorflow'
RUN apt update \ RUN apt update \
&& apt install --no-install-recommends -y gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 && apt install --no-install-recommends -y gcc git zip unzip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
# Create working directory # Create working directory
WORKDIR $APP_HOME WORKDIR $APP_HOME

4
docker/Dockerfile-python
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@ -16,7 +16,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
# Install linux packages # Install linux packages
# g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
RUN apt update \ RUN apt update \
&& apt install --no-install-recommends -y python3-pip git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 && apt install --no-install-recommends -y python3-pip git zip unzip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
# Create working directory # Create working directory
WORKDIR $APP_HOME WORKDIR $APP_HOME
@ -54,4 +54,4 @@ RUN rm -rf tmp
# t=ultralytics/ultralytics:latest-python && sudo docker pull $t && sudo docker run -it --ipc=host $t # t=ultralytics/ultralytics:latest-python && sudo docker pull $t && sudo docker run -it --ipc=host $t
# Pull and Run with local volume mounted # Pull and Run with local volume mounted
# t=ultralytics/ultralytics:latest-python && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t # t=ultralytics/ultralytics:latest-python && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/shared/datasets:/usr/src/datasets $t

5
docker/Dockerfile-runner
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@ -9,14 +9,15 @@ FROM ultralytics/ultralytics:latest
WORKDIR /actions-runner WORKDIR /actions-runner
# Download and unpack the latest runner from https://github.com/actions/runner # Download and unpack the latest runner from https://github.com/actions/runner
RUN FILENAME=actions-runner-linux-x64-2.309.0.tar.gz && \ RUN FILENAME=actions-runner-linux-x64-2.317.0.tar.gz && \
curl -o $FILENAME -L https://github.com/actions/runner/releases/download/v2.309.0/$FILENAME && \ curl -o $FILENAME -L https://github.com/actions/runner/releases/download/v2.317.0/$FILENAME && \
tar xzf $FILENAME && \ tar xzf $FILENAME && \
rm $FILENAME rm $FILENAME
# Install runner dependencies # Install runner dependencies
ENV RUNNER_ALLOW_RUNASROOT=1 ENV RUNNER_ALLOW_RUNASROOT=1
ENV DEBIAN_FRONTEND=noninteractive ENV DEBIAN_FRONTEND=noninteractive
RUN pip install --no-cache-dir pytest-cov
RUN ./bin/installdependencies.sh && \ RUN ./bin/installdependencies.sh && \
apt-get -y install libicu-dev apt-get -y install libicu-dev

2
ultralytics/__init__.py
View file

@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = "8.2.41" __version__ = "8.2.42"
import os import os

8
ultralytics/engine/exporter.py
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@ -822,13 +822,13 @@ class Exporter:
import tensorflow as tf # noqa import tensorflow as tf # noqa
check_requirements( check_requirements(
( (
"keras", # required by onnx2tf package "keras", # required by 'onnx2tf' package
"tf_keras", # required by onnx2tf package "tf_keras", # required by 'onnx2tf' package
"sng4onnx>=1.0.1", # required by 'onnx2tf' package
"onnx_graphsurgeon>=0.3.26", # required by 'onnx2tf' package
"onnx>=1.12.0", "onnx>=1.12.0",
"onnx2tf>1.17.5,<=1.22.3", "onnx2tf>1.17.5,<=1.22.3",
"sng4onnx>=1.0.1",
"onnxslim>=0.1.31", "onnxslim>=0.1.31",
"onnx_graphsurgeon>=0.3.26",
"tflite_support<=0.4.3" if IS_JETSON else "tflite_support", # fix ImportError 'GLIBCXX_3.4.29' "tflite_support<=0.4.3" if IS_JETSON else "tflite_support", # fix ImportError 'GLIBCXX_3.4.29'
"flatbuffers>=23.5.26,<100", # update old 'flatbuffers' included inside tensorflow package "flatbuffers>=23.5.26,<100", # update old 'flatbuffers' included inside tensorflow package
"onnxruntime-gpu" if cuda else "onnxruntime", "onnxruntime-gpu" if cuda else "onnxruntime",

8
ultralytics/utils/loss.py
View file

@ -214,7 +214,7 @@ class v8DetectionLoss:
targets = torch.cat((batch["batch_idx"].view(-1, 1), batch["cls"].view(-1, 1), batch["bboxes"]), 1) targets = torch.cat((batch["batch_idx"].view(-1, 1), batch["cls"].view(-1, 1), batch["bboxes"]), 1)
targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]]) targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]])
gt_labels, gt_bboxes = targets.split((1, 4), 2) # cls, xyxy gt_labels, gt_bboxes = targets.split((1, 4), 2) # cls, xyxy
mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0) mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0.0)
# Pboxes # Pboxes
pred_bboxes = self.bbox_decode(anchor_points, pred_distri) # xyxy, (b, h*w, 4) pred_bboxes = self.bbox_decode(anchor_points, pred_distri) # xyxy, (b, h*w, 4)
@ -280,7 +280,7 @@ class v8SegmentationLoss(v8DetectionLoss):
targets = torch.cat((batch_idx, batch["cls"].view(-1, 1), batch["bboxes"]), 1) targets = torch.cat((batch_idx, batch["cls"].view(-1, 1), batch["bboxes"]), 1)
targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]]) targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]])
gt_labels, gt_bboxes = targets.split((1, 4), 2) # cls, xyxy gt_labels, gt_bboxes = targets.split((1, 4), 2) # cls, xyxy
mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0) mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0.0)
except RuntimeError as e: except RuntimeError as e:
raise TypeError( raise TypeError(
"ERROR ❌ segment dataset incorrectly formatted or not a segment dataset.\n" "ERROR ❌ segment dataset incorrectly formatted or not a segment dataset.\n"
@ -467,7 +467,7 @@ class v8PoseLoss(v8DetectionLoss):
targets = torch.cat((batch_idx, batch["cls"].view(-1, 1), batch["bboxes"]), 1) targets = torch.cat((batch_idx, batch["cls"].view(-1, 1), batch["bboxes"]), 1)
targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]]) targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]])
gt_labels, gt_bboxes = targets.split((1, 4), 2) # cls, xyxy gt_labels, gt_bboxes = targets.split((1, 4), 2) # cls, xyxy
mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0) mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0.0)
# Pboxes # Pboxes
pred_bboxes = self.bbox_decode(anchor_points, pred_distri) # xyxy, (b, h*w, 4) pred_bboxes = self.bbox_decode(anchor_points, pred_distri) # xyxy, (b, h*w, 4)
@ -652,7 +652,7 @@ class v8OBBLoss(v8DetectionLoss):
targets = targets[(rw >= 2) & (rh >= 2)] # filter rboxes of tiny size to stabilize training targets = targets[(rw >= 2) & (rh >= 2)] # filter rboxes of tiny size to stabilize training
targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]]) targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]])
gt_labels, gt_bboxes = targets.split((1, 5), 2) # cls, xywhr gt_labels, gt_bboxes = targets.split((1, 5), 2) # cls, xywhr
mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0) mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0.0)
except RuntimeError as e: except RuntimeError as e:
raise TypeError( raise TypeError(
"ERROR ❌ OBB dataset incorrectly formatted or not a OBB dataset.\n" "ERROR ❌ OBB dataset incorrectly formatted or not a OBB dataset.\n"