`ultralytics 8.0.152` bump `torch>=1.8.0` (#4299)

.github/workflows/ci.yaml

@@ -152,7 +152,7 @@ jobs:
         torch: [latest]
         include:
           - os: ubuntu-latest
-            python-version: '3.8'  # torch 1.7.0 requires python >=3.6, <=3.8
+            python-version: '3.8'  # torch 1.8.0 requires python >=3.6, <=3.8
             torch: '1.8.0'  # min torch version CI https://pypi.org/project/torchvision/
     steps:
       - uses: actions/checkout@v3

.github/workflows/greetings.yml

@@ -36,7 +36,7 @@ jobs:
 
             ## Install
 
-            Pip install the `ultralytics` package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt) in a [**Python>=3.7**](https://www.python.org/) environment with [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/).
+            Pip install the `ultralytics` package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/).
 
             ```bash
             pip install ultralytics

README.md

@@ -57,7 +57,7 @@ See below for a quickstart installation and usage example, and see the [YOLOv8 D
 <details open>
 <summary>Install</summary>
 
-Pip install the ultralytics package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/).
+Pip install the ultralytics package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/).
 
 [![PyPI version](https://badge.fury.io/py/ultralytics.svg)](https://badge.fury.io/py/ultralytics) [![Downloads](https://static.pepy.tech/badge/ultralytics)](https://pepy.tech/project/ultralytics)
 

README.zh-CN.md

@@ -57,7 +57,7 @@
 <details open>
 <summary>安装</summary>
 
-使用Pip在一个[**Python>=3.8**](https://www.python.org/)环境中安装`ultralytics`包，此环境还需包含[**PyTorch>=1.7**](https://pytorch.org/get-started/locally/)。这也会安装所有必要的[依赖项](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt)。
+使用Pip在一个[**Python>=3.8**](https://www.python.org/)环境中安装`ultralytics`包，此环境还需包含[**PyTorch>=1.8**](https://pytorch.org/get-started/locally/)。这也会安装所有必要的[依赖项](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt)。
 
 [![PyPI version](https://badge.fury.io/py/ultralytics.svg)](https://badge.fury.io/py/ultralytics) [![Downloads](https://static.pepy.tech/badge/ultralytics)](https://pepy.tech/project/ultralytics)
 

docs/yolov5/environments/aws_quickstart_tutorial.md

@@ -56,7 +56,7 @@ Select the checkbox next to your running instance, and then click Connect. Copy
 
 ## 4. Run YOLOv5
 
-Once you have logged in to your instance, clone the repository and install the dependencies in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Once you have logged in to your instance, clone the repository and install the dependencies in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/environments/google_cloud_quickstart_tutorial.md

@@ -27,7 +27,7 @@ The preinstalled [Anaconda](https://docs.anaconda.com/anaconda/packages/pkg-docs
 
 ## Step 2: Set Up the VM
 
-Clone the YOLOv5 repository and install the [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) will be downloaded automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone the YOLOv5 repository and install the [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) will be downloaded automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/quickstart_tutorial.md

@@ -11,8 +11,8 @@ See below for quickstart examples.
 ## Install
 
 Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a
-[**Python>=3.7.0**](https://www.python.org/) environment, including
-[**PyTorch>=1.7**](https://pytorch.org/get-started/locally/).
+[**Python>=3.8.0**](https://www.python.org/) environment, including
+[**PyTorch>=1.8**](https://pytorch.org/get-started/locally/).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/tutorials/hyperparameter_evolution.md

@@ -10,7 +10,7 @@ Hyperparameters in ML control various aspects of training, and finding optimal v
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/tutorials/model_ensembling.md

@@ -12,7 +12,7 @@ From [https://en.wikipedia.org/wiki/Ensemble_learning](https://en.wikipedia.org/
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/tutorials/model_export.md

@@ -11,7 +11,7 @@ UPDATED 8 December 2022.
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone
@@ -111,7 +111,7 @@ Output:
 
 ```bash
 export: data=data/coco128.yaml, weights=['yolov5s.pt'], imgsz=[640, 640], batch_size=1, device=cpu, half=False, inplace=False, train=False, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=12, verbose=False, workspace=4, nms=False, agnostic_nms=False, topk_per_class=100, topk_all=100, iou_thres=0.45, conf_thres=0.25, include=['torchscript', 'onnx']
-YOLOv5 🚀 v6.2-104-ge3e5122 Python-3.7.13 torch-1.12.1+cu113 CPU
+YOLOv5 🚀 v6.2-104-ge3e5122 Python-3.8.0 torch-1.12.1+cu113 CPU
 
 Downloading https://github.com/ultralytics/yolov5/releases/download/v6.2/yolov5s.pt to yolov5s.pt...
 100% 14.1M/14.1M [00:00<00:00, 274MB/s]

docs/yolov5/tutorials/model_pruning_and_sparsity.md

@@ -9,7 +9,7 @@ UPDATED 25 September 2022.
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/tutorials/multi_gpu_training.md

@@ -9,7 +9,7 @@ UPDATED 25 December 2022.
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/tutorials/pytorch_hub_model_loading.md

@@ -9,7 +9,7 @@ UPDATED 26 March 2023.
 
 ## Before You Start
 
-Install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 pip install -r https://raw.githubusercontent.com/ultralytics/yolov5/master/requirements.txt

docs/yolov5/tutorials/running_on_jetson_nano.md

@@ -55,8 +55,8 @@ vi requirements.txt
 - **Step 5.** Edit the following lines. Here you need to press **i** first to enter editing mode. Press **ESC**, then type **:wq** to save and quit
 
 ```sh
-# torch>=1.7.0
-# torchvision>=0.8.1
+# torch>=1.8.0
+# torchvision>=0.9.0
 ```
 
 **Note:** torch and torchvision are excluded for now because they will be installed later.

docs/yolov5/tutorials/test_time_augmentation.md

@@ -11,7 +11,7 @@ UPDATED 25 September 2022.
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/tutorials/train_custom_data.md

@@ -9,7 +9,7 @@ UPDATED 7 June 2023.
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

docs/yolov5/tutorials/transfer_learning_with_frozen_layers.md

@@ -9,7 +9,7 @@ UPDATED 25 September 2022.
 
 ## Before You Start
 
-Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
 
 ```bash
 git clone https://github.com/ultralytics/yolov5  # clone

requirements.txt

@@ -9,8 +9,8 @@ pillow>=7.1.2
 pyyaml>=5.3.1
 requests>=2.23.0
 scipy>=1.4.1
-torch>=1.7.0
-torchvision>=0.8.1
+torch>=1.8.0
+torchvision>=0.9.0
 tqdm>=4.64.0
 
 # Logging -------------------------------------

setup.py

@@ -21,7 +21,7 @@ def get_version():
 setup(
     name='ultralytics',  # name of pypi package
     version=get_version(),  # version of pypi package
-    python_requires='>=3.7',
+    python_requires='>=3.8',
     license='AGPL-3.0',
     description=('Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, '
                  'pose estimation and image classification.'),

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.151'
+__version__ = '8.0.152'
 
 from ultralytics.hub import start
 from ultralytics.models import RTDETR, SAM, YOLO

ultralytics/nn/tasks.py

@@ -598,11 +598,11 @@ def attempt_load_weights(weights, device=None, inplace=True, fuse=False):
         # Append
         ensemble.append(model.fuse().eval() if fuse and hasattr(model, 'fuse') else model.eval())  # model in eval mode
 
-    # Module compatibility updates
+    # Module updates
     for m in ensemble.modules():
         t = type(m)
         if t in (nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU, Detect, Segment):
-            m.inplace = inplace  # torch 1.7.0 compatibility
+            m.inplace = inplace
         elif t is nn.Upsample and not hasattr(m, 'recompute_scale_factor'):
             m.recompute_scale_factor = None  # torch 1.11.0 compatibility
 
@@ -634,11 +634,11 @@ def attempt_load_one_weight(weight, device=None, inplace=True, fuse=False):
 
     model = model.fuse().eval() if fuse and hasattr(model, 'fuse') else model.eval()  # model in eval mode
 
-    # Module compatibility updates
+    # Module updates
     for m in model.modules():
         t = type(m)
         if t in (nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU, Detect, Segment):
-            m.inplace = inplace  # torch 1.7.0 compatibility
+            m.inplace = inplace
         elif t is nn.Upsample and not hasattr(m, 'recompute_scale_factor'):
             m.recompute_scale_factor = None  # torch 1.11.0 compatibility
 

ultralytics/utils/checks.py

@@ -215,7 +215,7 @@ def check_font(font='Arial.ttf'):
         return file
 
 
-def check_python(minimum: str = '3.7.0') -> bool:
+def check_python(minimum: str = '3.8.0') -> bool:
     """
     Check current python version against the required minimum version.
 

ultralytics/utils/downloads.py

@@ -288,7 +288,7 @@ def safe_download(url,
 
         unzip_dir = dir or f.parent  # unzip to dir if provided else unzip in place
         if is_zipfile(f):
-            unzip_dir = unzip_file(file=f, path=unzip_dir)  # unzip
+            unzip_dir = unzip_file(file=f, path=unzip_dir, progress=progress)  # unzip
         elif f.suffix in ('.tar', '.gz'):
             LOGGER.info(f'Unzipping {f} to {unzip_dir.resolve()}...')
             subprocess.run(['tar', 'xf' if f.suffix == '.tar' else 'xfz', f, '--directory', unzip_dir], check=True)