PyCharm reformat (#4209)

* PyCharm reformat

* YAML reformat

* Markdown reformat

.github/ISSUE_TEMPLATE/bug-report.md

@@ -7,21 +7,24 @@ assignees: ''
 
 ---
 
-Before submitting a bug report, please be aware that your issue **must be reproducible** with all of the following, otherwise it is non-actionable, and we can not help you:
+Before submitting a bug report, please be aware that your issue **must be reproducible** with all of the following,
+otherwise it is non-actionable, and we can not help you:
+
 - **Current repo**: run `git fetch && git status -uno` to check and `git pull` to update repo
 - **Common dataset**: coco.yaml or coco128.yaml
 - **Common environment**: Colab, Google Cloud, or Docker image. See https://github.com/ultralytics/yolov5#environments
 
-If this is a custom dataset/training question you **must include** your `train*.jpg`, `val*.jpg` and `results.png` figures, or we can not help you. You can generate these with `utils.plot_results()`.
+If this is a custom dataset/training question you **must include** your `train*.jpg`, `val*.jpg` and `results.png`
-
+figures, or we can not help you. You can generate these with `utils.plot_results()`.
 
 ## 🐛 Bug
-A clear and concise description of what the bug is.
 
+A clear and concise description of what the bug is.
 
 ## To Reproduce (REQUIRED)
 
 Input:
+
 ```
 import torch
 
@@ -30,6 +33,7 @@ c = a / 0
 ```
 
 Output:
+
 ```
 Traceback (most recent call last):
   File "/Users/glennjocher/opt/anaconda3/envs/env1/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3331, in run_code
@@ -39,17 +43,17 @@ Traceback (most recent call last):
 RuntimeError: ZeroDivisionError
 ```
 
-
 ## Expected behavior
+
 A clear and concise description of what you expected to happen.
 
-
 ## Environment
+
 If applicable, add screenshots to help explain your problem.
 
 - OS: [e.g. Ubuntu]
 - GPU [e.g. 2080 Ti]
 
-
 ## Additional context
+
 Add any other context about the problem here.

.github/ISSUE_TEMPLATE/feature-request.md

@@ -13,7 +13,8 @@ assignees: ''
 
 ## Motivation
 
-<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->
+<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? 
+e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->
 
 ## Pitch
 

.github/ISSUE_TEMPLATE/question.md

@@ -9,5 +9,4 @@ assignees: ''
 
 ## ❔Question
 
-
 ## Additional context

CONTRIBUTING.md

@@ -8,32 +8,44 @@ We love your input! We want to make contributing to YOLOv5 as easy and transpare
 - Proposing a new feature
 - Becoming a maintainer
 
-YOLOv5 works so well due to our combined community effort, and for every small improvement you contribute you will be helping push the frontiers of what's possible in AI 😃!
+YOLOv5 works so well due to our combined community effort, and for every small improvement you contribute you will be
-
+helping push the frontiers of what's possible in AI 😃!
 
 ## Submitting a Pull Request (PR) 🛠️
+
 Submitting a PR is easy! This example shows how to submit a PR for updating `requirements.txt` in 4 steps:
 
 ### 1. Select File to Update
+
 Select `requirements.txt` to update by clicking on it in GitHub.
 <p align="center"><img width="800" alt="PR_step1" src="https://user-images.githubusercontent.com/26833433/122260847-08be2600-ced4-11eb-828b-8287ace4136c.png"></p>
 
 ### 2. Click 'Edit this file'
+
 Button is in top-right corner.
 <p align="center"><img width="800" alt="PR_step2" src="https://user-images.githubusercontent.com/26833433/122260844-06f46280-ced4-11eb-9eec-b8a24be519ca.png"></p>
 
 ### 3. Make Changes
+
 Change `matplotlib` version from `3.2.2` to `3.3`.
 <p align="center"><img width="800" alt="PR_step3" src="https://user-images.githubusercontent.com/26833433/122260853-0a87e980-ced4-11eb-9fd2-3650fb6e0842.png"></p>
 
 ### 4. Preview Changes and Submit PR
-Click on the **Preview changes** tab to verify your updates. At the bottom of the screen select 'Create a **new branch** for this commit', assign your branch a descriptive name such as `fix/matplotlib_version` and click the green **Propose changes** button. All done, your PR is now submitted to YOLOv5 for review and approval 😃!
+
+Click on the **Preview changes** tab to verify your updates. At the bottom of the screen select 'Create a **new branch**
+for this commit', assign your branch a descriptive name such as `fix/matplotlib_version` and click the green **Propose
+changes** button. All done, your PR is now submitted to YOLOv5 for review and approval 😃!
 <p align="center"><img width="800" alt="PR_step4" src="https://user-images.githubusercontent.com/26833433/122260856-0b208000-ced4-11eb-8e8e-77b6151cbcc3.png"></p>
 
 ### PR recommendations
 
 To allow your work to be integrated as seamlessly as possible, we advise you to:
-- ✅ Verify your PR is **up-to-date with origin/master.** If your PR is behind origin/master an automatic [GitHub actions](https://github.com/ultralytics/yolov5/blob/master/.github/workflows/rebase.yml) rebase may be attempted by including the /rebase command in a comment body, or by running the following code, replacing 'feature' with the name of your local branch:
+
+- ✅ Verify your PR is **up-to-date with origin/master.** If your PR is behind origin/master an
+  automatic [GitHub actions](https://github.com/ultralytics/yolov5/blob/master/.github/workflows/rebase.yml) rebase may
+  be attempted by including the /rebase command in a comment body, or by running the following code, replacing 'feature'
+  with the name of your local branch:
+
 ```bash
 git remote add upstream https://github.com/ultralytics/yolov5.git
 git fetch upstream
@@ -41,30 +53,42 @@ git checkout feature  # <----- replace 'feature' with local branch name
 git merge upstream/master
 git push -u origin -f
 ```
-- ✅ Verify all Continuous Integration (CI) **checks are passing**.
-- ✅ Reduce changes to the absolute **minimum** required for your bug fix or feature addition. _"It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is."_  -Bruce Lee
 
+- ✅ Verify all Continuous Integration (CI) **checks are passing**.
+- ✅ Reduce changes to the absolute **minimum** required for your bug fix or feature addition. _"It is not daily increase
+  but daily decrease, hack away the unessential. The closer to the source, the less wastage there is."_  -Bruce Lee
 
 ## Submitting a Bug Report 🐛
 
 If you spot a problem with YOLOv5 please submit a Bug Report!
 
-For us to start investigating a possibel problem we need to be able to reproduce it ourselves first. We've created a few short guidelines below to help users provide what we need in order to get started.
+For us to start investigating a possibel problem we need to be able to reproduce it ourselves first. We've created a few
+short guidelines below to help users provide what we need in order to get started.
 
-When asking a question, people will be better able to provide help if you provide **code** that they can easily understand and use to **reproduce** the problem. This is referred to by community members as creating a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example). Your code that reproduces the problem should be:
+When asking a question, people will be better able to provide help if you provide **code** that they can easily
+understand and use to **reproduce** the problem. This is referred to by community members as creating
+a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example). Your code that reproduces
+the problem should be:
 
 * ✅ **Minimal** – Use as little code as possible that still produces the same problem
 * ✅ **Complete** – Provide **all** parts someone else needs to reproduce your problem in the question itself
 * ✅ **Reproducible** – Test the code you're about to provide to make sure it reproduces the problem
 
-In addition to the above requirements, for [Ultralytics](https://ultralytics.com/) to provide assistance your code should be:
+In addition to the above requirements, for [Ultralytics](https://ultralytics.com/) to provide assistance your code
+should be:
 
-* ✅ **Current** – Verify that your code is up-to-date with current GitHub [master](https://github.com/ultralytics/yolov5/tree/master), and if necessary `git pull` or `git clone` a new copy to ensure your problem has not already been resolved by previous commits.
+* ✅ **Current** – Verify that your code is up-to-date with current
-* ✅ **Unmodified** – Your problem must be reproducible without any modifications to the codebase in this repository. [Ultralytics](https://ultralytics.com/) does not provide support for custom code ⚠️.
+  GitHub [master](https://github.com/ultralytics/yolov5/tree/master), and if necessary `git pull` or `git clone` a new
-
+  copy to ensure your problem has not already been resolved by previous commits.
-If you believe your problem meets all of the above criteria, please close this issue and raise a new one using the 🐛 **Bug Report** [template](https://github.com/ultralytics/yolov5/issues/new/choose) and providing a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) to help us better understand and diagnose your problem. 
+* ✅ **Unmodified** – Your problem must be reproducible without any modifications to the codebase in this
+  repository. [Ultralytics](https://ultralytics.com/) does not provide support for custom code ⚠️.
 
+If you believe your problem meets all of the above criteria, please close this issue and raise a new one using the 🐛 **
+Bug Report** [template](https://github.com/ultralytics/yolov5/issues/new/choose) and providing
+a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) to help us better
+understand and diagnose your problem.
 
 ## License
 
-By contributing, you agree that your contributions will be licensed under the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/)
+By contributing, you agree that your contributions will be licensed under
+the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/)

README.md

@@ -52,31 +52,33 @@ YOLOv5 🚀 is a family of object detection architectures and models pretrained
 
 </div>
 
-
 ## <div align="center">Documentation</div>
 
 See the [YOLOv5 Docs](https://docs.ultralytics.com) for full documentation on training, testing and deployment.
 
-
 ## <div align="center">Quick Start Examples</div>
 
-
 <details open>
 <summary>Install</summary>
 
-[**Python>=3.6.0**](https://www.python.org/) is required with all [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) installed including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/):
+[**Python>=3.6.0**](https://www.python.org/) is required with all
+[requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) installed including
+[**PyTorch>=1.7**](https://pytorch.org/get-started/locally/):
 <!-- $ sudo apt update && apt install -y libgl1-mesa-glx libsm6 libxext6 libxrender-dev -->
+
 ```bash
 $ git clone https://github.com/ultralytics/yolov5
 $ cd yolov5
 $ pip install -r requirements.txt
 ```
+
 </details>
 
 <details open>
 <summary>Inference</summary>
 
-Inference with YOLOv5 and [PyTorch Hub](https://github.com/ultralytics/yolov5/issues/36). Models automatically download from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases).
+Inference with YOLOv5 and [PyTorch Hub](https://github.com/ultralytics/yolov5/issues/36). Models automatically download
+from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases).
 
 ```python
 import torch
@@ -85,7 +87,7 @@ import torch
 model = torch.hub.load('ultralytics/yolov5', 'yolov5s')  # or yolov5m, yolov5l, yolov5x, custom
 
 # Images
-img = 'https://ultralytics.com/images/zidane.jpg'  # or PosixPath, PIL, OpenCV, numpy, list
+img = 'https://ultralytics.com/images/zidane.jpg'  # or file, Path, PIL, OpenCV, numpy, list
 
 # Inference
 results = model(img)
@@ -101,7 +103,9 @@ results.print()  # or .show(), .save(), .crop(), .pandas(), etc.
 <details>
 <summary>Inference with detect.py</summary>
 
-`detect.py` runs inference on a variety of sources, downloading models automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases) and saving results to `runs/detect`.
+`detect.py` runs inference on a variety of sources, downloading models automatically from
+the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases) and saving results to `runs/detect`.
+
 ```bash
 $ python detect.py --source 0  # webcam
                             file.jpg  # image 
@@ -117,13 +121,18 @@ $ python detect.py --source 0  # webcam
 <details>
 <summary>Training</summary>
 
-Run commands below to reproduce results on [COCO](https://github.com/ultralytics/yolov5/blob/master/data/scripts/get_coco.sh) dataset (dataset auto-downloads on first use). 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).
+Run commands below to reproduce results
+on [COCO](https://github.com/ultralytics/yolov5/blob/master/data/scripts/get_coco.sh) dataset (dataset auto-downloads on
+first use). 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                                40
                                          yolov5l                                24
                                          yolov5x                                16
 ```
+
 <img width="800" src="https://user-images.githubusercontent.com/26833433/90222759-949d8800-ddc1-11ea-9fa1-1c97eed2b963.png">
 
 </details>  
@@ -132,7 +141,8 @@ $ python train.py --data coco.yaml --cfg yolov5s.yaml --weights '' --batch-size
 <summary>Tutorials</summary>
 
 * [Train Custom Data](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data)&nbsp; 🚀 RECOMMENDED
-* [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results)&nbsp; ☘️ RECOMMENDED
+* [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results)&nbsp; ☘️
+  RECOMMENDED
 * [Weights & Biases Logging](https://github.com/ultralytics/yolov5/issues/1289)&nbsp; 🌟 NEW
 * [Supervisely Ecosystem](https://github.com/ultralytics/yolov5/issues/2518)&nbsp; 🌟 NEW
 * [Multi-GPU Training](https://github.com/ultralytics/yolov5/issues/475)
@@ -147,10 +157,11 @@ $ python train.py --data coco.yaml --cfg yolov5s.yaml --weights '' --batch-size
 
 </details>
 
-
 ## <div align="center">Environments and Integrations</div>
 
-Get started in seconds with our verified environments and integrations, including [Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_readme) for automatic YOLOv5 experiment logging. Click each icon below for details.
+Get started in seconds with our verified environments and integrations,
+including [Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_readme) for automatic YOLOv5 experiment
+logging. Click each icon below for details.
 
 <div align="center">
     <a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb">
@@ -173,7 +184,6 @@ Get started in seconds with our verified environments and integrations, includin
     </a>
 </div>  
 
-
 ## <div align="center">Compete and Win</div>
 
 We are super excited about our first-ever Ultralytics YOLOv5 🚀 EXPORT Competition with **$10,000** in cash prizes!
@@ -183,7 +193,6 @@ We are super excited about our first-ever Ultralytics YOLOv5 🚀 EXPORT Competi
   <img width="850" src="https://github.com/ultralytics/yolov5/releases/download/v1.0/banner-export-competition.png"></a>
 </p>
 
-
 ## <div align="center">Why YOLOv5</div>
 
 <p align="center"><img width="800" src="https://user-images.githubusercontent.com/26833433/114313216-f0a5e100-9af5-11eb-8445-c682b60da2e3.png"></p>
@@ -195,11 +204,13 @@ We are super excited about our first-ever Ultralytics YOLOv5 🚀 EXPORT Competi
 <details>
   <summary>Figure Notes (click to expand)</summary>
 
-  * GPU Speed measures end-to-end time per image averaged over 5000 COCO val2017 images using a V100 GPU with batch size 32, and includes image preprocessing, PyTorch FP16 inference, postprocessing and NMS. 
+* GPU Speed measures end-to-end time per image averaged over 5000 COCO val2017 images using a V100 GPU with batch size
+  32, and includes image preprocessing, PyTorch FP16 inference, postprocessing and NMS.
 * EfficientDet data from [google/automl](https://github.com/google/automl) at batch size 8.
-  * **Reproduce** by `python val.py --task study --data coco.yaml --iou 0.7 --weights yolov5s6.pt yolov5m6.pt yolov5l6.pt yolov5x6.pt`
+* **Reproduce** by
-</details>
+  `python val.py --task study --data coco.yaml --iou 0.7 --weights yolov5s6.pt yolov5m6.pt yolov5l6.pt yolov5x6.pt`
 
+</details>
 
 ### Pretrained Checkpoints
 
@@ -222,23 +233,29 @@ We are super excited about our first-ever Ultralytics YOLOv5 🚀 EXPORT Competi
 <details>
   <summary>Table Notes (click to expand)</summary>
 
-  * AP<sup>test</sup> denotes COCO [test-dev2017](http://cocodataset.org/#upload) server results, all other AP results denote val2017 accuracy.  
+* AP<sup>test</sup> denotes COCO [test-dev2017](http://cocodataset.org/#upload) server results, all other AP results
-  * AP values are for single-model single-scale unless otherwise noted. **Reproduce mAP** by `python val.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65`  
+  denote val2017 accuracy.
-  * Speed<sub>GPU</sub> averaged over 5000 COCO val2017 images using a GCP [n1-standard-16](https://cloud.google.com/compute/docs/machine-types#n1_standard_machine_types) V100 instance, and includes FP16 inference, postprocessing and NMS. **Reproduce speed** by `python val.py --data coco.yaml --img 640 --conf 0.25 --iou 0.45 --half`  
+* AP values are for single-model single-scale unless otherwise noted. **Reproduce mAP**
+  by `python val.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65`
+* Speed<sub>GPU</sub> averaged over 5000 COCO val2017 images using a
+  GCP [n1-standard-16](https://cloud.google.com/compute/docs/machine-types#n1_standard_machine_types) V100 instance, and
+  includes FP16 inference, postprocessing and NMS. **Reproduce speed**
+  by `python val.py --data coco.yaml --img 640 --conf 0.25 --iou 0.45 --half`
 * All checkpoints are trained to 300 epochs with default settings and hyperparameters (no autoaugmentation).
-  * Test Time Augmentation ([TTA](https://github.com/ultralytics/yolov5/issues/303)) includes reflection and scale augmentation. **Reproduce TTA** by `python val.py --data coco.yaml --img 1536 --iou 0.7 --augment`
+* Test Time Augmentation ([TTA](https://github.com/ultralytics/yolov5/issues/303)) includes reflection and scale
-</details>
+  augmentation. **Reproduce TTA** by `python val.py --data coco.yaml --img 1536 --iou 0.7 --augment`
 
+</details>
 
 ## <div align="center">Contribute</div>
 
-We love your input! We want to make contributing to YOLOv5 as easy and transparent as possible. Please see our [Contributing Guide](CONTRIBUTING.md) to get started. 
+We love your input! We want to make contributing to YOLOv5 as easy and transparent as possible. Please see
-
+our [Contributing Guide](CONTRIBUTING.md) to get started.
 
 ## <div align="center">Contact</div>
 
-For issues running YOLOv5 please visit [GitHub Issues](https://github.com/ultralytics/yolov5/issues). For business or professional support requests please visit 
+For issues running YOLOv5 please visit [GitHub Issues](https://github.com/ultralytics/yolov5/issues). For business or
-[https://ultralytics.com/contact](https://ultralytics.com/contact).
+professional support requests please visit [https://ultralytics.com/contact](https://ultralytics.com/contact).
 
 <br>
 

data/scripts/get_coco.sh

@@ -12,7 +12,7 @@ d='../datasets' # unzip directory
 url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
 f='coco2017labels.zip' # or 'coco2017labels-segments.zip', 68 MB
 echo 'Downloading' $url$f ' ...'
-curl -L $url$f -o $f && unzip -q $f -d $d && rm $f & # download, unzip, remove in background
+curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
 
 # Download/unzip images
 d='../datasets/coco/images' # unzip directory
@@ -22,6 +22,6 @@ f2='val2017.zip'   # 1G, 5k images
 f3='test2017.zip'  # 7G, 41k images (optional)
 for f in $f1 $f2; do
   echo 'Downloading' $url$f '...'
-  curl -L $url$f -o $f && unzip -q $f -d $d && rm $f & # download, unzip, remove in background
+  curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
 done
 wait # finish background tasks

data/scripts/get_coco128.sh

@@ -12,6 +12,6 @@ d='../datasets' # unzip directory
 url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
 f='coco128.zip' # or 'coco2017labels-segments.zip', 68 MB
 echo 'Downloading' $url$f ' ...'
-curl -L $url$f -o $f && unzip -q $f -d $d && rm $f & # download, unzip, remove in background
+curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
 
 wait # finish background tasks

train.py

@@ -83,7 +83,6 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
             if resume:
                 weights, epochs, hyp = opt.weights, opt.epochs, opt.hyp
 
-            
     # Config
     plots = not evolve  # create plots
     cuda = device.type != 'cpu'
@@ -96,7 +95,6 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
     assert len(names) == nc, f'{len(names)} names found for nc={nc} dataset in {data}'  # check
     is_coco = data.endswith('coco.yaml') and nc == 80  # COCO dataset
 
-
     # Model
     pretrained = weights.endswith('.pt')
     if pretrained:

utils/downloads.py

@@ -115,7 +115,6 @@ def get_token(cookie="./cookie"):
                 return line.split()[-1]
     return ""
 
-
 # Google utils: https://cloud.google.com/storage/docs/reference/libraries ----------------------------------------------
 #
 #

utils/loggers/__init__.py

@@ -1,7 +1,8 @@
 # YOLOv5 experiment logging utils
-import torch
 import warnings
 from threading import Thread
+
+import torch
 from torch.utils.tensorboard import SummaryWriter
 
 from utils.general import colorstr, emojis

utils/loggers/wandb/log_dataset.py

@@ -1,5 +1,4 @@
 import argparse
-import yaml
 
 from wandb_utils import WandbLogger
 

utils/loggers/wandb/sweep.py

@@ -1,7 +1,8 @@
 import sys
-import wandb
 from pathlib import Path
 
+import wandb
+
 FILE = Path(__file__).absolute()
 sys.path.append(FILE.parents[2].as_posix())  # add utils/ to path
 

utils/loggers/wandb/wandb_utils.py

@@ -3,9 +3,10 @@
 import logging
 import os
 import sys
-import yaml
 from contextlib import contextmanager
 from pathlib import Path
+
+import yaml
 from tqdm import tqdm
 
 FILE = Path(__file__).absolute()

val.py

@@ -13,7 +13,6 @@ from threading import Thread
 
 import numpy as np
 import torch
-import yaml
 from tqdm import tqdm
 
 FILE = Path(__file__).absolute()