make installable pip package

.github/workflows/ci-testing.yml

@@ -14,7 +14,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: [3.8]
+        python-version: [3.7, 3.8]
         model: ['yolov5s']  # models to test
 
     # Timeout: https://stackoverflow.com/a/59076067/4521646
@@ -53,23 +53,44 @@ jobs:
 
       - name: Download data
         run: |
-          python -c "from utils.google_utils import * ; gdrive_download('1n_oKgR81BJtqk75b00eAjdv03qVCQn2f', 'coco128.zip')"
+          python -c "from yolo5.utils.google_utils import * ; gdrive_download('1n_oKgR81BJtqk75b00eAjdv03qVCQn2f', 'coco128.zip')"
           mv ./coco128 ../
 
+      - name: PyTest
+        run: |
+          pip install -q coverage pytest pytest-flake8
+          # todo: make code PEP8 complient and uncoment this Flake8 check
+          coverage run --source yolo5 -m pytest yolo5 --doctest-modules #  --flake8
+          coverage report
+
       - name: Tests workflow
         run: |
           export PYTHONPATH="$PWD"  # to run *.py. files in subdirectories
           di=cpu # inference devices  # define device
-
           # train
-          python train.py --img 256 --batch 8 --weights weights/${{ matrix.model }}.pt --cfg models/${{ matrix.model }}.yaml --epochs 1 --device $di
+          python yolo5/train.py --img 256 --batch 8 --weights ./weights/${{ matrix.model }}.pt --cfg ./models/${{ matrix.model }}.yaml --epochs 1 --device $di
           # detect
-          python detect.py --weights weights/${{ matrix.model }}.pt --device $di
-          python detect.py --weights runs/exp0/weights/last.pt --device $di
+          python yolo5/detect.py --weights ./weights/${{ matrix.model }}.pt --device $di
+          python yolo5/detect.py --weights ./runs/exp0/weights/last.pt --device $di
           # test
-          python test.py --img 256 --batch 8 --weights weights/${{ matrix.model }}.pt --device $di
-          python test.py --img 256 --batch 8 --weights runs/exp0/weights/last.pt --device $di
-
-          python models/yolo.py --cfg models/${{ matrix.model }}.yaml  # inspect
-          python models/export.py --img 256 --batch 1 --weights weights/${{ matrix.model }}.pt  # export
+          python yolo5/test.py --img 256 --batch 8 --weights ./weights/${{ matrix.model }}.pt --device $di
+          python yolo5/test.py --img 256 --batch 8 --weights ./runs/exp0/weights/last.pt --device $di
+          # inspect
+          python yolo5/models/yolo.py --cfg ./models/${{ matrix.model }}.yaml
+          # export
+          python yolo5/export.py --img 256 --batch 1 --weights ./weights/${{ matrix.model }}.pt
         shell: bash
+
+      - name: Test Install
+        run: |
+          pip install -q check-manifest twine
+
+          check-manifest
+          python setup.py check --metadata --strict
+
+          # Build the package
+          python setup.py sdist bdist_wheel
+          twine check ./dist/*
+
+          # Dry run install
+          python setup.py install --dry-run

MANIFEST.in

@@ -0,0 +1,39 @@
+# Manifest syntax https://docs.python.org/2/distutils/sourcedist.html
+graft wheelhouse
+
+recursive-exclude __pycache__ *.pyc *.pyo *.orig
+
+# Include the README
+include *.md
+
+# Include the license file
+include LICENSE
+
+# Include the Requirements
+include requirements.txt
+
+# Include package
+recursive-include yolo5 *.py *.yaml
+
+# Include setup
+include setup.*
+
+# Exclude testing
+exclude pytest.*
+recursive-exclude tests *
+exclude tests
+
+# Exclude experiments
+exclude */*.sh
+exclude *.ipynb
+exclude Dockerfile .dockerignore
+
+prune .git
+prune .github
+prune run
+prune venv
+prune build
+prune docs
+prune tests
+prune data
+prune inference

README.md

@@ -41,6 +41,13 @@ Python 3.7 or later with all `requirements.txt` dependencies installed, includin
 $ pip install -U -r requirements.txt
 ```
 
+## Installation
+
+You can install this package straight with pip
+```bash
+pip install git+https://github.com/ultralytics/yolov5.git
+```
+
 
 ## Tutorials
 
@@ -68,19 +75,19 @@ YOLOv5 may be run in any of the following up-to-date verified environments (with
 
 Inference can be run on most common media formats. Model [checkpoints](https://drive.google.com/open?id=1Drs_Aiu7xx6S-ix95f9kNsA6ueKRpN2J) are downloaded automatically if available. Results are saved to `./inference/output`.
 ```bash
-$ python detect.py --source 0  # webcam
-                            file.jpg  # image 
-                            file.mp4  # video
-                            path/  # directory
-                            path/*.jpg  # glob
-                            rtsp://170.93.143.139/rtplive/470011e600ef003a004ee33696235daa  # rtsp stream
-                            http://112.50.243.8/PLTV/88888888/224/3221225900/1.m3u8  # http stream
+$ python yolo5/detect.py --source 0  # webcam
+                                  file.jpg  # image 
+                                  file.mp4  # video
+                                  path/  # directory
+                                  path/*.jpg  # glob
+                                  rtsp://170.93.143.139/rtplive/470011e600ef003a004ee33696235daa  # rtsp stream
+                                  http://112.50.243.8/PLTV/88888888/224/3221225900/1.m3u8  # http stream
 ```
 
 To run inference on examples in the `./inference/images` folder:
 
 ```bash
-$ python detect.py --source ./inference/images/ --weights yolov5s.pt --conf 0.4
+$ python yolo5/detect.py --source ./inference/images/ --weights yolov5s.pt --conf 0.4
 
 Namespace(agnostic_nms=False, augment=False, classes=None, conf_thres=0.4, device='', fourcc='mp4v', half=False, img_size=640, iou_thres=0.5, output='inference/output', save_txt=False, source='./inference/images/', view_img=False, weights='yolov5s.pt')
 Using CUDA device0 _CudaDeviceProperties(name='Tesla P100-PCIE-16GB', total_memory=16280MB)
@@ -99,10 +106,10 @@ Results saved to /content/yolov5/inference/output
 
 Download [COCO](https://github.com/ultralytics/yolov5/blob/master/data/get_coco2017.sh), install [Apex](https://github.com/NVIDIA/apex) and run command below. Training times for YOLOv5s/m/l/x are 2/4/6/8 days on a single V100 (multi-GPU times faster). Use the largest `--batch-size` your GPU allows (batch sizes shown for 16 GB devices).
 ```bash
-$ python train.py --data coco.yaml --cfg yolov5s.yaml --weights '' --batch-size 64
-                                         yolov5m                                48
-                                         yolov5l                                32
-                                         yolov5x                                16
+$ python yolo5/train.py --data coco.yaml --cfg yolov5s.yaml --weights '' --batch-size 64
+                                               yolov5m                                48
+                                               yolov5l                                32
+                                               yolov5x                                16
 ```
 <img src="https://user-images.githubusercontent.com/26833433/84186698-c4d54d00-aa45-11ea-9bde-c632c1230ccd.png" width="900">
 

setup.cfg

@@ -0,0 +1,30 @@
+[metadata]
+# This includes the license file(s) in the wheel.
+# https://wheel.readthedocs.io/en/stable/user_guide.html#including-license-files-in-the-generated-wheel-file
+license_files = LICENSE
+
+[bdist_wheel]
+# This flag says to generate wheels that support both Python 2 and Python
+# 3. If your code will not run unchanged on both Python 2 and 3, you will
+# need to generate separate wheels for each Python version that you
+# support. Removing this line (or setting universal to 0) will prevent
+# bdist_wheel from trying to make a universal wheel. For more see:
+# https://packaging.python.org/guides/distributing-packages-using-setuptools/#wheels
+universal=1
+
+[flake8]
+# http://flake8.pycqa.org/en/latest/user/configuration.html
+ignore = E501
+max-line-length = 100
+exclude = *.egg,build,temp
+select = E,W,F
+doctests = True
+verbose = 2
+# max-complexity = 10
+
+[tool:pytest]
+log_cli = 1
+log_cli_level = CRITICAL
+log_file = pytest.log
+log_file_level = DEBUG
+filterwarnings = ignore::FutureWarning

setup.py

@@ -0,0 +1,136 @@
+"""A setuptools based setup module.
+
+See:
+https://packaging.python.org/guides/distributing-packages-using-setuptools/
+https://github.com/pypa/sampleproject
+"""
+
+# Always prefer setuptools over distutils
+from os import path
+from setuptools import setup, find_packages
+
+import yolo5
+
+PATH_HERE = path.abspath(path.dirname(__file__))
+
+with open(path.join(PATH_HERE, 'requirements.txt')) as fp:
+    install_reqs = [r.rstrip() for r in fp.readlines() if not r.startswith('#')]
+
+# Get the long description from the README file
+with open(path.join(PATH_HERE, 'README.md'), encoding='utf-8') as fp:
+    long_description = fp.read()
+
+# Arguments marked as "Required" below must be included for upload to PyPI.
+# Fields marked as "Optional" may be commented out.
+
+setup(
+    # This is the name of your project. The first time you publish this
+    # package, this name will be registered for you. It will determine how
+    # users can install this project, e.g.:
+    #
+    # $ pip install YOLOv5
+    #
+    # And where it will live on PyPI: https://pypi.org/project/YOLOv5/
+    name='YOLOv5',  # Required
+    version=yolo5.__version__,  # Required
+    description=yolo5.__doc__,  # Optional
+
+    # This is an optional longer description of your project that represents
+    # the body of text which users will see when they visit PyPI.
+    long_description=yolo5.__doc_long__,  # Optional
+
+    # Denotes that our long_description is in Markdown; valid values are
+    # text/plain, text/x-rst, and text/markdown
+    long_description_content_type='text/markdown',  # Optional (see note above)
+
+    # This should be a valid link to your project's main homepage.
+    url='https://github.com/ultralytics/yolov5',  # Optional
+
+    # This should be your name or the name of the organization which owns the project.
+    author='Ultralytics',  # Optional
+    # This should be a valid email address corresponding to the author listed above.
+    author_email='glenn.jocher@ultralytics.com',  # Optional
+
+    # Classifiers help users find your project by categorizing it.
+    # For a list of valid classifiers, see https://pypi.org/classifiers/
+    classifiers=[  # Optional
+        # How mature is this project? Common values are
+        #   3 - Alpha
+        #   4 - Beta
+        #   5 - Production/Stable
+        'Development Status :: 5 - Production/Stable',
+
+        # Indicate who your project is intended for
+        'Intended Audience :: Developers',
+
+        # Operation system
+        'Operating System :: OS Independent',
+
+        # Topics
+        'Topic :: Education',
+        'Topic :: Scientific/Engineering',
+        'Topic :: Scientific/Engineering :: Artificial Intelligence',
+        'Topic :: Scientific/Engineering :: Image Recognition',
+
+        # Pick your license as you wish
+        'License :: OSI Approved :: Apache Software License',
+
+        # Specify the Python versions you support here. In particular, ensure
+        # that you indicate whether you support Python 2, Python 3 or both.
+        # These classifiers are *not* checked by 'pip install'. See instead
+        # 'python_requires' below.
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
+    ],
+
+    # This field adds keywords for your project which will appear on the
+    # project page. What does your project relate to?
+    keywords='YOLO object-detection',  # Optional
+
+    # You can just specify package directories manually here if your project is
+    # simple. Or you can use find_packages().
+    packages=find_packages(exclude=['contrib', 'docs', 'tests']),  # Required
+
+    # Specify which Python versions you support. In contrast to the
+    # 'Programming Language' classifiers above, 'pip install' will check this
+    # and refuse to install the project if the version does not match. If you
+    # do not support Python 2, you can simplify this to '>=3.5' or similar, see
+    # https://packaging.python.org/guides/distributing-packages-using-setuptools/#python-requires
+    python_requires='>=3.6, <4',
+    install_requires=install_reqs,
+
+    # This field lists other packages that your project depends on to run.
+    # Any package you put here will be installed by pip when your project is
+    # installed, so they must be valid existing projects.
+    # install_requires=[],  # Optional
+
+    # Although 'package_data' is the preferred approach, in some case you may
+    # need to place data files outside of your packages. See:
+    # http://docs.python.org/3.4/distutils/setupscript.html#installing-additional-files
+    #
+    # In this case, 'data_file' will be installed into '<sys.prefix>/my_data'
+    data_files=[('models',
+                 [f'yolo5/models/yolov5{n}.yaml' for n in 'smlx']
+                 + ['yolo5/models/hub/yolov3-spp.yaml']
+                 + [f'yolo5/models/hub/yolov5-{n}.yaml' for n in ('fpn', 'panet')]
+                 )],  # Optional
+
+    # To provide executable scripts, use entry points in preference to the
+    # "scripts" keyword. Entry points provide cross-platform support and allow
+    # `pip` to create the appropriate form of executable for the target
+    # platform.
+    # entry_points={  # Optional
+    #     'console_scripts': [
+    #         'sandbox=sandbox:main',
+    #     ],
+    # },
+
+    # List additional URLs that are relevant to your project as a dict.
+    project_urls={  # Optional
+        'Bug Reports': 'https://github.com/ultralytics/yolov5/issues',
+        'Funding': 'https://www.ultralytics.com',
+        'Source': 'https://github.com/ultralytics/yolov5/',
+    },
+)

yolo5/__init__.py

@@ -0,0 +1,12 @@
+__version__ = '2.0rc1'
+__doc__ = "YOLO v5 - object detection network"
+__doc_long__ = """
+# YOLO v5
+
+This repository represents Ultralytics open-source research into future object detection methods,
+ and incorporates our lessons learned and best practices evolved over training thousands of models
+ on custom client datasets with our previous YOLO repository https://github.com/ultralytics/yolov3.
+
+**All code and models are under active development, and are subject to modification or deletion without notice.**
+ Use at your own risk.
+"""

detect.py → yolo5/detect.py

@@ -10,10 +10,10 @@
 import torch.backends.cudnn as cudnn
 from numpy import random
 
-from models.experimental import attempt_load
-from utils.datasets import LoadStreams, LoadImages
-from utils.general import check_img_size, non_max_suppression, apply_classifier, scale_coords, xyxy2xywh, plot_one_box
-from utils.torch_utils import select_device, load_classifier, time_synchronized
+from yolo5.models.experimental import attempt_load
+from yolo5.utils.datasets import LoadStreams, LoadImages
+from yolo5.utils.general import check_img_size, non_max_suppression, apply_classifier, scale_coords, xyxy2xywh, plot_one_box
+from yolo5.utils.torch_utils import select_device, load_classifier, time_synchronized
 
 
 def detect(save_img=False):

models/export.py → yolo5/export.py

@@ -8,17 +8,10 @@
 
 import torch
 
-from utils.google_utils import attempt_download
+from yolo5.utils.google_utils import attempt_download
 
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--weights', type=str, default='./yolov5s.pt', help='weights path')
-    parser.add_argument('--img-size', nargs='+', type=int, default=[640, 640], help='image size')
-    parser.add_argument('--batch-size', type=int, default=1, help='batch size')
-    opt = parser.parse_args()
-    opt.img_size *= 2 if len(opt.img_size) == 1 else 1  # expand
-    print(opt)
 
+def main(opt):
     # Input
     img = torch.zeros((opt.batch_size, 3, *opt.img_size))  # image size(1,3,320,192) iDetection
 
@@ -72,3 +65,14 @@
 
     # Finish
     print('\nExport complete. Visualize with https://github.com/lutzroeder/netron.')
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--weights', type=str, default='./yolov5s.pt', help='weights path')
+    parser.add_argument('--img-size', nargs='+', type=int, default=[640, 640], help='image size')
+    parser.add_argument('--batch-size', type=int, default=1, help='batch size')
+    opt = parser.parse_args()
+    opt.img_size *= 2 if len(opt.img_size) == 1 else 1  # expand
+    print(opt)
+
+    main(opt)