* 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 <glenn.jocher@ultralytics.com>

* 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

* Update AutoShape()

* autodownload ONNX

* Cleanup

* Finish updates

* Add Usage

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* fix device

* Update hubconf.py

* Update common.py

* smart param selection

* autodownload all formats

* autopad only pytorch models

* new_shape edits

* stride tensor fix

* Cleanup

* feat: change file suffix in pythonic way

* fix: enforce binding addresses order

* fix: enforce binding addresses order

* fix path error in export.py

* Update export.py

updated!

* Update export.py

oops forget something

* Fix float zeros format

* 255 to integer

* Update `set_logging()`

* Update export.py

* pre-commit fixes

* Update LoadImages

* Update LoadStreams

* Update print_args

* Single LOGGER definition

* yolo.py fix

Co-authored-by: pre-commit <pre-commit@example.com>

* use os.path.relpath instead of relative_to

* use os.path.relpath instead of relative_to

* Remove os.path from val.py

* Remove os.path from train.py

* Update detect.py import to os

* Update export.py import to os

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

* Allow YOLOv5 execution from arbitrary `cwd`

* Fix str bugs

* Add arguments to TensorFlow NMS call

* Add regex substitution to reorder Identity_*

* Delete reorder in docstring

* Cleanup

* Cleanup2

* Removed `+ \` on string ends (not needed)

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

* Update `sys.path.append(str(ROOT))`

* Cleanup

* Refactor argparser printing to `print_args()`

* Cleanup

* Add fused conv support

* Set all saved_model values to non trainable

* Fix TFLite fp16 model export

* Fix int8 TFLite conversion

* added callbacks

* added back callback to main

* added save_dir to callback output

* merged in upstream

* removed ghost code

* added url check

* Add url2file()

* Update file-only

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

* Add `--int8` argument

* parents[0] bug fix

* Fix order

* Initial commit

* Remove unused export_torchscript return

* ROOT variable

* Add prefix to fcn arg

* fix ROOT

* check_yaml into run()

* interim fixes

* imgsz=(320, 320)

* Hardcode tf_raw_resize False

* Finish opt elimination

* Update representative_dataset_gen()

* Update export.py with TF methods

* SiLU and GraphDef fixes

* file_size() directory handling feature

* export fixes

* add lambda: to representative_dataset

* Detect training False default

* Fuse false for TF models

* Embed agnostic NMS arguments

* Remove lambda

* TensorFlow.js export success

* Add pb to Usage

* Add *_tfjs_model/ to ignore files

* prepend YOLOv5 to function headers

* Remove end --- comments

* parameterize tfjs export pb file

* update run() data default /ROOT

* update --include help

* update imports

* return ct_model

* Consolidate TFLite export

* pb prerequisite to tfjs

* TF modules CamelCase

* Remove exports from tf.py and cleanup

* pass agnostic NMS arguments

* CI

* CI

* ignore *_web_model/

* Add tensorflow to CI dependencies

* CI tensorflow-cpu

* Update requirements.txt

* Remove tensorflow check_requirement

* CI coreml tfjs

* export only onnx torchscript

* reorder exports torchscript first

* Changed onnx-simplifier check behavior

Export.py has been updated to check for onnx-simplifier requirement only when the --simplify argument is added.
Allows for better flexibility and one less requirement if simplify is not needed.

* Fix single-element tuples

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

* `check_requirements(('coremltools',))`

* Update ci-testing.yml

* Update ci-testing.yml

* Implement new headers

* Reformat 1

* Reformat 2

* Reformat 3 - math

* Reformat 4 - yaml

* Add cache-on-disk and cache-directory to cache images on disk

* Fix load_image with cache_on_disk

* Add no_cache flag for load_image

* Revert the parts('logging' and a new line) that do not need to be modified

* Add the assertion for shapes of cached images

* Add a suffix string for cached images

* Fix boundary-error of letterbox for load_mosaic

* Add prefix as cache-key of cache-on-disk

* Update cache-function on disk

* Add psutil in requirements.txt

* Update train.py

* Cleanup1

* Cleanup2

* Skip existing npy

* Include re-space

* Export return character fix

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

* Addition refactor `export.py`

* Update export.py

* Refactor `export.py`

* cleanup

* Update check_requirements()

* Update export.py

* Add yolov5/ to path

* rename functions to run()

* cleanup

* rename fix

* CI fix

* cleanup find models/export.py

* Update DDP for `torch.distributed.run`

* Add LOCAL_RANK

* remove opt.local_rank

* backend="gloo|nccl"

* print

* print

* debug

* debug

* os.getenv

* gloo

* gloo

* gloo

* cleanup

* fix getenv

* cleanup

* cleanup destroy

* try nccl

* return opt

* add --local_rank

* add timeout

* add init_method

* gloo

* move destroy

* move destroy

* move print(opt) under if RANK

* destroy only RANK 0

* move destroy inside train()

* restore destroy outside train()

* update print(opt)

* cleanup

* nccl

* gloo with 60 second timeout

* update namespace printing

* Slightly modify CLI execution

This simple change makes it easier to run the primary functions of this
repo (train/detect/test) from within Python. An object which represents
`opt` can be constructed and fed to the `main` function of each of these
modules, rather than having to call the lower level functions directly,
or run the module as a script.

* Update export.py

Add CLI parsing update for more convenient module usage within Python.

Co-authored-by: Lewis Belcher <lb@desupervised.io>

* Refactor models/export.py arguments

* cleanup

* cleanup

* early assert for cpu and half option

early assert for cpu and half option

* Modified comment

Modified comment

* call model.eval() when opt.train is False

call model.eval() when opt.train is False

* single-line if statement

* cleanup

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

* Add output names & dynamic axes for onnx export

Add output_names and dynamic_axes names for all outputs in torch.onnx.export. The first four outputs of the model will have names output0, output1, output2, output3

* use first output only + cleanup

Co-authored-by: Samridha Shrestha <samridha.shrestha@g42.ai>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Check CoreML models.train() mode

* Update export.py