Update Neuralmagic-YoloV5 integration to v6.1 (#29)

* Fix TensorRT potential unordered binding addresses (ultralytics#5826)

* feat: change file suffix in pythonic way

* fix: enforce binding addresses order

* fix: enforce binding addresses order

* Handle non-TTY `wandb.errors.UsageError` (ultralytics#5839)

* `try: except (..., wandb.errors.UsageError)`

* bug fix

* Avoid inplace modifying`imgs` in `LoadStreams` (ultralytics#5850)

When OpenCV retrieving image fail, original code would modify source images **inplace**, which may result in plotting bounding boxes on a black image. That is, before inference, source image `im0s[i]` is OK, but after inference before `Process predictions`,  `im0s[i]` may have been changed.

* Update `LoadImages` `ret_val=False` handling (ultralytics#5852)

Video errors may occur.

* Update val.py (ultralytics#5838)

* Update val.py

Solving Non-ASCII character '\xf0' error during runtime

* Update val.py

Co-authored-by: Glenn Jocher <[email protected]>

* Update TorchScript suffix to `*.torchscript` (ultralytics#5856)

* Add `--workers 8` argument to val.py (ultralytics#5857)

* Update val.py

Add an option to choose number of workers if not called by train.py

* Update comment

* 120 char line width

Co-authored-by: Glenn Jocher <[email protected]>

* Update `plot_lr_scheduler()` (ultralytics#5864)

shallow copy modify originals

* Update `nl` after `cutout()` (ultralytics#5873)

* `AutoShape()` models as `DetectMultiBackend()` instances (ultralytics#5845)

* Update AutoShape()

* autodownload ONNX

* Cleanup

* Finish updates

* Add Usage

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* fix device

* Update hubconf.py

* Update common.py

* smart param selection

* autodownload all formats

* autopad only pytorch models

* new_shape edits

* stride tensor fix

* Cleanup

* Single-command multiple-model export (ultralytics#5882)

* Export multiple models in series

Export multiple models in series by adding additional `*.pt` files to the `--weights` argument, i.e.:

```bash
python export.py --include tflite --weights yolov5n.pt  # export 1 model
python export.py --include tflite --weights yolov5n.pt yolov5s.pt yolov5m.pt yolov5l.pt yolov5x.pt  # export 5 models
```

* Update export.py

* Update README.md

* `Detections().tolist()` explicit argument fix (ultralytics#5907)

debugged for missigned Detections attributes

* Update wandb_utils.py (ultralytics#5908)

* Add *.engine (TensorRT extensions) to .gitignore (ultralytics#5911)

* Add *.engine (TensorRT extensions) to .gitignore

* Update .dockerignore

Co-authored-by: Glenn Jocher <[email protected]>

* Add ONNX inference providers (ultralytics#5918)

* Add ONNX inference providers

Fix for ultralytics#5916

* Update common.py

* Add hardware checks to `notebook_init()` (ultralytics#5919)

* Update notebook

* Update notebook

* update string

* update string

* Updates

* Updates

* Updates

* check both ipython and psutil

* remove sample_data if is_colab

* cleanup

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* Revert "Update `plot_lr_scheduler()` (ultralytics#5864)" (ultralytics#5920)

This reverts commit 360eec6.

* Absolute '/content/sample_data' (ultralytics#5922)

* Default PyTorch Hub to `autocast(False)` (ultralytics#5926)

* Fix ONNX opset inconsistency with parseargs and run args (ultralytics#5937)

* Make `select_device()` robust to `batch_size=-1` (ultralytics#5940)

* Find out a bug. When set batch_size = -1 to use the autobatch.

reproduce:

* Fix type conflict

Co-authored-by: Glenn Jocher <[email protected]>

* fix .gitignore not tracking existing folders (ultralytics#5946)

* fix .gitignore not tracking existing folders

fix .gitignore so that the files that are in the repository are actually being tracked.

Everything in the data/ folder is ignored, which also means the subdirectories are ignored. Fix so that the subdirectories and their contents are still tracked.

* Remove data/trainings

Co-authored-by: Glenn Jocher <[email protected]>

* Update `strip_optimizer()` (ultralytics#5949)

Replace 'training_result' with 'best_fitness' in strip_optimizer() to match key with ckpt from train.py

* Add nms and agnostic nms to export.py (ultralytics#5938)

* add nms and agnostic nms to export.py

* fix agnostic implies nms

* reorder args to group TF args

* PEP8 120 char

Co-authored-by: Glenn Jocher <[email protected]>

* Refactor NUM_THREADS (ultralytics#5954)

* Fix Detections class `tolist()` method (ultralytics#5945)

* Fix tolist() to add the file for each Detection

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* Fix PEP8 requirement for 2 spaces before an inline comment

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* Cleanup

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* Fix `imgsz` bug (ultralytics#5948)

* fix imgsz bug

* Update detect.py

Co-authored-by: Glenn Jocher <[email protected]>

* `pretrained=False` fix (ultralytics#5966)

* `pretriained=False` fix

Fix for ultralytics#5964

* CI speed improvement

* make parameter ignore epochs (ultralytics#5972)

* make parameter ignore epochs

ignore epochs functionality add to prevent spikes at the beginning when fitness spikes and decreases after.
Discussed at ultralytics#5971

* Update train.py

Co-authored-by: Glenn Jocher <[email protected]>

* YOLOv5s6 params and FLOPs fix (ultralytics#5977)

* Update callbacks.py with `__init__()` (ultralytics#5979)

Add __init__() function.

* Increase `ar_thr` from 20 to 100 for better detection on slender (high aspect ratio) objects (ultralytics#5556)

* Making `ar_thr` available as a hyperparameter

* Disabling ar_thr as hyperparameter and computing from the dataset instead

* Fixing bug in ar_thr computation

* Fix `ar_thr` to 100

* Allow `--weights URL` (ultralytics#5991)

* Recommend `jar xf file.zip` for zips (ultralytics#5993)

* *.torchscript inference `self.jit` fix (ultralytics#6007)

* Check TensorRT>=8.0.0 version (ultralytics#6021)

* Check TensorRT>=8.0.0 version

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* Multi-layer capable `--freeze` argument (ultralytics#6019)

* support specfiy multiple frozen layers

* fix bug

* Cleanup Freeze section

* Cleanup argument

Co-authored-by: Glenn Jocher <[email protected]>

* train -> val comment fix (ultralytics#6024)

* Add dataset source citations (ultralytics#6032)

* Kaggle `LOGGER` fix (ultralytics#6041)

* Simplify `set_logging()` indexing (ultralytics#6042)

* `--freeze` fix (ultralytics#6044)

Fix for ultralytics#6038

* OpenVINO Export (ultralytics#6057)

* OpenVINO export

* Remove timeout

* Add 3 files

* str

* Constrain opset to 12

* Default ONNX opset to 12

* Make dir

* Make dir

* Cleanup

* Cleanup

* check_requirements(('openvino-dev',))

* Reduce G/D/CIoU logic operations (ultralytics#6074)

Consider that the default value is CIOU，adjust the order of judgment could reduce the number of judgments.
And “elif CIoU:” didn't need 'if'.

Co-authored-by: 李杰 <[email protected]>

* Init tensor directly on device (ultralytics#6068)

Slightly more efficient than .to(device)

* W&B: track batch size after autobatch (ultralytics#6039)

* track batch size after autobatch

* remove redundant import

* Update __init__.py

* Update __init__.py

Co-authored-by: Glenn Jocher <[email protected]>

* W&B: Log best results after training ends (ultralytics#6120)

* log best.pt metrics at train end

* update

* Update __init__.py

Co-authored-by: Glenn Jocher <[email protected]>

* Log best results (ultralytics#6085)

* log best result in summary

* comment added

* add space for `flake8`

* log `best/epoch`

* fix `dimension` for epoch

ValueError: all the input arrays must have same number of dimensions

* log `best/` in `utils.logger.__init__`

* fix pre-commit

1. missing whitespace around operator
2.  over-indented

* Refactor/reduce G/C/D/IoU `if: else` statements (ultralytics#6087)

* Refactor the code to reduece else

* Update metrics.py

* Cleanup

Co-authored-by: Cmos <[email protected]>
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* Add EdgeTPU support (ultralytics#3630)

* Add models/tf.py for TensorFlow and TFLite export

* Set auto=False for int8 calibration

* Update requirements.txt for TensorFlow and TFLite export

* Read anchors directly from PyTorch weights

* Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export

* Remove check_anchor_order, check_file, set_logging from import

* Reformat code and optimize imports

* Autodownload model and check cfg

* update --source path, img-size to 320, single output

* Adjust representative_dataset

* Put representative dataset in tfl_int8 block

* detect.py TF inference

* weights to string

* weights to string

* cleanup tf.py

* Add --dynamic-batch-size

* Add xywh normalization to reduce calibration error

* Update requirements.txt

TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error

* Fix imports

Move C3 from models.experimental to models.common

* Add models/tf.py for TensorFlow and TFLite export

* Set auto=False for int8 calibration

* Update requirements.txt for TensorFlow and TFLite export

* Read anchors directly from PyTorch weights

* Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export

* Remove check_anchor_order, check_file, set_logging from import

* Reformat code and optimize imports

* Autodownload model and check cfg

* update --source path, img-size to 320, single output

* Adjust representative_dataset

* detect.py TF inference

* Put representative dataset in tfl_int8 block

* weights to string

* weights to string

* cleanup tf.py

* Add --dynamic-batch-size

* Add xywh normalization to reduce calibration error

* Update requirements.txt

TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error

* Fix imports

Move C3 from models.experimental to models.common

* implement C3() and SiLU()

* Add TensorFlow and TFLite Detection

* Add --tfl-detect for TFLite Detection

* Add int8 quantized TFLite inference in detect.py

* Add --edgetpu for Edge TPU detection

* Fix --img-size to add rectangle TensorFlow and TFLite input

* Add --no-tf-nms to detect objects using models combined with TensorFlow NMS

* Fix --img-size list type input

* Update README.md

* Add Android project for TFLite inference

* Upgrade TensorFlow v2.3.1 -> v2.4.0

* Disable normalization of xywh

* Rewrite names init in detect.py

* Change input resolution 640 -> 320 on Android

* Disable NNAPI

* Update README.me --img 640 -> 320

* Update README.me for Edge TPU

* Update README.md

* Fix reshape dim to support dynamic batching

* Fix reshape dim to support dynamic batching

* Add epsilon argument in tf_BN, which is different between TF and PT

* Set stride to None if not using PyTorch, and do not warmup without PyTorch

* Add list support in check_img_size()

* Add list input support in detect.py

* sys.path.append('./') to run from yolov5/

* Add int8 quantization support for TensorFlow 2.5

* Add get_coco128.sh

* Remove --no-tfl-detect in models/tf.py (Use tf-android-tfl-detect branch for EdgeTPU)

* Update requirements.txt

* Replace torch.load() with attempt_load()

* Update requirements.txt

* Add --tf-raw-resize to set half_pixel_centers=False

* Remove android directory

* Update README.md

* Update README.md

* Add multiple OS support for EdgeTPU detection

* Fix export and detect

* Export 3 YOLO heads with Edge TPU models

* Remove xywh denormalization with Edge TPU models in detect.py

* Fix saved_model and pb detect error

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* Fix pre-commit.ci failure

* Add edgetpu in export.py docstring

* Fix Edge TPU model detection exported by TF 2.7

* Add class names for TF/TFLite in DetectMultibackend

* Fix assignment with nl in TFLite Detection

* Add check when getting Edge TPU compiler version

* Add UTF-8 encoding in opening --data file for Windows

* Remove redundant TensorFlow import

* Add Edge TPU in export.py's docstring

* Add the detect layer in Edge TPU model conversion

* Default `dnn=False`

* Cleanup data.yaml loading

* Update detect.py

* Update val.py

* Comments and generalize data.yaml names

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* Enable AdamW optimizer (ultralytics#6152)

* Update export format docstrings (ultralytics#6151)

* Update export documentation

* Cleanup

* Update export.py

* Update README.md

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* Update README.md

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* Update train.py

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* Update greetings.yml (ultralytics#6165)

* [pre-commit.ci] pre-commit suggestions (ultralytics#6177)

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* Update NMS `max_wh=7680` for 8k images (ultralytics#6178)

* Add OpenVINO inference (ultralytics#6179)

* Ignore `*_openvino_model/` dir (ultralytics#6180)

* Global export format sort (ultralytics#6182)

* Global export sort

* Cleanup

* Fix TorchScript on mobile export (ultralytics#6183)

* fix export of TorchScript on mobile

* Cleanup

Co-authored-by: yinrong <[email protected]>
Co-authored-by: Glenn Jocher <[email protected]>

* TensorRT 7 `anchor_grid` compatibility fix (ultralytics#6185)

* fix: TensorRT 7 incompatiable

* Add comment

* Add if: else and comment

Co-authored-by: Glenn Jocher <[email protected]>

* Add `tensorrt>=7.0.0` checks (ultralytics#6193)

* Add `tensorrt>=7.0.0` checks

* Update export.py

* Update common.py

* Update export.py

* Add CoreML inference (ultralytics#6195)

* Add Apple CoreML inference

* Cleanup

* Fix `nan`-robust stream FPS (ultralytics#6198)

Fix for Webcam stop working suddenly (Issue ultralytics#6197)

* Edge TPU compiler comment (ultralytics#6196)

* Edge TPU compiler comment

* 7 to 8 fix

* TFLite `--int8` 'flatbuffers==1.12' fix (ultralytics#6216)

* TFLite `--int8` 'flatbuffers==1.12' fix

Temporary workaround for TFLite INT8 export.

* Update export.py

* Update export.py

* TFLite `--int8` 'flatbuffers==1.12' fix 2 (ultralytics#6217)

* TFLite `--int8` 'flatbuffers==1.12' fix 2

Reorganizes ultralytics#6216 fix to update before `tensorflow` import so no restart required.

* Update export.py

* Add `edgetpu_compiler` checks (ultralytics#6218)

* Add `edgetpu_compiler` checks

* Update export.py

* Update export.py

* Update export.py

* Update export.py

* Update export.py

* Update export.py

* Attempt `edgetpu-compiler` autoinstall (ultralytics#6223)

* Attempt `edgetpu-compiler` autoinstall

Attempt to install edgetpu-compiler dependency if missing on Linux.

* Update export.py

* Update export.py

* Update README speed reproduction command (ultralytics#6228)

* Update P2-P7 `models/hub` variants (ultralytics#6230)

* Update p2-p7 `models/hub` variants

* Update common.py

* AutoAnchor camelcase corrections

* TensorRT 7 export fix (ultralytics#6235)

* Fix `cmd` string on `tfjs` export (ultralytics#6243)

* Fix cmd string on tfjs export

* Cleanup

Co-authored-by: Glenn Jocher <[email protected]>

* TensorRT pip install

* Enable ONNX `--half` FP16 inference (ultralytics#6268)

* Enable ONNX ``--half` FP16 inference

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* Update `export.py` with Detect, Validate usages (ultralytics#6280)

* Add `is_kaggle()` function (ultralytics#6285)

* Add `is_kaggle()` function

Return True if environment is Kaggle Notebook.

* Remove root loggers only if is_kaggle() == True

* Update general.py

* Fix `device` count check (ultralytics#6290)

* Fix device count check()

* Update torch_utils.py

* Update torch_utils.py

* Update hubconf.py

* Fixing bug multi-gpu training (ultralytics#6299)

* Fixing bug multi-gpu training

This solves this issue: ultralytics#6297 (comment)

* Update torch_utils.py for pep8

* `select_device()` cleanup (ultralytics#6302)

* `select_device()` cleanup

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Fix `train.py` parameter groups desc error (ultralytics#6318)

* Fix `train.py` parameter groups desc error

* Cleanup

Co-authored-by: Glenn Jocher <[email protected]>

* Remove `dataset_stats()` autodownload capability (ultralytics#6303)

* Remove `dataset_stats()` autodownload capability

@kalenmike security update per Slack convo

* Update datasets.py

* Console corrupted -> corrupt (ultralytics#6338)

* Console corrupted -> corrupt 

Minor style changes.

* Update export.py

* TensorRT `assert im.device.type != 'cpu'` on export (ultralytics#6340)

* TensorRT `assert im.device.type != 'cpu'` on export

* Update export.py

* `export.py` return exported files/dirs (ultralytics#6343)

* `export.py` return exported files/dirs

* Path to str

* Created using Colaboratory

* `export.py` automatic `forward_export` (ultralytics#6352)

* `export.py` automatic `forward_export`

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* New environment variable `VERBOSE` (ultralytics#6353)

New environment variable `VERBOSE`

* Reuse `de_parallel()` rather than `is_parallel()` (ultralytics#6354)

* `DEVICE_COUNT` instead of `WORLD_SIZE` to calculate `nw` (ultralytics#6324)

* Flush callbacks when on `--evolve` (ultralytics#6374)

* log best.pt metrics at train end

* update

* Update __init__.py

* flush callbacks when using evolve

Co-authored-by: Glenn Jocher <[email protected]>

* FROM nvcr.io/nvidia/pytorch:21.12-py3 (ultralytics#6377)

* FROM nvcr.io/nvidia/pytorch:21.10-py3 (ultralytics#6379)

21.12 generates dockerhub errors so rolling back to 21.10 with latest pytorch install. Not sure if this torch install will work on non-GPU dockerhub autobuild so this is an experiment.

* Add `albumentations` to Dockerfile (ultralytics#6392)

* Add `stop_training=False` flag to callbacks (ultralytics#6365)

* New flag 'stop_training' in util.callbacks.Callbacks class to prematurely stop training from callback handler

* Removed most of the new  checks, leaving only the one after calling 'on_train_batch_end'

* Cleanup

Co-authored-by: Glenn Jocher <[email protected]>

* Add `detect.py` GIF video inference (ultralytics#6410)

* Add detect.py GIF video inference

* Cleanup

* Update `greetings.yaml` email address (ultralytics#6412)

* Update `greetings.yaml` email address

* Update greetings.yml

* Rename logger from 'utils.logger' to 'yolov5' (ultralytics#6421)

* Gave a more explicit name to the logger

* Cleanup

Co-authored-by: Glenn Jocher <[email protected]>

* Prefer `tflite_runtime` for TFLite inference if installed (ultralytics#6406)

* import tflite_runtime if tensorflow not installed

* rename tflite to tfli

* Attempt tflite_runtime for all TFLite workflows

Also rename tfli to tfl

Co-authored-by: Glenn Jocher <[email protected]>

* Update workflows (ultralytics#6427)

* Workflow updates

* quotes fix

* best to weights fix

* Namespace `VERBOSE` env variable to `YOLOv5_VERBOSE` (ultralytics#6428)

* Verbose updates

* Verbose updates

* Add `*.asf` video support (ultralytics#6436)

* Revert "Remove `dataset_stats()` autodownload capability (ultralytics#6303)" (ultralytics#6442)

This reverts commit 3119b2f.

* Fix `select_device()` for Multi-GPU (ultralytics#6434)

* Fix `select_device()` for Multi-GPU

Possible fix for ultralytics#6431

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Update torch_utils.py

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Fix2 `select_device()` for Multi-GPU (ultralytics#6461)

* Fix2 select_device() for Multi-GPU

* Cleanup

* Cleanup

* Simplify error message

* Improve assert

* Update torch_utils.py

* Add Product Hunt social media icon (ultralytics#6464)

* Social media icons update

* fix URL

* Update README.md

* Resolve dataset paths (ultralytics#6489)

* Simplify TF normalized to pixels (ultralytics#6494)

* Improved `export.py` usage examples (ultralytics#6495)

* Improved `export.py` usage examples

* Cleanup

* CoreML inference fix `list()` -> `sorted()` (ultralytics#6496)

* Suppress `torch.jit.TracerWarning` on export (ultralytics#6498)

* Suppress torch.jit.TracerWarning

TracerWarnings can be safely ignored.

* Cleanup

* Suppress export.run() TracerWarnings (ultralytics#6499)

Suppresses warnings when calling export.run() directly, not just CLI python export.py.

Also adds Requirements examples for CPU and GPU backends

* W&B: Remember batchsize on resuming (ultralytics#6512)

* log best.pt metrics at train end

* update

* Update __init__.py

* flush callbacks when using evolve

* remember batch size on resuming

* Update train.py

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* Update hyp.scratch-high.yaml (ultralytics#6525)

Update `lrf: 0.1`, tested on YOLOv5x6 to 55.0 [email protected]:0.95, slightly higher than current.

* TODO issues exempt from stale action (ultralytics#6530)

* Update val_batch*.jpg for Chinese fonts (ultralytics#6526)

* Update plots for Chinese fonts

* make is_chinese() non-str safe

* Add global FONT

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* Update general.py

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* Social icons after text (ultralytics#6473)

* Social icons after text

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* Update README.md

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* Edge TPU compiler `sudo` fix (ultralytics#6531)

* Edge TPU compiler sudo fix

Allows for auto-install of Edge TPU compiler on non-sudo systems like the YOLOv5 Docker image.

@kalenmike

* Update export.py

* Update export.py

* Update export.py

* Edge TPU export 'list index out of range' fix (ultralytics#6533)

* Edge TPU `tf.lite.experimental.load_delegate` fix (ultralytics#6536)

* Edge TPU `tf.lite.experimental.load_delegate` fix

Fix attempt for ultralytics#6535

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* Fixing minor multi-streaming issues with TensoRT engine (ultralytics#6504)

* Update batch-size in model.warmup() + indentation for logging inference results

* These changes are in response to PR comments

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Load checkpoint on CPU instead of on GPU (ultralytics#6516)

* Load checkpoint on CPU instead of on GPU

* refactor: simplify code

* Cleanup

* Update train.py

Co-authored-by: Glenn Jocher <[email protected]>

* flake8: code meanings (ultralytics#6481)

* Fix 6 Flake8 issues (ultralytics#6541)

* F541

* F821

* F841

* E741

* E302

* E722

* Apply suggestions from code review

* Update general.py

* Update datasets.py

* Update export.py

* Update plots.py

* Update plots.py

Co-authored-by: Glenn Jocher <[email protected]>

* Edge TPU TF imports fix (ultralytics#6542)

* Edge TPU TF imports fix

Fix for ultralytics#6535 (comment)

* Update common.py

* Move trainloader functions to class methods (ultralytics#6559)

* Move trainloader functions to class methods

* results = ThreadPool(NUM_THREADS).imap(self.load_image, range(n))

* Cleanup

* Improved AutoBatch DDP error message (ultralytics#6568)

* Improved AutoBatch DDP error message

* Cleanup

* Fix zero-export handling with `if any(f):` (ultralytics#6569)

* Fix zero-export handling with `if any(f):`

Partial fix for ultralytics#6563

* Cleanup

* Fix `plot_labels()` colored histogram bug (ultralytics#6574)

* Fix `plot_labels()` colored histogram bug

* Cleanup

* Allow custom` --evolve` project names (ultralytics#6567)

* Update train.py

As see in ultralytics#6463, modification on train in evolve process to allow custom save directory.

* fix val

* PEP8

whitespace around operator

* Cleanup

Co-authored-by: Glenn Jocher <[email protected]>

* Add `DATASETS_DIR` global in general.py (ultralytics#6578)

* return `opt` from `train.run()` (ultralytics#6581)

* Fix YouTube dislike button bug in `pafy` package (ultralytics#6603)

Per ultralytics#6583 (comment) by @alicera

* Update train.py

* Fix `hyp_evolve.yaml` indexing bug (ultralytics#6604)

* Fix `hyp_evolve.yaml` indexing bug

Bug caused hyp_evolve.yaml to display latest generation result rather than best generation result.

* Update plots.py

* Update general.py

* Update general.py

* Update general.py

* Fix `ROOT / data` when running W&B `log_dataset()` (ultralytics#6606)

* Fix missing data folder when running log_dataset

* Use ROOT/'data'

* PEP8 whitespace

* YouTube dependency fix `youtube_dl==2020.12.2` (ultralytics#6612)

Per ultralytics#5860 (comment) by @hdnh2006

* Add YOLOv5n to Reproduce section (ultralytics#6619)

* W&B: Improve resume stability (ultralytics#6611)

* log best.pt metrics at train end

* update

* Update __init__.py

* flush callbacks when using evolve

* remember batch size on resuming

* Update train.py

* improve stability of resume

Co-authored-by: Glenn Jocher <[email protected]>

* W&B: don't log media in evolve (ultralytics#6617)

* YOLOv5 Export Benchmarks (ultralytics#6613)

* Add benchmarks.py

* Update

* Add requirements

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* dataset autodownload from root

* Update

* Redirect to /dev/null

* sudo --help

* Cleanup

* Add exports pd df

* Updates

* Updates

* Updates

* Cleanup

* dir handling fix

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Cleanup

* Cleanup2

* Cleanup3

* Cleanup model_type

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Fix ConfusionMatrix scale `vmin=0.0` (ultralytics#6638)

Fix attempt for ultralytics#6626

* Fixed wandb logger KeyError (ultralytics#6637)

* Fix yolov3.yaml remove list (ultralytics#6655)

Per ultralytics/yolov3#1887 (comment)

* Validate with 2x `--workers` (ultralytics#6658)

* Validate with 2x `--workers` single-GPU/CPU fix (ultralytics#6659)

Fix for ultralytics#6658 for single-GPU and CPU training use cases

* Add `--cache val` (ultralytics#6663)

New `--cache val` argument will cache validation set only into RAM. Should help multi-GPU training speeds without consuming as much RAM as full `--cache ram`.

* Robust `scipy.cluster.vq.kmeans` too few points (ultralytics#6668)

* Handle `scipy.cluster.vq.kmeans` too few points

Resolves ultralytics#6664

* Update autoanchor.py

* Cleanup

* Update Dockerfile `torch==1.10.2+cu113` (ultralytics#6669)

* FROM nvcr.io/nvidia/pytorch:22.01-py3 (ultralytics#6670)

* FROM nvcr.io/nvidia/pytorch:21.10-py3 (ultralytics#6671)

22.10 returns 'no space left on device' error message.

Seems like a bug at docker. Raised issue in docker/hub-feedback#2209

* Update Dockerfile reorder installs (ultralytics#6672)

Also `nvidia-tensorboard-plugin-dlprof`, `nvidia-tensorboard` are no longer installed in NVCR base.

* FROM nvcr.io/nvidia/pytorch:21.10-py3 (ultralytics#6673)

Reordered installation may help reduce resource usage in autobuild

* FROM nvcr.io/nvidia/pytorch:21.10-py3 (ultralytics#6677)

Revert to 21.10 on autobuild fail

* Fix TF exports >= 2GB (ultralytics#6292)

* Fix exporting saved_model: pb exceeds 2GB

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Replace TF v1.x API with TF v2.x API for saved_model export

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Clean up

* Remove lambda in tf.function()

* Revert "Remove lambda in tf.function()" to be compatible with TF v2.4

This reverts commit 46c7931f11dfdea6ae340c77287c35c30b9e0779.

* Fix for pre-commit.ci

* Cleanup1

* Cleanup2

* Backwards compatibility update

* Update common.py

* Update common.py

* Cleanup3

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <[email protected]>

* Fix `--evolve --bucket gs://...` (ultralytics#6698)

* Fix CoreML P6 inference (ultralytics#6700)

* Fix CoreML P6 inference

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Fix floating point in number of workers `nw` (ultralytics#6701)

Integer division by a float yields a (rounded) float. This causes
the dataloader to crash when creating a range.

* Edge TPU inference fix (ultralytics#6686)

* refactor: use edgetpu flag

* fix: remove bitwise and assignation to tflite

* Cleanup and fix tflite

* Cleanup

Co-authored-by: Glenn Jocher <[email protected]>

* Use `export_formats()` in export.py (ultralytics#6705)

* Use `export_formats()` in export.py

* list fix

* Suppress `torch` AMP-CPU warnings (ultralytics#6706)

This is a torch bug, but they seem unable or unwilling to fix it so I'm creating a suppression in YOLOv5. 

Resolves ultralytics#6692

* Update `nw` to `max(nd, 1)` (ultralytics#6714)

* GH: add PR template (ultralytics#6482)

* GH: add PR template

* Update CONTRIBUTING.md

* Update PULL_REQUEST_TEMPLATE.md

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md

Co-authored-by: Glenn Jocher <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Switch default LR scheduler from cos to linear (ultralytics#6729)

* Switch default LR scheduler from cos to linear

Based on empirical results of training both ways on all YOLOv5 models.

* linear bug fix

* Updated VOC hyperparameters (ultralytics#6732)

* Update hyps

* Update hyp.VOC.yaml

* Update pathlib

* Update hyps

* Update hyps

* Update hyps

* Update hyps

* YOLOv5 v6.1 release (ultralytics#6739)

* Pre-commit table fix (ultralytics#6744)

* Update tutorial.ipynb (2 CPUs, 12.7 GB RAM, 42.2/166.8 GB disk) (ultralytics#6767)

* Update min warmup iterations from 1k to 100 (ultralytics#6768)

* Default `OMP_NUM_THREADS=8` (ultralytics#6770)

* Update tutorial.ipynb (ultralytics#6771)

* Update hyp.VOC.yaml (ultralytics#6772)

* Fix export for 1-channel images (ultralytics#6780)

Export failed for 1-channel input shape, 1-liner fix

* Update EMA decay `tau` (ultralytics#6769)

* Update EMA

* Update EMA

* ratio invert

* fix ratio invert

* fix2 ratio invert

* warmup iterations to 100

* ema_k

* implement tau

* implement tau

* YOLOv5s6 params FLOPs fix (ultralytics#6782)

* Update PULL_REQUEST_TEMPLATE.md (ultralytics#6783)

* Update autoanchor.py (ultralytics#6794)

* Update autoanchor.py

* Update autoanchor.py

* Update sweep.yaml (ultralytics#6825)

* Update sweep.yaml

Changed focal loss gamma search range between 1 and 4

* Update sweep.yaml

lowered the min value to match default

* AutoAnchor improved initialization robustness (ultralytics#6854)

* Update AutoAnchor

* Update AutoAnchor

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Add `*.ts` to `VID_FORMATS` (ultralytics#6859)

* Update `--cache disk` deprecate `*_npy/` dirs (ultralytics#6876)

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Updates

* Cleanup

* Cleanup

* Update yolov5s.yaml (ultralytics#6865)

* Update yolov5s.yaml

* Update yolov5s.yaml

Co-authored-by: Glenn Jocher <[email protected]>

* Default FP16 TensorRT export (ultralytics#6798)

* Assert engine precision ultralytics#6777

* Default to FP32 inputs for TensorRT engines

* Default to FP16 TensorRT exports ultralytics#6777

* Remove wrong line ultralytics#6777

* Automatically adjust detect.py input precision ultralytics#6777

* Automatically adjust val.py input precision ultralytics#6777

* Add missing colon

* Cleanup

* Cleanup

* Remove default trt_fp16_input definition

* Experiment

* Reorder detect.py if statement to after half checks

* Update common.py

* Update export.py

* Cleanup

Co-authored-by: Glenn Jocher <[email protected]>

* Bump actions/setup-python from 2 to 3 (ultralytics#6880)

Bumps [actions/setup-python](https://github.com/actions/setup-python) from 2 to 3.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](actions/setup-python@v2...v3)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>

Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Bump actions/checkout from 2 to 3 (ultralytics#6881)

Bumps [actions/checkout](https://github.com/actions/checkout) from 2 to 3.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](actions/checkout@v2...v3)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>

Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Fix TRT `max_workspace_size` deprecation notice (ultralytics#6856)

* Fix TRT `max_workspace_size` deprecation notice

* Update export.py

* Update export.py

* Update bytes to GB with bitshift (ultralytics#6886)

* Move `git_describe()` to general.py (ultralytics#6918)

* Move `git_describe()` to general.py

* Move `git_describe()` to general.py

* PyTorch 1.11.0 compatibility updates (ultralytics#6932)

Resolves `AttributeError: 'Upsample' object has no attribute 'recompute_scale_factor'` first raised in ultralytics#5499

* Optimize PyTorch 1.11.0 compatibility update (ultralytics#6933)

* Allow 3-point segments (ultralytics#6938)

May resolve ultralytics#6931

* Fix PyTorch Hub export inference shapes (ultralytics#6949)

May resolve ultralytics#6947

* DetectMultiBackend() `--half` handling (ultralytics#6945)

* DetectMultiBackend() `--half` handling

* CI fixes

* rename .half to .fp16 to avoid conflict

* warmup fix

* val update

* engine update

* engine update

* Update Dockerfile `torch==1.11.0+cu113` (ultralytics#6954)

* New val.py `cuda` variable (ultralytics#6957)

* New val.py `cuda` variable

Fix for ONNX GPU val.

* Update val.py

* DetectMultiBackend() return `device` update (ultralytics#6958)

Fixes ONNX validation that returns outputs on CPU.

* Tensor initialization on device improvements (ultralytics#6959)

* Update common.py speed improvements

Eliminate .to() ops where possible for reduced data transfer overhead. Primarily affects warmup and PyTorch Hub inference.

* Updates

* Updates

* Update detect.py

* Update val.py

* EdgeTPU optimizations (ultralytics#6808)

* removed transpose op for better edgetpu support

* fix for training case

* enabled experimental new quantizer flag

* precalculate add and mul ops at compile time

Co-authored-by: Glenn Jocher <[email protected]>

* Model `ema` key backward compatibility fix (ultralytics#6972)

Fix for older model loading issue in ultralytics@d3d9cbc#commitcomment-68622388

* pt model to cpu on TF export

* YOLOv5 Export Benchmarks for GPU (ultralytics#6963)

* Add benchmarks.py GPU support

* Updates

* Updates

* Updates

* Updates

* Add --half

* Add TRT requirements

* Cleanup

* Add TF to warmup types

* Update export.py

* Update export.py

* Update benchmarks.py

* Update TQDM bar format (ultralytics#6988)

* Conditional `Timeout()` by OS (disable on Windows) (ultralytics#7013)

* Conditional `Timeout()` by OS (disable on Windows)

* Update general.py

* fix: add default PIL font as fallback  (ultralytics#7010)

* fix: add default font as fallback

Add default font as fallback if the downloading of the Arial.ttf font
fails for some reason, e.g. no access to public internet.

* Update plots.py

Co-authored-by: Maximilian Strobel <[email protected]>
Co-authored-by: Glenn Jocher <[email protected]>

* Consistent saved_model output format (ultralytics#7032)

* `ComputeLoss()` indexing/speed improvements (ultralytics#7048)

* device as class attribute

* Update loss.py

* Update loss.py

* improve zeros

* tensor split

* Update Dockerfile to `git clone` instead of `COPY` (ultralytics#7053)

Resolves git command errors that currently happen in image, i.e.:

```bash
root@382ae64aeca2:/usr/src/app# git pull
Warning: Permanently added the ECDSA host key for IP address '140.82.113.3' to the list of known hosts.
[email protected]: Permission denied (publickey).
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.
```

* Create SECURITY.md (ultralytics#7054)

* Create SECURITY.md

Resolves ultralytics#7052

* Move into ./github

* Update SECURITY.md

* Fix incomplete URL substring sanitation (ultralytics#7056)

Resolves code scanning alert in ultralytics#7055

* Use PIL to eliminate chroma subsampling in crops (ultralytics#7008)

* use pillow to save higher-quality jpg (w/o color subsampling)

* Cleanup and doc issue

Co-authored-by: Glenn Jocher <[email protected]>

* Fix `check_anchor_order()` in pixel-space not grid-space (ultralytics#7060)

* Update `check_anchor_order()`

Use mean area per output layer for added stability.

* Check in pixel-space not grid-space fix

* Update detect.py non-inplace with `y.tensor_split()` (ultralytics#7062)

* Update common.py lists for tuples (ultralytics#7063)

Improved profiling.

* Update W&B message to `LOGGER.info()` (ultralytics#7064)

* Update __init__.py (ultralytics#7065)

* Add non-zero `da` `check_anchor_order()` condition (ultralytics#7066)

* Fix2 `check_anchor_order()` in pixel-space not grid-space (ultralytics#7067)

Follows ultralytics#7060 which provided only a partial solution to this issue. ultralytics#7060 resolved occurences in yolo.py, this applies the same fix in autoanchor.py.

* Revert "Update detect.py non-inplace with `y.tensor_split()` (ultralytics#7062)" (ultralytics#7074)

This reverts commit d5e363f.

* Update loss.py with `if self.gr < 1:` (ultralytics#7087)

* Update loss.py with `if self.gr < 1:`

* Update loss.py

* Update loss for FP16 `tobj` (ultralytics#7088)

* Update model summary to display model name (ultralytics#7101)

* `torch.split()` 1.7.0 compatibility fix (ultralytics#7102)

* Update loss.py

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update loss.py

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Update benchmarks significant digits (ultralytics#7103)

* Model summary `pathlib` fix (ultralytics#7104)

Stems not working correctly for YOLOv5l with current .rstrip() implementation. After fix:
```
YOLOv5l summary: 468 layers, 46563709 parameters, 46563709 gradients, 109.3 GFLOPs
```

* Remove named arguments where possible (ultralytics#7105)

* Remove named arguments where possible

Speed improvements.

* Update yolo.py

* Update yolo.py

* Update yolo.py

* Multi-threaded VisDrone and VOC downloads (ultralytics#7108)

* Multi-threaded VOC download

* Update VOC.yaml

* Update

* Update general.py

* Update general.py

* `np.fromfile()` Chinese image paths fix (ultralytics#6979)

* 🎉 🆕 now can read Chinese image path. 

use "cv2.imdecode(np.fromfile(f, np.uint8), cv2.IMREAD_COLOR)" instead of "cv2.imread(f)" for Chinese image path.

* Update datasets.py

* Update __init__.py

Co-authored-by: Glenn Jocher <[email protected]>

* Add PyTorch Hub `results.save(labels=False)` option (ultralytics#7129)

Resolves ultralytics#388 (comment)

* SparseML integration

* Add SparseML dependancy

* Update: add missing files

* Update requirements.txt

* Update: sparseml-nightly support

* Update: remove model versioning

* Partial update for multi-stage recipes

* Update: multi-stage recipe support

* Update: remove sparseml dep

* Fix: multi-stage recipe handeling

* Fix: multi stage support

* Fix: non-recipe runs

* Add: legacy hyperparam files

* Fix: add copy-paste to hyps

* Fix: nit

* apply structure fixes

* Squashed rebase to v6.1 upstream

* Update SparseML Integration to V6.1 (#26)

* SparseML integration

* Add SparseML dependancy

* Update: add missing files

* Update requirements.txt

* Update: sparseml-nightly support

* Update: remove model versioning

* Partial update for multi-stage recipes

* Update: multi-stage recipe support

* Update: remove sparseml dep

* Fix: multi-stage recipe handeling

* Fix: multi stage support

* Fix: non-recipe runs

* Add: legacy hyperparam files

* Fix: add copy-paste to hyps

* Fix: nit

* apply structure fixes

* manager fixes

* Update function name

Co-authored-by: Konstantin <[email protected]>
Co-authored-by: Konstantin Gulin <[email protected]>

Author: bfineran

.dockerignore

@@ -8,17 +8,23 @@ coco
 storage.googleapis.com
 
 data/samples/*
-**/results*.txt
+**/results*.csv
 *.jpg
 
 # Neural Network weights -----------------------------------------------------------------------------------------------
-**/*.weights
 **/*.pt
 **/*.pth
 **/*.onnx
+**/*.engine
 **/*.mlmodel
 **/*.torchscript
-
+**/*.torchscript.pt
+**/*.tflite
+**/*.h5
+**/*.pb
+*_saved_model/
+*_web_model/
+*_openvino_model/
 
 # Below Copied From .gitignore -----------------------------------------------------------------------------------------
 # Below Copied From .gitignore -----------------------------------------------------------------------------------------

.github/ISSUE_TEMPLATE/bug-report.md

@@ -0,0 +1,85 @@
+name: 🐛 Bug Report
+# title: " "
+description: Problems with YOLOv5
+labels: [bug, triage]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thank you for submitting a YOLOv5 🐛 Bug Report!
+
+  - type: checkboxes
+    attributes:
+      label: Search before asking
+      description: >
+        Please search the [issues](https://github.com/ultralytics/yolov5/issues) to see if a similar bug report already exists.
+      options:
+        - label: >
+            I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and found no similar bug report.
+          required: true
+
+  - type: dropdown
+    attributes:
+      label: YOLOv5 Component
+      description: |
+        Please select the part of YOLOv5 where you found the bug.
+      multiple: true
+      options:
+        - "Training"
+        - "Validation"
+        - "Detection"
+        - "Export"
+        - "PyTorch Hub"
+        - "Multi-GPU"
+        - "Evolution"
+        - "Integrations"
+        - "Other"
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Bug
+      description: Provide console output with error messages and/or screenshots of the bug.
+      placeholder: |
+        💡 ProTip! Include as much information as possible (screenshots, logs, tracebacks etc.) to receive the most helpful response.
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Environment
+      description: Please specify the software and hardware you used to produce the bug.
+      placeholder: |
+        - YOLO: YOLOv5 🚀 v6.0-67-g60e42e1 torch 1.9.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)
+        - OS: Ubuntu 20.04
+        - Python: 3.9.0
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Minimal Reproducible Example
+      description: >
+        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 [minimal reproducible example](https://stackoverflow.com/help/minimal-reproducible-example).
+      placeholder: |
+        ```
+        # Code to reproduce your issue here
+        ```
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Additional
+      description: Anything else you would like to share?
+
+  - type: checkboxes
+    attributes:
+      label: Are you willing to submit a PR?
+      description: >
+        (Optional) We encourage you to submit a [Pull Request](https://github.com/ultralytics/yolov5/pulls) (PR) to help improve YOLOv5 for everyone, especially if you have a good understanding of how to implement a fix or feature.
+        See the YOLOv5 [Contributing Guide](https://github.com/ultralytics/yolov5/blob/master/CONTRIBUTING.md) to get started.
+      options:
+        - label: Yes I'd like to help by submitting a PR!

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -0,0 +1,8 @@
+blank_issues_enabled: true
+contact_links:
+  - name: Slack
+    url: https://join.slack.com/t/ultralytics/shared_invite/zt-w29ei8bp-jczz7QYUmDtgo6r6KcMIAg
+    about: Ask on Ultralytics Slack Forum
+  - name: Stack Overflow
+    url: https://stackoverflow.com/search?q=YOLOv5
+    about: Ask on Stack Overflow with 'YOLOv5' tag

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,50 @@
+name: 🚀 Feature Request
+description: Suggest a YOLOv5 idea
+# title: " "
+labels: [enhancement]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thank you for submitting a YOLOv5 🚀 Feature Request!
+
+  - type: checkboxes
+    attributes:
+      label: Search before asking
+      description: >
+        Please search the [issues](https://github.com/ultralytics/yolov5/issues) to see if a similar feature request already exists.
+      options:
+        - label: >
+            I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and found no similar feature requests.
+          required: true
+
+  - type: textarea
+    attributes:
+      label: Description
+      description: A short description of your feature.
+      placeholder: |
+        What new feature would you like to see in YOLOv5?
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Use case
+      description: |
+        Describe the use case of your feature request. It will help us understand and prioritize the feature request.
+      placeholder: |
+        How would this feature be used, and who would use it?
+
+  - type: textarea
+    attributes:
+      label: Additional
+      description: Anything else you would like to share?
+
+  - type: checkboxes
+    attributes:
+      label: Are you willing to submit a PR?
+      description: >
+        (Optional) We encourage you to submit a [Pull Request](https://github.com/ultralytics/yolov5/pulls) (PR) to help improve YOLOv5 for everyone, especially if you have a good understanding of how to implement a fix or feature.
+        See the YOLOv5 [Contributing Guide](https://github.com/ultralytics/yolov5/blob/master/CONTRIBUTING.md) to get started.
+      options:
+        - label: Yes I'd like to help by submitting a PR!

.github/ISSUE_TEMPLATE/feature-request.md

@@ -0,0 +1,33 @@
+name: ❓ Question
+description: Ask a YOLOv5 question
+# title: " "
+labels: [question]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thank you for asking a YOLOv5 ❓ Question!
+
+  - type: checkboxes
+    attributes:
+      label: Search before asking
+      description: >
+        Please search the [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) to see if a similar question already exists.
+      options:
+        - label: >
+            I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) and found no similar questions.
+          required: true
+
+  - type: textarea
+    attributes:
+      label: Question
+      description: What is your question?
+      placeholder: |
+        💡 ProTip! Include as much information as possible (screenshots, logs, tracebacks etc.) to receive the most helpful response.
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Additional
+      description: Anything else you would like to share?

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -0,0 +1,9 @@
+<!--
+Thank you for submitting a YOLOv5 🚀 Pull Request! We want to make contributing to YOLOv5 as easy and transparent as possible. A few tips to get you started:
+
+- Search existing YOLOv5 [PRs](https://github.com/ultralytics/yolov5/pull) to see if a similar PR already exists.
+- Link this PR to a YOLOv5 [issue](https://github.com/ultralytics/yolov5/issues) to help us understand what bug fix or feature is being implemented.
+- Provide before and after profiling/inference/training results to help us quantify the improvement your PR provides (if applicable).
+
+Please see our ✅ [Contributing Guide](https://github.com/ultralytics/yolov5/blob/master/CONTRIBUTING.md) for more details.
+-->

.github/ISSUE_TEMPLATE/question.md

@@ -0,0 +1,7 @@
+# Security Policy
+
+We aim to make YOLOv5 🚀 as secure as possible! If you find potential vulnerabilities or have any concerns please let us know so we can investigate and take corrective action if needed.
+
+### Reporting a Vulnerability
+
+To report vulnerabilities please email us at [email protected] or visit https://ultralytics.com/contact. Thank you!