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Update sweep.yaml #6825

Merged
merged 2 commits into from
Mar 4, 2022
Merged

Update sweep.yaml #6825

merged 2 commits into from
Mar 4, 2022

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lcombaldieu
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@lcombaldieu lcombaldieu commented Mar 2, 2022

Changed focal loss gamma search range between 1 and 4. Values between 0 and 0.1 yield no results.

🛠️ PR Summary

Made with ❤️ by Ultralytics Actions

🌟 Summary

Adjustment to hyperparameter sweep range in YOLOv5's Weights & Biases configuration.

📊 Key Changes

  • Increased the maximum value of the fl_gamma hyperparameter from 0.1 to 4.0 in the Weights & Biases sweep configuration.

🎯 Purpose & Impact

  • 🎛️ This change allows for a broader exploration of the fl_gamma parameter when running hyperparameter sweeps, potentially leading to better model performance.
  • 🧠 It could help in discovering new optimal settings during automated hyperparameter tuning, which may improve object detection results for users.
  • 🚀 Users leveraging Weights & Biases for hyperparameter tuning will experience more versatile sweep configurations, enhancing the opportunity for model optimization.

Changed focal loss gamma search range between 1 and 4
@glenn-jocher
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@lcombaldieu this doesn't make any sense. You'd be introducing a lower bound that is much higher than the default value.

lowered the min value to match default
@lcombaldieu
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lcombaldieu commented Mar 3, 2022

You are right @glenn-jocher, I lowered the min value to 0, however high values of gamma should be explored as explained in most paper about focal loss, the usual value for gamma is 2. Values as high as 5 can be explored in very imbalanced datasets
image

@glenn-jocher glenn-jocher merged commit bcc92e2 into ultralytics:master Mar 4, 2022
@glenn-jocher
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@lcombaldieu got it! Thanks for the reference, yes you are correct we should allow a higher maximum. PR is merged. Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐

@lcombaldieu
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@glenn-jocher quick update : focal loss gamma is the most important parameter in my sweeps, with values <1 diverging every time. Hopes this can help you achieve even higher accuracy on COCO.
image

@glenn-jocher
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@lcombaldieu your results don't extrapolate to common datasets, as COCO training converges without issue at the default fl_gamma value of 0.0

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@lcombaldieu

fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)

bfineran added a commit to neuralmagic/yolov5 that referenced this pull request Apr 8, 2022
* Fix TensorRT potential unordered binding addresses (ultralytics#5826)

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* fix: enforce binding addresses order

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* new_shape edits

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```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
```

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This reverts commit 360eec6.

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

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reproduce:

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* fix .gitignore not tracking existing folders

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

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* Remove data/trainings

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

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

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* Fix `imgsz` bug (ultralytics#5948)

* fix imgsz bug

* Update detect.py

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* CI speed improvement

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1. missing whitespace around operator
2.  over-indented

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TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error

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* Fix --img-size list type input

* Update README.md

* Add Android project for TFLite inference

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* Update README.me for Edge TPU

* Update README.md

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* Add get_coco128.sh

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

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* Replace torch.load() with attempt_load()

* Update requirements.txt

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* Remove android directory

* Update README.md

* Update README.md

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* 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 assignment with nl in TFLite Detection

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

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* Enable AdamW optimizer (ultralytics#6152)

* Update export format docstrings (ultralytics#6151)

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* Update greetings.yml (ultralytics#6165)

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* Add `tensorrt>=7.0.0` checks

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* Update common.py

* Update export.py

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

Temporary workaround for TFLite INT8 export.

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* Update export.py

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

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

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

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* 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

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

New environment variable `VERBOSE`

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* 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.

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

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

* Cleanup

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

* Add detect.py GIF video inference

* Cleanup

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* 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

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

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

Update `lrf: 0.1`, tested on YOLOv5x6 to 55.0 mAP@0.5:0.95, 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

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

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* Update general.py

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* Social icons after text (ultralytics#6473)

* Social icons after text

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

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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

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* 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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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

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* Cleanup

* Cleanup2

* Cleanup3

* Cleanup model_type

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* 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

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

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

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* 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

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

* Fix CoreML P6 inference (ultralytics#6700)

* Fix CoreML P6 inference

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* 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 <glenn.jocher@ultralytics.com>

* 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

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* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md

* Update PULL_REQUEST_TEMPLATE.md

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* 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

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* 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

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* 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

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* 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
...

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* 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)

---
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* 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

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* 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 <Maximilian.Strobel@infineon.com>
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* 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.
git@github.com: 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

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* 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

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* 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

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* 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 <konstantin@neuralmagic.com>
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KSGulin added a commit to neuralmagic/yolov5 that referenced this pull request Apr 14, 2022
* 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 <glenn.jocher@ultralytics.com>

* 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

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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
```

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@kalenmike security update per Slack convo

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This reverts commit 3119b2f.

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* Update export.py

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

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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

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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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>
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

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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 <glenn.jocher@ultralytics.com>

* 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 <glenn.jocher@ultralytics.com>

* 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] <support@github.com>

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] <support@github.com>

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 <glenn.jocher@ultralytics.com>

* 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 <Maximilian.Strobel@infineon.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* 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.
git@github.com: 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 <glenn.jocher@ultralytics.com>

* 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

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* 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 <glenn.jocher@ultralytics.com>

* 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 <konstantin@neuralmagic.com>
Co-authored-by: Konstantin Gulin <66528950+KSGulin@users.noreply.github.com>
BjarneKuehl pushed a commit to fhkiel-mlaip/yolov5 that referenced this pull request Aug 26, 2022
* Update sweep.yaml

Changed focal loss gamma search range between 1 and 4

* Update sweep.yaml

lowered the min value to match default
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