`ultralytics 8.2.42` NVIDIA TensorRT 10 default (#13943)

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>

docker/Dockerfile

@@ -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
 # libsm6 required by libqxcb to create QT-based windows for visualization; set 'QT_DEBUG_PLUGINS=1' to test in docker
 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
 # 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
 
 # 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
 # sudo docker kill $(sudo docker ps -q)

docker/Dockerfile-arm64

@@ -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
 # pkg-config and libhdf5-dev (not included) are needed to build 'h5py==3.11.0' aarch64 wheel required by 'tensorflow'
 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
 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
 
 # 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

docker/Dockerfile-conda

@@ -22,7 +22,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt .
 RUN conda config --set solver libmamba && \
     conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia && \
     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 -------------------------------------------------------------------------------------------------------
@@ -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
 
 # 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

docker/Dockerfile-cpu

@@ -16,7 +16,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
 # Install linux packages
 # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
 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
 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
 
 # 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

docker/Dockerfile-jetson-jetpack5

@@ -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
 # pkg-config and libhdf5-dev (not included) are needed to build 'h5py==3.11.0' aarch64 wheel required by 'tensorflow'
 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
 WORKDIR $APP_HOME

docker/Dockerfile-python

@@ -16,7 +16,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
 # Install linux packages
 # g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
 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
 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
 
 # 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

docker/Dockerfile-runner

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

ultralytics/__init__.py

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

ultralytics/engine/exporter.py

@@ -822,13 +822,13 @@ class Exporter:
             import tensorflow as tf  # noqa
         check_requirements(
             (
-                "keras",  # required by onnx2tf package
-                "tf_keras",  # required by onnx2tf package
+                "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",
                 "onnx2tf>1.17.5,<=1.22.3",
-                "sng4onnx>=1.0.1",
                 "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'
                 "flatbuffers>=23.5.26,<100",  # update old 'flatbuffers' included inside tensorflow package
                 "onnxruntime-gpu" if cuda else "onnxruntime",

ultralytics/utils/loss.py

@@ -214,7 +214,7 @@ class v8DetectionLoss:
         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]])
         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
         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 = 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
-            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:
             raise TypeError(
                 "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 = 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
-        mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0)
+        mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0.0)
 
         # Pboxes
         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 = 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
-            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:
             raise TypeError(
                 "ERROR ❌ OBB dataset incorrectly formatted or not a OBB dataset.\n"