Revert unintentional change to test batch sizes caused by PR https://github.com/ultralytics/yolov5/pull/2125

* Update tensorboard>=2.4.1 

Update tensorboard version to attempt to address https://github.com/ultralytics/yolov5/issues/2573 (tensorboard logging fail in Docker image).

* cleanup

Exclude non-critical packages from dependency checks in detect.py. pycocotools and thop in particular are not required for inference.

Issue first raised in https://github.com/ultralytics/yolov5/issues/1944 and also raised in https://github.com/ultralytics/yolov5/discussions/2556

Fix for results.tolist() method breaking after YOLOv5 Hub profiling PRshttps://github.com/ultralytics/yolov5/pull/2460 https://github.com/ultralytics/yolov5/pull/2459 and

* Init Commit

* new wandb integration

* Update

* Use data_dict in test

* Updates

* Update: scope of log_img

* Update: scope of log_img

* Update

* Update: Fix logging conditions

* Add tqdm bar, support for .txt dataset format

* Improve Result table Logger

* Init Commit

* new wandb integration

* Update

* Use data_dict in test

* Updates

* Update: scope of log_img

* Update: scope of log_img

* Update

* Update: Fix logging conditions

* Add tqdm bar, support for .txt dataset format

* Improve Result table Logger

* Add dataset creation in training script

* Change scope: self.wandb_run

* Add wandb-artifact:// natively

you can now use --resume with wandb run links

* Add suuport for logging dataset while training

* Cleanup

* Fix: Merge conflict

* Fix: CI tests

* Automatically use wandb config

* Fix: Resume

* Fix: CI

* Enhance: Using val_table

* More resume enhancement

* FIX : CI

* Add alias

* Get useful opt config data

* train.py cleanup

* Cleanup train.py

* more cleanup

* Cleanup| CI fix

* Reformat using PEP8

* FIX:CI

* rebase

* remove uneccesary changes

* remove uneccesary changes

* remove uneccesary changes

* remove unecessary chage from test.py

* FIX: resume from local checkpoint

* FIX:resume

* FIX:resume

* Reformat

* Performance improvement

* Fix local resume

* Fix local resume

* FIX:CI

* Fix: CI

* Imporve image logging

* (:(:Redo CI tests:):)

* Remember epochs when resuming

* Remember epochs when resuming

* Update DDP location

Potential fix for #2405

* PEP8 reformat

* 0.25 confidence threshold

* reset train.py plots syntax to previous

* reset epochs completed syntax to previous

* reset space to previous

* remove brackets

* reset comment to previous

* Update: is_coco check, remove unused code

* Remove redundant print statement

* Remove wandb imports

* remove dsviz logger from test.py

* Remove redundant change from test.py

* remove redundant changes from train.py

* reformat and improvements

* Fix typo

* Add tqdm tqdm progress when scanning files, naming improvements

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

Fix for https://github.com/ultralytics/yolov5/issues/2394

* Be able to create dataset from annotated images only

Add the ability to create a dataset/splits only with images that have an annotation file, i.e a .txt file, associated to it. As we talked about this, the absence of a txt file could mean two things:

* either the image wasn't yet labelled by someone,
* either there is no object to detect.

When it's easy to create small datasets, when you have to create datasets with thousands of images (and more coming), it's hard to track where you at and you don't want to wait to have all of them annotated before starting to train. Which means some images would lack txt files and annotations, resulting in label inconsistency as you say in #2313. By adding the annotated_only argument to the function, people could create, if they want to, datasets/splits only with images that were labelled, for sure.

* Cleanup and update print()

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

Set HOME environment variable per Binder requirements. 
https://github.com/binder-examples/minimal-dockerfile

* Avoid mutable state in Detect

* LoadImages() pathlib update (#2140)

* Unique *.cache filenames fix (#2134)

* fix #2121

* Update test.py

* Update train.py

* Update autoanchor.py

* Update datasets.py

* Update log_dataset.py

* Update datasets.py

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

* Update train.py test batch_size (#2148)

* Update train.py

* Update loss.py

* Update train.py (#2149)

* Linear LR scheduler option (#2150)

* Linear LR scheduler option

* Update train.py

* Update data-autodownload background tasks (#2154)

* Update get_coco.sh

* Update get_voc.sh

* Update detect.py (#2167)

Without this cv2.imshow opens a window but nothing is visible

* Update requirements.txt (#2173)

* Update utils/datasets.py to support .webp files (#2174)

Simply added 'webp' as an image format to the img_formats array so that webp image files can be used as training data.

* Changed socket port and added timeout (#2176)

* PyTorch Hub results.save('path/to/dir') (#2179)

* YOLOv5 Segmentation Dataloader Updates (#2188)

* Update C3 module

* Update C3 module

* Update C3 module

* Update C3 module

* update

* update

* update

* update

* update

* update

* update

* update

* update

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* update

* update

* update

* update

* updates

* updates

* updates

* updates

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update datasets

* update

* update

* update

* update attempt_downlaod()

* merge

* merge

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* parameterize eps

* comments

* gs-multiple

* update

* max_nms implemented

* Create one_cycle() function

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* GitHub API rate limit fix

* update

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* ComputeLoss

* astuple

* epochs

* update

* update

* ComputeLoss()

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* merge

* merge

* merge

* merge

* update

* update

* update

* update

* commit=tag == tags[-1]

* Update cudnn.benchmark

* update

* update

* update

* updates

* updates

* updates

* updates

* updates

* updates

* updates

* update

* update

* update

* update

* update

* mosaic9

* update

* update

* update

* update

* update

* update

* institute cache versioning

* only display on existing cache

* reverse cache exists booleans

* Created using Colaboratory

* YOLOv5 PyTorch Hub results.save() method retains filenames (#2194)

* save results with name

* debug

* save original imgs names

* Update common.py

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

* TTA augument boxes one pixel shifted in de-flip ud and lr (#2219)

* TTA augument boxes one pixel shifted in de-flip ud and lr

* PEP8 reformat

Co-authored-by: Jaap van de Loosdrecht <jaap.van.de.loosdrecht@nhlstenden.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* LoadStreams() frame loss bug fix (#2222)

* Update yolo.py channel array (#2223)

* Add check_imshow() (#2231)

* Add check_imshow()

* Update general.py

* Update general.py

* Update CI badge (#2230)

* Add isdocker() (#2232)

* Add isdocker()

* Update general.py

* Update general.py

* YOLOv5 Hub URL inference bug fix (#2250)

* Update common.py

* Update common.py

* Update common.py

* Improved hubconf.py CI tests (#2251)

* Unified hub and detect.py box and labels plotting (#2243)

* reset head

* Update inference default to multi_label=False (#2252)

* Update inference default to multi_label=False

* bug fix

* Update plots.py

* Update plots.py

* Robust objectness loss balancing (#2256)

* Created using Colaboratory

* Update minimum stride to 32 (#2266)

* Dynamic ONNX engine generation (#2208)

* add: dynamic onnx export

* delete: test onnx inference

* fix dynamic output axis

* Code reduction

* fix: dynamic output axes, dynamic input naming

* Remove fixed axes

Co-authored-by: Shivam Swanrkar <ss8464@nyu.edu>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update greetings.yml for auto-rebase on PR (#2272)

* Update Dockerfile with apt install zip (#2274)

* FLOPS min stride 32 (#2276)

Signed-off-by: xiaowo1996 <429740343@qq.com>

* Update README.md

* Amazon AWS EC2 startup and re-startup scripts (#2185)

* Amazon AWS EC2 startup and re-startup scripts

* Create resume.py

* cleanup

* Amazon AWS EC2 startup and re-startup scripts (#2282)

* Update train.py (#2290)

* Update train.py

* Update train.py

* Update train.py

* Update train.py

* Create train.py

* Improved model+EMA checkpointing (#2292)

* Enhanced model+EMA checkpointing

* update

* bug fix

* bug fix 2

* always save optimizer

* ema half

* remove model.float()

* model half

* carry ema/model in fp32

* rm model.float()

* both to float always

* cleanup

* cleanup

* Improved model+EMA checkpointing 2 (#2295)

* Fix labels being missed when image extension appears twice in filename (#2300)

* W&B entity support (#2298)

* W&B entity support

* shorten wandb_entity to entity

Co-authored-by: Jan Hajek <jan.hajek@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Avoid mutable state in Detect

* Update yolo and remove .to(device)

Co-authored-by: Oleg Boiko <oboiko@chegg.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: train255 <thanhdd.it@gmail.com>
Co-authored-by: ab-101 <56578530+ab-101@users.noreply.github.com>
Co-authored-by: Transigent <wbdsmith@optusnet.com.au>
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
Co-authored-by: Daniel Khromov <danielkhromov@gmail.com>
Co-authored-by: VdLMV <jaap@vdlmv.nl>
Co-authored-by: Jaap van de Loosdrecht <jaap.van.de.loosdrecht@nhlstenden.com>
Co-authored-by: Yann Defretin <kinoute@gmail.com>
Co-authored-by: Aditya Lohia <64709773+aditya-dl@users.noreply.github.com>
Co-authored-by: Shivam Swanrkar <ss8464@nyu.edu>
Co-authored-by: xiaowo1996 <429740343@qq.com>
Co-authored-by: Iden Craven <iden.craven@gmail.com>
Co-authored-by: Jan Hajek <toretak@users.noreply.github.com>
Co-authored-by: Jan Hajek <jan.hajek@gmail.com>