d3ea0df8b9
New YOLOv5 Classification Models ( #8956 )
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* Update
* Logger step fix: Increment step with epochs (#8654 )
* enhance
* revert
* allow training from scratch
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* Update --img argument from train.py
single line
* fix image size from 640 to 128
* suport custom dataloader and augmentation
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* format
* Update dataloaders.py
* Single line return, single line comment, remove unused argument
* address PR comments
* fix spelling
* don't augment eval set
* use fstring
* update augmentations.py
* new maning convention for transforms
* reverse if statement, inline ops
* reverse if statement, inline ops
* updates
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* update dataloaders
* Remove additional if statement
* Remove is_train as redundant
* Cleanup
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* Update classifier.py
* Update augmentations.py
* fix: imshow clip warning
* update
* Revert ToTensorV2 removal
* Update classifier.py
* Update normalize values, revert uint8
* normalize image using cv2
* remove dedundant comment
* Update classifier.py
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* 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
* Allow logging models from GenericLogger (#8676 )
* enhance
* revert
* allow training from scratch
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Update --img argument from train.py
single line
* fix image size from 640 to 128
* suport custom dataloader and augmentation
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* format
* Update dataloaders.py
* Single line return, single line comment, remove unused argument
* address PR comments
* fix spelling
* don't augment eval set
* use fstring
* update augmentations.py
* new maning convention for transforms
* reverse if statement, inline ops
* reverse if statement, inline ops
* updates
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* update dataloaders
* Remove additional if statement
* Remove is_train as redundant
* Cleanup
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* Cleanup2
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* Update classifier.py
* Update augmentations.py
* fix: imshow clip warning
* update
* Revert ToTensorV2 removal
* Update classifier.py
* Update normalize values, revert uint8
* normalize image using cv2
* remove dedundant comment
* Update classifier.py
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* replace print with logger
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* support final model logging
* update
* update
* update
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* remove curses
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* Update
* Update
* Update
* Update
* Update dataset download
* Update dataset download
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Pass imgsz to classify_transforms()
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Cos scheduler
* Cos scheduler
* Remove unused args
* Update
* Add seed
* Add seed
* Update
* Update
* Add run(), main()
* Merge master
* Merge master
* Update
* Update
* Update
* Update
* Update
* Update
* Update
* Create YOLOv5 BaseModel class (#8829 )
* Create BaseModel
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* fix
* Hub load device fix
* Update
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* Add experiment
* Merge master
* Attach names
* weight decay = 1e-4
* weight decay = 5e-5
* update smart_optimizer console printout
* fashion-mnist fix
* Merge master
* Update Table
* Update Table
* Remove destroy process group
* add kwargs to forward()
* fuse fix for resnet50
* nc, names fix for resnet50
* nc, names fix for resnet50
* ONNX CPU inference fix
* revert
* cuda
* if augment or visualize
* if augment or visualize
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* New smart_inference_mode()
* Update README
* Refactor into /classify dir
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* reset defaults
* reset defaults
* fix gpu predict
* warmup
* ema half fix
* spacing
* remove data
* remove cache
* remove denormalize
* save run settings
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* verbose false on initial plots
* new save_yaml() function
* Update ci-testing.yml
* Path(data) CI fix
* Separate classification CI
* fix val
* fix val
* fix val
* smartCrossEntropyLoss
* skip validation on hub load
* autodownload with working dir root
* str(data)
* Dataset usage example
* im_show normalize
* im_show normalize
* add imagenet simple names to multibackend
* Add validation speeds
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* 24-space names
* Update bash scripts
* Update permissions
* Add bash script arguments
* remove verbose
* TRT data fix
* names generator fix
* optimize if names
* update usage
* Add local loading
* Verbose=False
* update names printing
* Add Usage examples
* Add Usage examples
* Add Usage examples
* Add Usage examples
* named_children
* reshape_classifier_outputs
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* update
* update
* fix CI
* fix incorrect class substitution
* fix incorrect class substitution
* remove denormalize
* ravel fix
* cleanup
* update opt file printing
* update opt file printing
* update defaults
* add opt to checkpoint
* Add warning
* Add comment
* plot half bug fix
* Use NotImplementedError
* fix export shape report
* Fix TRT load
* cleanup CI
* profile comment
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Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2022-08-17 11:59:01 +02:00
42812fcb18
Add bash script arguments ( #8962 )
2022-08-14 22:33:55 +02:00
487edd5609
Dataset autodownload fstring updates
2022-05-31 12:36:20 +02:00
b53917de8d
Remove `tqdm.auto` ( #7599 )
2022-04-26 15:00:01 -07:00
5783de26fe
Objects365 dataset breakdown images vs zips ( #7335 )
2022-04-07 16:12:44 +02:00
0ca85ed65f
Update Objects365.yaml ( #7323 )
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Updated dataset size to 712GB (includes undeleted zips).
2022-04-06 23:52:19 +02:00
32661f75ac
Add `retry=3` to `download()` ( #7313 )
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* Add `retry=3` to `download()`
* Update general.py
* Update general.py
* Update general.py
* Update VOC.yaml
* Update VisDrone.yaml
2022-04-06 13:12:41 +02:00
f735458987
Use `tqdm.auto` ( #7311 )
2022-04-06 12:20:24 +02:00
741fac815e
fix: disable usage of root logger ( #7296 )
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* fix: disable usage of root logger
`logging.basicConfig` configures Python's root logger. This prohibits
fine control of logging, overwrites logging configuration done outside
the package, and is not best practice. Instead, the used logger is now
configured directly, and the root logger is untouched.
Example:
If yolov5 is used as part of another project with some sophisticated
logging, the internal `logging.basicConfig` call overwrites all the
external configuration.
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2022-04-05 17:38:13 +02:00
c759bbdf19
Add `check_requirements(('pycocotools>=2.0',))` ( #7295 )
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Add `check_requirements(('pycocotools>=2.0',))`
2022-04-05 15:55:16 +02:00
b1300f3e0b
Add dataset sizes (zipped) ( #7293 )
2022-04-05 15:14:54 +02:00
5f97001ed4
Context manager `open(file) as f` fixes ( #7289 )
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* Flask context manager `open()` fix
* Additional read context manager fixes
2022-04-05 12:54:25 +02:00
c3ae4e4af6
Multi-threaded VisDrone and VOC downloads ( #7108 )
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* Multi-threaded VOC download
* Update VOC.yaml
* Update
* Update general.py
* Update general.py
2022-03-23 01:19:37 +01:00
cea994b3f6
Update hyp.VOC.yaml ( #6772 )
2022-02-25 00:14:17 +01:00
2692e67c5f
Updated VOC hyperparameters ( #6732 )
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* Update hyps
* Update hyp.VOC.yaml
* Update pathlib
* Update hyps
* Update hyps
* Update hyps
* Update hyps
2022-02-22 12:11:18 +01:00
19e0208fc9
Update hyp.scratch-high.yaml ( #6525 )
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Update `lrf: 0.1`, tested on YOLOv5x6 to 55.0 mAP@0.5:0.95, slightly higher than current.
2022-02-03 12:15:13 +01:00
26f0415287
Add dataset source citations ( #6032 )
2021-12-19 15:19:04 +01:00
abbdd4802e
train -> val comment fix ( #6024 )
2021-12-17 16:43:00 +01:00
628817dfae
Recommend `jar xf file.zip` for zips ( #5993 )
2021-12-15 17:19:19 +01:00
3883261143
New `DetectMultiBackend()` class ( #5549 )
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* New `DetectMultiBackend()` class
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* pb to pt fix
* Cleanup
* explicit apply_classifier path
* Cleanup2
* Cleanup3
* Cleanup4
* Cleanup5
* Cleanup6
* val.py MultiBackend inference
* warmup fix
* to device fix
* pt fix
* device fix
* Val cleanup
* COCO128 URL to assets
* half fix
* detect fix
* detect fix 2
* remove half from DetectMultiBackend
* training half handling
* training half handling 2
* training half handling 3
* Cleanup
* Fix CI error
* Add torchscript _extra_files
* Add TorchScript
* Add CoreML
* CoreML cleanup
* New `DetectMultiBackend()` class
* pb to pt fix
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Cleanup
* explicit apply_classifier path
* Cleanup2
* Cleanup3
* Cleanup4
* Cleanup5
* Cleanup6
* val.py MultiBackend inference
* warmup fix
* to device fix
* pt fix
* device fix
* Val cleanup
* COCO128 URL to assets
* half fix
* detect fix
* detect fix 2
* remove half from DetectMultiBackend
* training half handling
* training half handling 2
* training half handling 3
* Cleanup
* Fix CI error
* Add torchscript _extra_files
* Add TorchScript
* Add CoreML
* CoreML cleanup
* revert default to pt
* Add Usage examples
* Cleanup val
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2021-11-09 16:45:02 +01:00
ed887b5976
Add pre-commit CI actions ( #4982 )
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* define pre-commit
* add CI code
* configure
* apply pre-commit
* fstring
* apply MD
* pre-commit
* Update torch_utils.py
* Update print strings
* notes
* Cleanup code-format.yml
* Update setup.cfg
* Update .pre-commit-config.yaml
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2021-10-28 18:35:01 +02:00
fee83c1634
Weights download script minor improvements ( #5213 )
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* Add nano model to the download list
* Add possibility to also download the "*6" models
* Cleanup
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-10-23 14:20:26 +02:00
13f7275555
Update/inplace ops ( #5233 )
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* Clip Objects365 autodownload labels (#5214 )
Fixes out of bounds labels that seem to affect ~10% of images in dataset.
* Inplace ops
2021-10-18 14:24:48 +02:00
0000334a6f
Update Objects365.yaml val count ( #5212 )
2021-10-15 12:40:40 -07:00
fc3606420d
Update Objects365.yaml to include the official validation set ( #5194 )
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* Update Objects365.yaml
Download the official Objects365 validation set and convert the labels
* Enforce 4-space indent, reformat and cleanup
* shorten list comprehension
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-10-14 20:48:47 -07:00
1c9f710b46
Add hyp.scratch-med.yaml ( #5196 )
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* Add hyp.scratch-med.yaml
* Update hyp.scratch-med.yaml
2021-10-14 20:40:30 -07:00
956be8e642
YOLOv5 release v6.0 ( #5141 )
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* Update P5 models
* Update P6 models
* Update with GFLOPs and Params
* Update with GFLOPs and Params
* Update README
* Update
* Update README
* Update
* Update
* Add times
* Update README
* Update results
* Update results
* Update results
* Update hyps
* Update plots
* Update plots
* Update README.md
* Add nano models to hubconf.py
2021-10-11 23:47:18 -07:00
1492632796
Fix zipfile name for coco128-segments ( #4914 )
2021-09-25 06:43:24 -07:00
24bea5e4b7
Standardize headers and docstrings ( #4417 )
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* Implement new headers
* Reformat 1
* Reformat 2
* Reformat 3 - math
* Reformat 4 - yaml
2021-08-14 21:17:51 +02:00
3e7c59ad3b
Fix rename `utils.google_utils` to `utils.downloads` ( #4393 )
2021-08-11 23:40:47 +02:00
b60b62e874
PyCharm reformat ( #4209 )
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* PyCharm reformat
* YAML reformat
* Markdown reformat
2021-07-28 23:35:14 +02:00
5d66e48723
Train from `--data path/to/dataset.zip` feature ( #4185 )
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* Train from `--data path/to/dataset.zip` feature
* Update dataset_stats()
* cleanup
* cleanup2
2021-07-28 02:04:10 +02:00
3fef11706c
Update comments header ( #4184 )
2021-07-27 23:23:41 +02:00
0ad6301c96
Update script headers ( #4163 )
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* Update download script headers
* cleanup
* bug fix attempt
* bug fix attempt2
* bug fix attempt3
* cleanup
2021-07-26 15:23:33 +02:00
f8e11483df
Update dataset headers ( #4162 )
2021-07-26 14:23:43 +02:00
c6c88dc601
Copy-Paste augmentation for YOLOv5 ( #3845 )
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* Copy-paste augmentation initial commit
* if any segments
* Add obscuration rejection
* Add copy_paste hyperparameter
* Update comments
2021-07-01 00:35:04 +02:00
8e7f285051
Fix datasets for aws and get_coco.sh ( #3788 )
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* merge master
* Update get_coco.sh
2021-06-26 15:29:16 +02:00
bd581b330b
Create hyp.scratch-p6.yaml ( #3787 )
2021-06-26 15:13:06 +02:00
f89941711c
NGA xView 2018 Dataset Auto-Download ( #3775 )
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* update clip_coords for numpy
* uncomment
* cleanup
* Add autosplits
* fix
* cleanup
2021-06-26 00:49:05 +02:00
f79d7479da
Add optional dataset.yaml `path` attribute ( #3753 )
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* Add optional dataset.yaml `path` attribute
@KalenMike
* pass locals to python scripts
* handle lists
* update coco128.yaml
* Capitalize first letter
* add test key
* finalize GlobalWheat2020.yaml
* finalize objects365.yaml
* finalize SKU-110K.yaml
* finalize SKU-110K.yaml
* finalize VisDrone.yaml
* NoneType fix
* update download comment
* voc to VOC
* update
* update VOC.yaml
* update VOC.yaml
* remove dashes
* delete get_voc.sh
* force coco and coco128 to ../datasets
* Capitalize Argoverse_HD.yaml
* Capitalize Objects365.yaml
* update Argoverse_HD.yaml
* coco segments fix
* VOC single-thread
* update Argoverse_HD.yaml
* update data_dict in test handling
* create root
2021-06-25 01:25:03 +02:00
fdc22398fa
Create `data/hyps` directory ( #3747 )
2021-06-23 12:49:38 +02:00
ac34834563
Update download_weights.sh comment ( #3662 )
2021-06-17 16:21:10 +02:00
2754adad46
Remove `/weights` directory ( #3659 )
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* Remove `/weights` directory
* cleanup
2021-06-17 14:44:12 +02:00
17b0f71538
SKU-110K CVPR2019 Dataset Auto-Download ( #3167 )
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* SKU-110K CVPR2019 Dataset Auto-Download
This PR adds the **SKU-110K CVPR2019 Dataset** https://github.com/eg4000/SKU110K_CVPR19 to the list of YOLOv5 🚀 auto-download list.
- [x] [COCO](https://cocodataset.org/#home )
- [x] [COCO128](https://www.kaggle.com/ultralytics/coco128 )
- [x] [VOC](http://host.robots.ox.ac.uk/pascal/VOC/ )
- [x] [Argoverse-HD](http://www.cs.cmu.edu/~mengtial/proj/streaming/ )
- [x] [VisDrone2019-DET](https://github.com/VisDrone/VisDrone-Dataset )
- [x] [GlobalWheat-2020](http://www.global-wheat.com/ )
- [ ] [KITTI](https://www.kaggle.com/twaldo/kitti-object-detection )
- [x] [SKU110](https://github.com/eg4000/SKU110K_CVPR19 ) (grocery store items)
- [ ] [CityScapes](https://www.cityscapes-dataset.com/ )
- [x] [Objects365](https://www.objects365.org/overview.html )
- [ ] [OpenImages](https://storage.googleapis.com/openimages/web/index.html )
```yaml
# SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19
# Train command: python train.py --data SKU-110K.yaml
# Default dataset location is next to YOLOv5:
# /parent_folder
# /datasets/SKU-110K
# /yolov5
```
* Update SKU-110K.yaml
* Update SKU-110K.yaml
2021-05-14 17:05:26 +02:00
d6a71ae5f2
Update GlobalWheat2020.yaml test: # 1276 images ( #3101 )
2021-05-10 16:04:10 +02:00
b8be76f915
Add get_coco128.sh for downloading the coco128 dataset ( #3047 )
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* Add get_coco128.sh
* Update get_coco128.sh
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-05-06 13:44:14 +02:00
8cab907f60
download() ThreadPool update ( #3027 )
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* download() ThreadPool update
* update train image count
* cid + 1
2021-05-04 23:37:31 +02:00
5189b3addb
Objects365 Update
2021-05-04 02:25:14 +02:00
37eaffec7d
Curl update ( #3004 )
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* Curl update
* Curl update
2021-05-01 17:29:51 +02:00
f55730ee9c
Objects365 bug fix
2021-05-01 01:03:09 +02:00
Glenn Jocher
Max Strobel
Jirka Borovec
Cristi Fati
Farley Lai
Jebastin Nadar
Jiacong Fang