75feeb797c
YOLOv5 PyTorch Hub models >> check_requirements() ( #2591 )
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Prints 'Please restart runtime or rerun command for update to take effect.' following package auto-install to inform users to restart/rerun.
2021-03-24 16:42:54 +01:00
2b329b0945
Enhanced check_requirements() with auto-install ( #2575 )
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* Update check_requirements() with auto-install
This PR builds on an idea I had to automatically install missing dependencies rather than simply report an error message.
YOLOv5 should now 1) display all dependency issues and not simply display the first missing dependency, and 2) attempt to install/update each missing/VersionConflict package.
* cleanup
* cleanup 2
* Check requirements.txt file exists
* cleanup 3
2021-03-24 01:05:59 +01:00
1bf9365280
W&B DDP fix ( #2574 )
2021-03-23 16:54:34 +01:00
e8fc97aa38
Improved W&B integration ( #2125 )
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* 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>
2021-03-23 00:44:50 +01:00
9b11f0c58b
PyTorch Hub models default to CUDA:0 if available ( #2472 )
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* PyTorch Hub models default to CUDA:0 if available
* device as string bug fix
2021-03-14 23:16:17 -07:00
2d41e70e82
Scipy kmeans-robust autoanchor update ( #2470 )
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Fix for https://github.com/ultralytics/yolov5/issues/2394
2021-03-14 21:58:12 -07:00
38ff499b26
Update autosplit() with annotated_only option ( #2466 )
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* 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>
2021-03-14 17:11:27 -07:00
08d4918d7f
labels.jpg class names ( #2454 )
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* labels.png class names
* fontsize=10
2021-03-12 22:15:41 -08:00
f01f3223d5
Integer printout ( #2450 )
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* Integer printout
* test.py 'Labels'
* Update train.py
2021-03-12 13:35:44 -08:00
e8a2b83268
GCP sudo docker userdata.sh ( #2393 )
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* GCP sudo docker
* cleanup
2021-03-07 20:21:49 -08:00
7c2c95732c
AWS wait && echo "All tasks done." ( #2391 )
2021-03-07 20:18:30 -08:00
ba18528b47
bbox_iou() stability and speed improvements ( #2385 )
2021-03-06 13:07:34 -08:00
cd8ed3521d
image weights compatible faster random index generator v2 for mosaic augmentation ( #2383 )
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image weights compatible faster random index generator v2 for mosaic augmentation
2021-03-05 22:58:26 -08:00
2c56ad5436
Confusion matrix background axis swap ( #2114 )
2021-03-02 16:09:52 -08:00
fab5085674
EMA bug fix 2 ( #2330 )
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* EMA bug fix 2
* update
2021-03-01 17:13:34 -08:00
a82dce7faa
Fix labels being missed when image extension appears twice in filename ( #2300 )
2021-02-25 18:05:38 -08:00
ec1d8496ba
Improved model+EMA checkpointing ( #2292 )
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* 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
2021-02-24 18:26:46 -08:00
0070995bd5
Amazon AWS EC2 startup and re-startup scripts ( #2282 )
2021-02-24 01:43:59 -08:00
d5d275b6e9
Amazon AWS EC2 startup and re-startup scripts ( #2185 )
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* Amazon AWS EC2 startup and re-startup scripts
* Create resume.py
* cleanup
2021-02-23 23:10:14 -08:00
83dc1b4484
FLOPS min stride 32 ( #2276 )
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Signed-off-by: xiaowo1996 <429740343@qq.com>
2021-02-23 09:38:56 -08:00
6f5d6fcdaa
Robust objectness loss balancing ( #2256 )
2021-02-20 11:19:01 -08:00
c09964c27c
Update inference default to multi_label=False ( #2252 )
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* Update inference default to multi_label=False
* bug fix
* Update plots.py
* Update plots.py
2021-02-19 15:39:09 -08:00
47faf95079
reset head
2021-02-19 15:20:41 -08:00
d2e754b67b
Add isdocker() ( #2232 )
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* Add isdocker()
* Update general.py
* Update general.py
2021-02-16 15:58:07 -08:00
26c2e54c8f
Add check_imshow() ( #2231 )
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* Add check_imshow()
* Update general.py
* Update general.py
2021-02-16 13:56:47 -08:00
7b833e37bf
LoadStreams() frame loss bug fix ( #2222 )
2021-02-15 11:02:20 -08:00
bdd88e1ed7
YOLOv5 Segmentation Dataloader Updates ( #2188 )
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* 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
2021-02-11 21:22:45 -08:00
a5d5f9262d
Changed socket port and added timeout ( #2176 )
2021-02-10 13:01:48 -08:00
c9bda112ae
Update utils/datasets.py to support .webp files ( #2174 )
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Simply added 'webp' as an image format to the img_formats array so that webp image files can be used as training data.
2021-02-10 00:16:38 -08:00
86897e3663
Update train.py test batch_size ( #2148 )
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* Update train.py
* Update loss.py
2021-02-06 10:29:32 -08:00
e9b3de463a
Unique *.cache filenames fix ( #2134 )
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* 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>
2021-02-05 11:12:43 -08:00
4bdc5a397e
LoadImages() pathlib update ( #2140 )
2021-02-05 09:06:23 -08:00
73a0669930
Start setup for improved W&B integration ( #1948 )
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* Add helper functions for wandb and artifacts
* cleanup
* Reorganize files
* Update wandb_utils.py
* Update log_dataset.py
We can remove this code, as the giou hyp has been deprecated for a while now.
* Reorganize and update dataloader call
* yaml.SafeLoader
* PEP8 reformat
* remove redundant checks
* Add helper functions for wandb and artifacts
* cleanup
* Reorganize files
* Update wandb_utils.py
* Update log_dataset.py
We can remove this code, as the giou hyp has been deprecated for a while now.
* Reorganize and update dataloader call
* yaml.SafeLoader
* PEP8 reformat
* remove redundant checks
* Update util files
* Update wandb_utils.py
* Remove word size
* Change path of labels.zip
* remove unused imports
* remove --rect
* log_dataset.py cleanup
* log_dataset.py cleanup2
* wandb_utils.py cleanup
* remove redundant id_count
* wandb_utils.py cleanup2
* rename cls
* use pathlib for zip
* rename dataloader to dataset
* Change import order
* Remove redundant code
* remove unused import
* remove unused imports
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-02-01 21:38:41 -08:00
9646ca438a
Update plot_study() ( #2112 )
2021-02-01 13:51:11 -08:00
be9edffded
Update test.py --task speed and study ( #2099 )
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* Add --speed benchmark
* test range 256 - 1536
* update
* update
* update
* update
2021-01-31 13:58:49 -08:00
a18efc3a73
Add variable-stride inference support ( #2091 )
2021-01-30 13:47:23 -08:00
630ec06af6
Update to colors.TABLEAU_COLORS ( #2069 )
2021-01-28 12:37:21 -08:00
f639e14e4d
Metric-Confidence plots feature addition ( #2057 )
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* Metric-Confidence plots feature addition
* cleanup
* Metric-Confidence plots feature addition
* cleanup
* Update run-once lines
* cleanup
* save all 4 curves to wandb
2021-01-27 17:10:53 -08:00
f59f80114c
Add 'exclude' tuple to check_requirements() ( #2041 )
2021-01-26 21:17:36 -08:00
59c21c7bcb
W&B log epoch ( #1946 )
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* W&B log epoch
* capitalize
* W&B log epoch
* capitalize
* Update train.py
New try using https://docs.wandb.ai/library/log#incremental-logging
* Update train.py
* Update test.py
* Update train.py
* Update plots.py
* Update train.py
* Update train.py
* label plot step -1
* update
* update
* update
* update
* update
* update
* Update train.py
* Update train.py
2021-01-26 21:16:01 -08:00
08d3119e09
Add histogram equalization fcn ( #2049 )
2021-01-26 17:30:42 -08:00
8fcbe43423
Check im.format during dataset caching ( #2042 )
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* Check im.format during dataset caching
* Update datasets.py
2021-01-25 20:55:35 -08:00
3b7feeafdf
Update general.py check_git_status() fix ( #2020 )
2021-01-22 15:59:01 -08:00
aac33f87ad
Update inference multiple-counting ( #2019 )
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* Update inference multiple-counting
* update github check
2021-01-22 15:39:08 -08:00
77fd83225f
Update google_utils.py ( #2017 )
2021-01-22 15:08:42 -08:00
1445ab2b27
check_git_status() Windows fix ( #2015 )
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* check_git_status() Windows fix
* Update general.py
* Update general.py
* Update general.py
* Update general.py
* Update general.py
* Update general.py
2021-01-22 12:37:12 -08:00
d9212140b3
Add xywhn2xyxy() ( #1983 )
2021-01-19 13:33:52 -08:00
b1cf25dd9a
check_git_status() asserts ( #1977 )
2021-01-18 10:49:28 -08:00
17751b9891
Update autoanchor.py with yaml.SafeLoader ( #1971 )
2021-01-18 10:47:42 -08:00
35400dc7b7
Update plots.py with yaml.SafeLoader ( #1968 )
2021-01-18 10:46:20 -08:00
b26a2f6242
check_git_status() when not exist /workspace ( #1966 )
2021-01-17 11:55:25 -08:00
e8a41e8916
prevent check_git_status() in docker images ( #1951 )
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* prevent check_git_status() running docker images
* Update general.py
2021-01-16 01:15:38 -08:00
ca9babb8e6
Add ComputeLoss() class ( #1950 )
2021-01-15 13:50:24 -08:00
b75c432ea0
GitHub API rate limit fallback ( #1930 )
2021-01-13 21:09:50 -08:00
051e9e80de
check_git_status() bug fix ( #1925 )
2021-01-13 10:25:53 -08:00
509dd51aca
check_git_status() improvements ( #1916 )
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* check_online()
* Update general.py
* update check_git_status()
* reverse rev-parse order
* fetch
* improved responsiveness
* comment
* comment
* remove hyp['giou'] compat warning
2021-01-12 21:51:49 -08:00
dd03b20ba5
colorstr() updates ( #1909 )
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* W&B ImportError message fix
* colorstr() updates
* colorstr() updates
* colorstr() default to 'blue', 'bold'
* train: magenta
* train: blue
2021-01-12 10:33:15 -08:00
1d1c0567a4
PyTorch Hub results.render() ( #1897 )
2021-01-10 20:06:11 -08:00
ffef77124e
Update torch_utils.py ( #1895 )
2021-01-10 12:26:29 -08:00
0f11aaf551
GitHub API rate limit newline ( #1894 )
2021-01-10 11:47:00 -08:00
d06ad3bc3d
GitHub API rate limit fix ( #1894 )
2021-01-10 11:42:45 -08:00
6ab589583c
Add colorstr() ( #1887 )
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* Add colorful()
* update
* newline fix
* add git description
* --always
* update loss scaling
* update loss scaling 2
* rename to colorstr()
2021-01-09 15:24:18 -08:00
fea9c9b80c
nn.SiLU() citation correction ( #1713 )
2021-01-06 20:58:41 -08:00
e77c77f580
Add check_requirements() ( #1853 )
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* Add check_requirements()
* add import
* parameterize filename
* add to detect, test
2021-01-06 16:35:40 -08:00
135ec5c5ce
W&B ID reset on training completion ( #1852 )
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* Update train.py
Fix the bug of always the same W&B ID and continue overwrite with the old logging.
BUG report
https://github.com/ultralytics/yolov5/issues/1851
* Fix the bug of duplicate W&B ID
fix the bug of https://github.com/ultralytics/yolov5/issues/1851
If we had trained on yolov5s.pt, the program will generate a new unique W&B ID.
If we hadn't, the program will keep the old code, we can still use --resume aug.
* Update general.py
* revert train.py changes
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-01-06 16:27:22 -08:00
69be8e738f
YOLOv5 v4.0 Release ( #1837 )
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* 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 study.png
* update study.png
* Update datasets.py
2021-01-04 19:54:09 -08:00
0e341c5660
Create one_cycle() function ( #1836 )
2021-01-04 15:49:08 -08:00
9f5a18bb80
Torch CUDA synchronize update ( #1826 )
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* torch.cuda.synchronize() update
* torch.cuda.synchronize() update
* torch.cuda.synchronize() update
* newline
2021-01-03 11:23:12 -08:00
c0ffcdf998
Display correct CUDA devices ( #1776 )
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* Display correct CUDA devices
* cleanup
2020-12-24 13:01:35 -08:00
3004fb5bc1
Automatic m.half() profile on x.half()
2020-12-21 15:20:33 -08:00
0bd9c48609
Update torch_utils.py
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FLOPS to GFLOPS
2020-12-21 13:29:52 -08:00
394d1c89f3
Input channel yaml['ch'] addition ( #1741 )
2020-12-19 10:54:01 -08:00
685d601308
Increase plot_labels() speed ( #1736 )
2020-12-18 18:05:38 -08:00
49abc722fc
Update profile_idetection() ( #1727 )
2020-12-18 01:19:17 -08:00
d5289b54c4
clean_str() function addition ( #1674 )
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* clean_str() function addition
* cleanup
* add euro symbol €
* add closing exclamation (spanish)
* cleanup
2020-12-17 17:20:20 -08:00
6bd5e8bca7
nn.SiLU() export support ( #1713 )
2020-12-16 17:55:57 -08:00
1fc9d42a64
NMS --classes 0 bug fix ( #1710 )
2020-12-16 08:58:51 -08:00
8bc0027afc
Update loss criteria constructor ( #1711 )
2020-12-16 08:39:35 -08:00
035ac82ed0
Fix torch multi-GPU --device error ( #1701 )
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* Fix torch GPU error
* Update torch_utils.py
single-line device =
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2020-12-15 20:42:14 -08:00
69ea70cd3b
Add idetection_profile() function to plots.py ( #1700 )
2020-12-15 18:35:47 -08:00
54043a9fa4
Streaming --save-txt bug fix ( #1672 )
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* Streaming --save-txt bug fix
* cleanup
2020-12-11 15:45:32 -08:00
ada90e3901
Profile() feature addition ( #1673 )
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* Profile() feature addition
* cleanup
2020-12-11 09:30:39 -08:00
94a7f55c4e
FReLU bias=False bug fix ( #1666 )
2020-12-10 13:06:15 -08:00
2e8e02745b
vast.ai compatability updates ( #1657 )
2020-12-09 19:01:08 -08:00
fa8f1fb0e9
Simplify autoshape() post-process ( #1653 )
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* Simplify autoshape() post-process
* cleanup
* cleanup
2020-12-09 07:44:06 -08:00
84f9bb5d92
Normalized mosaic plotting bug fix ( #1647 )
2020-12-08 18:44:13 -08:00
0bb43953eb
Reinstate PR curve sentinel values ( #1645 )
2020-12-08 17:40:49 -08:00
68e6ab668b
Hub device mismatch bug fix ( #1619 )
2020-12-06 17:53:38 +01:00
791dadb51c
Pycocotools best.pt after COCO train ( #1616 )
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* Pycocotools best.pt after COCO train
* cleanup
2020-12-06 14:58:33 +01:00
8918e63476
Increase FLOPS robustness ( #1608 )
2020-12-05 11:41:34 +01:00
f010147578
Update matplotlib.use('Agg') tight ( #1583 )
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* Update matplotlib tight_layout=True
* udpate
* udpate
* update
* png to ps
* update
* update
2020-12-02 15:53:16 +01:00
784feae30a
Update matplotlib svg backend ( #1580 )
2020-12-02 14:05:12 +01:00
577f298d9b
plot_images() scale bug fix ( #1566 )
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fix bugs in plot_images
2020-12-01 11:29:59 +01:00
b6ed1104a6
Daemon thread plotting ( #1561 )
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* Daemon thread plotting
* remove process_batch
* plot after print
2020-11-30 16:44:14 +01:00
cff9263490
f.read().strip() ( #1551 )
2020-11-29 11:59:52 +01:00
9fa7f9f598
f.read().strip()
2020-11-29 11:58:14 +01:00
96a84468b9
Update labels_to_image_weights() ( #1545 )
2020-11-28 12:25:45 +01:00
c9798ae0e1
Update plot_study_txt() ( #1533 )
2020-11-26 22:18:17 +01:00
0f2057ed33
Targets scaling bug fix ( #1529 )
2020-11-26 18:33:28 +01:00
2c3efa430b
Mosaic plots bug fix ( #1526 )
2020-11-26 14:02:22 +01:00
Glenn Jocher
Ayush Chaurasia
Yann Defretin
Yonghye Kwon
Ryan Avery
Iden Craven
xiaowo1996
NanoCode012
Transigent
train255
Abhiram V
Tommy in Tongji
Polydefkis Gkagkos
Hu Ye