dabad5793a
Created using Colaboratory
2021-07-08 15:45:53 +02:00
e7888af94c
Fix inconsistent NMS IoU value for COCO ( #3934 )
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Evaluation of 'best' and 'last' models will use the same params as the evaluation during the training phase.
This PR fixes https://github.com/ultralytics/yolov5/issues/3907
2021-07-08 15:29:02 +02:00
8c6f9e15bf
Update `dataset_stats()` for zipped datasets ( #3926 )
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* Update `dataset_stats()` for zipped datasets
@KalenMike
* cleanup
2021-07-08 11:42:30 +02:00
850970e081
`feature_visualization()` CUDA fix ( #3925 )
2021-07-07 16:23:31 +02:00
588094eb7a
Update `setattr()` default for Hub PIL images ( #3923 )
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Fix inference from PIL source.
2021-07-07 16:13:12 +02:00
411842e058
Fix `torch.hub.list('ultralytics/yolov5')` pathlib bug ( #3921 )
2021-07-07 16:08:42 +02:00
87b094bcbc
Feature visualization update ( #3920 )
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* Feature visualization update
* Save to jpg (faster)
* Save to png
2021-07-07 15:41:58 +02:00
61047a2b4f
Save PyTorch Hub models to `/root/hub/cache/dir` ( #3904 )
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* Create hubconf.py
* Add save_dir variable
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-07-07 13:41:46 +02:00
33202b7f0b
YOLOv5 + Albumentations integration ( #3882 )
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* Albumentations integration
* ToGray p=0.01
* print confirmation
* create instance in dataloader init method
* improved version handling
* transform not defined fix
* assert string update
* create check_version()
* add spaces
* update class comment
2021-07-05 18:01:54 +02:00
6a3ee7cf03
Hub models `map_location=device` ( #3894 )
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* Hub models `map_location=device`
* cleanup
2021-07-05 16:20:46 +02:00
8930e22cce
Evolution commented `hyp['anchors']` fix ( #3887 )
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Fix for `KeyError: 'anchors'` error when start hyperparameter evolution:
```bash
python train.py --evolve
```
```bash
Traceback (most recent call last):
File "E:\yolov5\train.py", line 623, in <module>
hyp[k] = max(hyp[k], v[1]) # lower limit
KeyError: 'anchors'
```
2021-07-05 12:48:27 +02:00
3c3f8fbd5d
Improved BGR2RGB speeds ( #3880 )
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* Update BGR2RGB ops
* speed improvements
* cleanup
2021-07-04 20:12:32 +02:00
9e8fb9fd0b
Create `utils/augmentations.py` ( #3877 )
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* Create `utils/augmentations.py`
* cleanup
2021-07-04 18:14:04 +02:00
81b31824f5
Models `*.yaml` reformat ( #3875 )
2021-07-04 16:55:08 +02:00
bd88e7f4f2
Created using Colaboratory
2021-07-04 15:55:23 +02:00
9d86b54eb3
Add multi-stream saving feature ( #3864 )
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* Added the recording feature for multiple streams
Thanks for the very cool repo!!
I was trying to record multiple feeds at the same time, but the current version of the detector only had one video writer and one vid_path!
So the streams were not being saved and only were initialized with one frame and this process didn't record the whole thing.
Fix:
I made a list of `vid_writer` and `vid_path` and the `i` from the loop over the `pred` took care of the writer which need to work!
I hope this helps, Thanks!
* Cleanup list lengths
* batch size variable
* Update datasets.py
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-07-04 12:55:57 +02:00
d3e9d69850
`--evolve 300` generations CLI argument ( #3863 )
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* evolve command accepts argument for number of generations
* evolve generations argument used in evolve for loop
* evolve argument boolean fixes
* default to 300 evolve generations
* Update train.py
Co-authored-by: John San Soucie <jsansoucie@whoi.edu>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-07-04 12:14:35 +02:00
831773f5a2
Add EXIF rotation to YOLOv5 Hub inference ( #3852 )
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* rotating an image according to its exif tag
* Update common.py
* Update datasets.py
* Update datasets.py
faster
* delete extraneous gpg file
* Update common.py
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-07-02 13:25:54 +02:00
4717a3b038
Created using Colaboratory
2021-07-02 12:24:27 +02:00
b6863385b5
Created using Colaboratory
2021-07-02 12:23:09 +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
25d1f2932c
Plot `AutoShape()` detections in ascending order ( #3843 )
2021-06-30 15:10:40 +02:00
7d6af69638
Fix `LoadStreams()` dataloader frame skip issue ( #3833 )
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* Update datasets.py to read every 4th frame of streams
* Update datasets.py
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-06-30 12:11:29 +02:00
57c5d02bbe
Concise `TransformerBlock()` ( #3821 )
2021-06-29 16:03:10 +02:00
5ea771d93d
Move IoU functions to metrics.py ( #3820 )
2021-06-29 13:18:13 +02:00
3213d8713f
Fix for `dataset_stats()` with updated data.yaml ( #3819 )
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@KalenMike
2021-06-29 12:44:59 +02:00
02719dde52
Update `feature_visualization()` ( #3807 )
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* Update `feature_visualization()`
Only plot for data with height, width > 1
* cleanup
* Cleanup
2021-06-28 13:48:14 +02:00
20d45aa4f1
Add feature map visualization ( #3804 )
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* Add feature map visualization
Add a feature_visualization function to visualize the mid feature map of the model.
* Update yolo.py
* remove boolean from forward and reorder if statement
* remove print from forward
* General cleanup
* Indent
* Update plots.py
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-06-28 13:18:45 +02:00
3974d725b6
Fix warmup `accumulate` ( #3722 )
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* gradient accumulation during warmup in train.py
Context:
`accumulate` is the number of batches/gradients accumulated before calling the next optimizer.step().
During warmup, it is ramped up from 1 to the final value nbs / batch_size.
Although I have not seen this in other libraries, I like the idea. During warmup, as grads are large, too large steps are more of on issue than gradient noise due to small steps.
The bug:
The condition to perform the opt step is wrong
> if ni % accumulate == 0:
This produces irregular step sizes if `accumulate` is not constant. It becomes relevant when batch_size is small and `accumulate` changes many times during warmup.
This demo also shows the proposed solution, to use a ">=" condition instead:
https://colab.research.google.com/drive/1MA2z2eCXYB_BC5UZqgXueqL_y1Tz_XVq?usp=sharing
Further, I propose not to restrict the number of warmup iterations to >= 1000. If the user changes hyp['warmup_epochs'], this causes unexpected behavior. Also, it makes evolution unstable if this parameter was to be optimized.
* replace last_opt_step tracking by do_step(ni)
* add docstrings
* move down nw
* Update train.py
* revert math import move
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-06-28 12:25:13 +02:00
5e976a274d
Fix competition link ( #3799 )
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* link to the competition repaired
* Update README.md
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-06-27 15:28:50 +02:00
47543f97b1
FROM nvcr.io/nvidia/pytorch:21.05-py3 ( #3794 )
2021-06-26 17:12:43 +02:00
5e6886c860
Update Dockerfile ( #3792 )
2021-06-26 16:51:17 +02:00
96c87f1711
nvcr.io/nvidia/pytorch:21.06-py3 ( #3791 )
2021-06-26 16:28:06 +02:00
07166ba38c
Update Usage examples ( #3790 )
2021-06-26 16:09:56 +02:00
92d49fde35
Update seeds for single-GPU reproducibility ( #3789 )
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For seed=0 on single-GPU.
2021-06-26 15:42:40 +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
8035b61682
Update objectness IoU sort ( #3786 )
2021-06-26 14:52:18 +02:00
157aa2f886
Objectness IoU Sort ( #3610 )
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Co-authored-by: U-LAPTOP-5N89P8V7\banhu <ban.huang@foxmail.com>
2021-06-26 14:45:53 +02:00
9dc5d35fce
Update README.md fix banner width ( #3785 )
2021-06-26 13:05:46 +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
ffb6e11050
W&B: Update Tables API and comply with new dataset_check ( #3772 )
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* Update tables API and windows path fix
* update dataset check
2021-06-25 20:45:33 +02:00
09246a5a33
fix/incorrect_fitness_import ( #3770 )
2021-06-25 16:16:18 +02:00
f2d97ebb25
Remove DDP MultiHeadAttention fix ( #3768 )
2021-06-25 12:52:05 +02:00
374957317a
Add `xyxy2xywhn()` ( #3765 )
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* Edit Comments for numpy2torch tensor process
Edit Comments for numpy2torch tensor process
* add xyxy2xywhn
add xyxy2xywhn
* add xyxy2xywhn
* formatting
* pass arguments
pass arguments
* edit comment for xyxy2xywhn()
edit comment for xyxy2xywhn()
* cleanup datasets.py
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-06-25 11:47:46 +02:00
03281f8c76
COCO annotations JSON fix ( #3764 )
2021-06-25 01:55:53 +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
417a2f425c
Edit comment ( #3759 )
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edit comment
2021-06-24 15:57:27 +02:00
ae4261c774
Force non-zero hyp evolution weights `w` ( #3748 )
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Fix for https://github.com/ultralytics/yolov5/issues/3741
2021-06-23 12:56:22 +02:00
fdc22398fa
Create `data/hyps` directory ( #3747 )
2021-06-23 12:49:38 +02:00
Glenn Jocher
Eldar Kurtic
jmiranda-laplateforme
johnohagan
ketan-b
san-soucie
Valentin Aliferov
Feras Oughali
Zigarss
yellowdolphin
batrlatom
Ayush Chaurasia
Piotr Skalski
Yonghye Kwon