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YOLOv5 v6.1 release #6739

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merged 1 commit into from
Feb 22, 2022
Merged

YOLOv5 v6.1 release #6739

merged 1 commit into from
Feb 22, 2022

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@glenn-jocher glenn-jocher commented Feb 22, 2022

YOLOv5 v6.1 - TensorRT, TensorFlow Edge TPU and OpenVINO Export and Inference

This release incorporates new features and bug fixes (271 PRs from 48 contributors) since our last release in October 2021. It adds TensorRT, Edge TPU and OpenVINO support, and provides retrained models at --batch-size 128 with new default one-cycle linear LR scheduler. YOLOv5 now officially supports 11 different formats, not just for export but for inference (both detect.py and PyTorch Hub), and validation to profile mAP and speed results after export.

Format export.py --include Model
PyTorch - yolov5s.pt
TorchScript torchscript yolov5s.torchscript
ONNX onnx yolov5s.onnx
OpenVINO openvino yolov5s_openvino_model/
TensorRT engine yolov5s.engine
CoreML coreml yolov5s.mlmodel
TensorFlow SavedModel saved_model yolov5s_saved_model/
TensorFlow GraphDef pb yolov5s.pb
TensorFlow Lite tflite yolov5s.tflite
TensorFlow Edge TPU edgetpu yolov5s_edgetpu.tflite
TensorFlow.js tfjs yolov5s_web_model/

Usage examples (ONNX shown):

Export:          python export.py --weights yolov5s.pt --include onnx
Detect:          python detect.py --weights yolov5s.onnx
PyTorch Hub:     model = torch.hub.load('ultralytics/yolov5', 'custom', 'yolov5s.onnx')
Validate:        python val.py --weights yolov5s.onnx
Visualize:       https://netron.app

Important Updates

New Results

All model trainings logged to https://wandb.ai/glenn-jocher/YOLOv5_v61_official

YOLOv5-P5 640 Figure (click to expand)

Figure Notes (click to expand)
  • COCO AP val denotes [email protected]:0.95 metric measured on the 5000-image COCO val2017 dataset over various inference sizes from 256 to 1536.
  • GPU Speed measures average inference time per image on COCO val2017 dataset using a AWS p3.2xlarge V100 instance at batch-size 32.
  • EfficientDet data from google/automl at batch size 8.
  • Reproduce by python val.py --task study --data coco.yaml --iou 0.7 --weights yolov5n6.pt yolov5s6.pt yolov5m6.pt yolov5l6.pt yolov5x6.pt

Example YOLOv5l before and after metrics:

YOLOv5l
Large
size
(pixels)
mAPval
0.5:0.95
mAPval
0.5
Speed
CPU b1
(ms)
Speed
V100 b1
(ms)
Speed
V100 b32
(ms)
params
(M)
FLOPs
@640 (B)
v5.0 640 48.2 66.9 457.9 11.6 2.8 47.0 115.4
v6.0 (previous) 640 48.8 67.2 424.5 10.9 2.7 46.5 109.1
v6.1 (this release) 640 49.0 67.3 424.5 10.9 2.7 46.5 109.1

Pretrained Checkpoints

Model size
(pixels)
mAPval
0.5:0.95
mAPval
0.5
Speed
CPU b1
(ms)
Speed
V100 b1
(ms)
Speed
V100 b32
(ms)
params
(M)
FLOPs
@640 (B)
YOLOv5n 640 28.0 45.7 45 6.3 0.6 1.9 4.5
YOLOv5s 640 37.4 56.8 98 6.4 0.9 7.2 16.5
YOLOv5m 640 45.4 64.1 224 8.2 1.7 21.2 49.0
YOLOv5l 640 49.0 67.3 430 10.1 2.7 46.5 109.1
YOLOv5x 640 50.7 68.9 766 12.1 4.8 86.7 205.7
YOLOv5n6 1280 36.0 54.4 153 8.1 2.1 3.2 4.6
YOLOv5s6 1280 44.8 63.7 385 8.2 3.6 16.8 12.6
YOLOv5m6 1280 51.3 69.3 887 11.1 6.8 35.7 50.0
YOLOv5l6 1280 53.7 71.3 1784 15.8 10.5 76.8 111.4
YOLOv5x6
+ TTA
1280
1536
55.0
55.8
72.7
72.7
3136
-
26.2
-
19.4
-
140.7
-
209.8
-
Table Notes (click to expand)
  • All checkpoints are trained to 300 epochs with default settings. Nano and Small models use hyp.scratch-low.yaml hyps, all others use hyp.scratch-high.yaml.
  • mAPval values are for single-model single-scale on COCO val2017 dataset.
    Reproduce by python val.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65
  • Speed averaged over COCO val images using a AWS p3.2xlarge instance. NMS times (~1 ms/img) not included.
    Reproduce by python val.py --data coco.yaml --img 640 --task speed --batch 1
  • TTA Test Time Augmentation includes reflection and scale augmentations.
    Reproduce by python val.py --data coco.yaml --img 1536 --iou 0.7 --augment

Changelog

Changes between previous release and this release: v6.0...v6.1
Changes since this release: v6.1...HEAD

New Features and Bug Fixes (271)
New Contributors (48)

Full Changelog: v6.0...v6.1

🛠️ PR Summary

Made with ❤️ by Ultralytics Actions

🌟 Summary

Update to README with new benchmark images and hyperparameter settings.

📊 Key Changes

  • Replaced benchmark result images with updated ones.
  • Updated model performance statistics for various YOLOv5 models.
  • Adjusted documentation regarding hyperparameters used for different YOLOv5 models.

🎯 Purpose & Impact

  • Provide Up-to-Date Visuals: Easier comparison of model performance with current benchmark images. 🖼️
  • Reflect Model Optimizations: Users are informed about the latest model accuracy and speed, helping them choose the right model for their needs. ⚖️
  • Clarify Training Details: Clearer guidance on the hyperparameters used for training different model sizes, leading to better reproducibility and understanding of training setups. 📝

Potentially, these updates could enhance users' trust in the YOLOv5 project by showcasing improvements and maintaining transparency around training processes. 🛠️

@glenn-jocher glenn-jocher self-assigned this Feb 22, 2022
@glenn-jocher glenn-jocher added the documentation Improvements or additions to documentation label Feb 22, 2022
@glenn-jocher glenn-jocher merged commit 3752807 into master Feb 22, 2022
@glenn-jocher glenn-jocher deleted the release/v6.1 branch February 22, 2022 11:35
eladc-git pushed a commit to eladc-git/yolov5 that referenced this pull request Mar 10, 2022
bfineran added a commit to neuralmagic/yolov5 that referenced this pull request Apr 8, 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.

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* Update val.py

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

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

* Update comment

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* 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

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* Update hubconf.py

* Update common.py

* smart param selection

* autodownload all formats

* autopad only pytorch models

* new_shape edits

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* 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

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* Add ONNX inference providers (ultralytics#5918)

* Add ONNX inference providers

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* Update common.py

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

* Update notebook

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* check both ipython and psutil

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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.

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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

* 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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* 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)

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* Cleanup Freeze section

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

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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'.

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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

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* log best result in summary

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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

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* Add list input support in detect.py

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* Add get_coco128.sh

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* Cleanup data.yaml loading

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* Enable AdamW optimizer (ultralytics#6152)

* Update export format docstrings (ultralytics#6151)

* Update export documentation

* Cleanup

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* Update README.md

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* Update README.md

* Update README.md

* Update README.md

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* Update greetings.yml (ultralytics#6165)

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

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* Add comment

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

* Add `tensorrt>=7.0.0` checks

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* Update common.py

* Update export.py

* Add CoreML inference (ultralytics#6195)

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

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

Temporary workaround for TFLite INT8 export.

* Update export.py

* Update export.py

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

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

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* Attempt `edgetpu-compiler` autoinstall

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

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Return True if environment is Kaggle Notebook.

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* Fix device count check()

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* Fixing bug multi-gpu training

This solves this issue: ultralytics#6297 (comment)

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* `select_device()` cleanup

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* 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`

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

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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

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

* 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

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

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* Update general.py

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

* 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

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

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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 <[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

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* 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

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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

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

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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 <[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

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* 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

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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

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]>

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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

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

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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

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* 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.

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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

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* fix: enforce binding addresses order

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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.

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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
```

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Consider that the default value is CIOU,adjust the order of judgment could reduce the number of judgments.
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* Add get_coco128.sh

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* Replace torch.load() with attempt_load()

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* Enable AdamW optimizer (ultralytics#6152)

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

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

* Add `tensorrt>=7.0.0` checks

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* Add CoreML inference (ultralytics#6195)

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

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

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* Update export.py

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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)

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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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* Cleanup

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* Update `greetings.yaml` email address

* Update greetings.yml

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* Verbose updates

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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

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TracerWarnings can be safely ignored.

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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 <[email protected]>

* 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

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

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* Update general.py

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

* 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

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

* 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

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

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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

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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 <[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

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* 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

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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

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

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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 <[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

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* 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

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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

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

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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 <[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]>
BjarneKuehl pushed a commit to fhkiel-mlaip/yolov5 that referenced this pull request Aug 26, 2022
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