会社で必要になったので、YOLOのv8を試してみる。
公式GitHub
↑ 頻繁にバージョンアップするので、v8.1.0のタグが付いているところのリンク。
ドキュメント見ると、YOLO v5でやったときだとGitHubリポジトリからクローンして使っていたが、今はpipでインストールすればいいだけになっているよう。
やりたいこと
人物の姿勢推定をやりたい。
前OpenPoseでやってみたが、最近のYOLOでも簡単にできるようになっているようだったので、やってみる。
以降はJupyterで実行。
環境準備
conda環境新しく作って、そこにpipでインストールする。
!conda create -n yolov8 python=3.10 -y
Collecting package metadata (current_repodata.json): ...working... done
Solving environment: ...working... done
## Package Plan ##
environment location: C:\Users\a\.conda\envs\yolov8
added / updated specs:
- python=3.10
The following NEW packages will be INSTALLED:
bzip2 pkgs/main/win-64::bzip2-1.0.8-he774522_0
ca-certificates pkgs/main/win-64::ca-certificates-2023.12.12-haa95532_0
libffi pkgs/main/win-64::libffi-3.4.4-hd77b12b_0
openssl pkgs/main/win-64::openssl-3.0.12-h2bbff1b_0
pip pkgs/main/win-64::pip-23.3.1-py310haa95532_0
python pkgs/main/win-64::python-3.10.13-he1021f5_0
setuptools pkgs/main/win-64::setuptools-68.2.2-py310haa95532_0
sqlite pkgs/main/win-64::sqlite-3.41.2-h2bbff1b_0
tk pkgs/main/win-64::tk-8.6.12-h2bbff1b_0
tzdata pkgs/main/noarch::tzdata-2023d-h04d1e81_0
vc pkgs/main/win-64::vc-14.2-h21ff451_1
vs2015_runtime pkgs/main/win-64::vs2015_runtime-14.27.29016-h5e58377_2
wheel pkgs/main/win-64::wheel-0.41.2-py310haa95532_0
xz pkgs/main/win-64::xz-5.4.5-h8cc25b3_0
zlib pkgs/main/win-64::zlib-1.2.13-h8cc25b3_0
Downloading and Extracting Packages
Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done
#
# To activate this environment, use
#
# $ conda activate yolov8
#
# To deactivate an active environment, use
#
# $ conda deactivate
==> WARNING: A newer version of conda exists. <==
current version: 23.5.2
latest version: 23.11.0
Please update conda by running
$ conda update -n base -c defaults conda
Or to minimize the number of packages updated during conda update use
conda install conda=23.11.0
Jupyterカーネルを作ったyolov8環境に切り替えて。
!pip install ultralytics
Collecting ultralytics
Downloading ultralytics-8.1.5-py3-none-any.whl.metadata (40 kB)
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Installing collected packages: pytz, py-cpuinfo, mpmath, urllib3, tzdata, tqdm, sympy, pyyaml, pyparsing, pillow, numpy, networkx, MarkupSafe, kiwisolver, idna, fsspec, fonttools, filelock, cycler, charset-normalizer, certifi, scipy, requests, pandas, opencv-python, jinja2, contourpy, torch, matplotlib, torchvision, thop, seaborn, ultralytics
Successfully installed MarkupSafe-2.1.4 certifi-2023.11.17 charset-normalizer-3.3.2 contourpy-1.2.0 cycler-0.12.1 filelock-3.13.1 fonttools-4.47.2 fsspec-2023.12.2 idna-3.6 jinja2-3.1.3 kiwisolver-1.4.5 matplotlib-3.8.2 mpmath-1.3.0 networkx-3.2.1 numpy-1.26.3 opencv-python-4.9.0.80 pandas-2.2.0 pillow-10.2.0 py-cpuinfo-9.0.0 pyparsing-3.1.1 pytz-2023.3.post1 pyyaml-6.0.1 requests-2.31.0 scipy-1.12.0 seaborn-0.13.1 sympy-1.12 thop-0.1.1.post2209072238 torch-2.1.2 torchvision-0.16.2 tqdm-4.66.1 tzdata-2023.4 ultralytics-8.1.5 urllib3-2.1.0
依存するパッケージもインストールされるようだが、例えばpytorchはどうか？
GPU使う場合は入れ替えしたりしないといけないが。
!pip show torch
Name: torch
Version: 2.1.2
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email: packages@pytorch.org
License: BSD-3
Location: c:\users\a\.conda\envs\yolov8\lib\site-packages
Requires: filelock, fsspec, jinja2, networkx, sympy, typing-extensions
Required-by: thop, torchvision, ultralytics
入ってた。
ついでに、ultralyticsパッケージ自体のバージョンも確認。
今後アップデートされても今回と同じことができるように、今のバージョンを控えておく。
!pip show ultralytics
Name: ultralytics
Version: 8.1.5
Summary: Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
Home-page:
Author: Glenn Jocher, Ayush Chaurasia, Jing Qiu
Author-email:
License: AGPL-3.0
Location: c:\users\a\.conda\envs\yolov8\lib\site-packages
Requires: matplotlib, numpy, opencv-python, pandas, pillow, psutil, py-cpuinfo, pyyaml, requests, scipy, seaborn, thop, torch, torchvision, tqdm
Required-by:
バージョン8.1.5だった。
推論実行
今まではPythonでスクリプトを実行する形だったが、yoloコマンドで実行できるよう。
まずyoloコマンドが実行できる確認。
!yolo version
8.1.5
GitHubリポジトリのサンプル通りに、オプションを付けて、サンプル画像を対象にやってみる。
GitHub - ultralytics/ultralytics at v8.1.0
!yolo detect predict model=yolov8n.pt source='https://ultralytics.com/images/bus.jpg'
Ultralytics YOLOv8.1.5 🚀 Python-3.10.13 torch-2.1.2+cpu CPU (12th Gen Intel Core(TM) i7-12700H)
YOLOv8n summary (fused): 168 layers, 3151904 parameters, 0 gradients, 8.7 GFLOPs
Downloading https://ultralytics.com/images/bus.jpg to 'bus.jpg'...
image 1/1 c:\work\yolo_test\yolov8\bus.jpg: 640x480 4 persons, 1 bus, 1 stop sign, 76.0ms
Speed: 3.0ms preprocess, 76.0ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 480)
Results saved to [1mruns\detect\predict[0m
💡 Learn more at https://docs.ultralytics.com/modes/predict
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100%|██████████| 476k/476k [00:00<00:00, 12.5MB/s]
ひとまず動いて、認識もされてるよう。
試したかったのは、人物の姿勢推定。
このサンプル画像で人が映っているので、試してみる。
yoloコマンドの使用方法は、Ultralytics社のドキュメントがあり。
Configuration - Ultralytics YOLOv8 Docs
- yoloコマンドの1つ目の引数(Optional)で、
poseを指定、これで姿勢推定のモードになるよう - GitHubドキュメントを見ると、姿勢推定用のpretrained modelがあるようだったので、これも指定。
!yolo pose predict model=yolov8n-pose.pt source='https://ultralytics.com/images/bus.jpg'
Downloading https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8n-pose.pt to 'yolov8n-pose.pt'...
Ultralytics YOLOv8.1.5 🚀 Python-3.10.13 torch-2.1.2+cpu CPU (12th Gen Intel Core(TM) i7-12700H)
YOLOv8n-pose summary (fused): 187 layers, 3289964 parameters, 0 gradients, 9.2 GFLOPs
Found https://ultralytics.com/images/bus.jpg locally at bus.jpg
image 1/1 c:\work\yolo_test\yolov8\bus.jpg: 640x480 4 persons, 96.1ms
Speed: 3.0ms preprocess, 96.1ms inference, 1.0ms postprocess per image at shape (1, 3, 640, 480)
Results saved to [1mruns\pose\predict[0m
💡 Learn more at https://docs.ultralytics.com/modes/predict
0%| | 0.00/6.51M [00:00<?, ?B/s]
23%|██▎ | 1.50M/6.51M [00:00<00:00, 14.7MB/s]
49%|████▉ | 3.22M/6.51M [00:00<00:00, 16.3MB/s]
75%|███████▌ | 4.90M/6.51M [00:00<00:00, 16.7MB/s]
100%|██████████| 6.51M/6.51M [00:00<00:00, 17.1MB/s]
これでできた。
- 検出対象は人だけになってる。
- 姿勢推定はそれなりにできてるような。
- 顔のパーツもある程度出てる(目、鼻、耳)
- 腕は、手首まで
- 足は、足首まで
モデルを変えたら変わるか？
一番重いモデルを使ってみる。
!yolo pose predict model=yolov8x-pose.pt source='https://ultralytics.com/images/bus.jpg'
Downloading https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8x-pose.pt to 'yolov8x-pose.pt'...
Ultralytics YOLOv8.1.5 🚀 Python-3.10.13 torch-2.1.2+cpu CPU (12th Gen Intel Core(TM) i7-12700H)
YOLOv8x-pose summary (fused): 287 layers, 69462204 parameters, 0 gradients, 263.2 GFLOPs
Found https://ultralytics.com/images/bus.jpg locally at bus.jpg
image 1/1 c:\work\yolo_test\yolov8\bus.jpg: 640x480 4 persons, 594.3ms
Speed: 2.9ms preprocess, 594.3ms inference, 1.0ms postprocess per image at shape (1, 3, 640, 480)
Results saved to [1mruns\pose\predict2[0m
💡 Learn more at https://docs.ultralytics.com/modes/predict
0%| | 0.00/133M [00:00<?, ?B/s]
1%| | 1.02M/133M [00:00<00:13, 10.4MB/s]
2%|▏ | 2.41M/133M [00:00<00:11, 12.2MB/s]
3%|▎ | 4.11M/133M [00:00<00:09, 14.7MB/s]
4%|▍ | 5.52M/133M [00:00<00:09, 14.3MB/s]
...
97%|█████████▋| 128M/133M [00:08<00:00, 12.4MB/s]
98%|█████████▊| 130M/133M [00:09<00:00, 13.5MB/s]
99%|█████████▉| 131M/133M [00:09<00:00, 14.0MB/s]
100%|██████████| 133M/133M [00:09<00:00, 15.0MB/s]
結果。
- 推論時間はすごい伸びた(yolov8n-pose: 96.1ms -> yolov8x-pose: 594.3ms)
- 右の人の膝の位置の推定が正確になってる
- 左の人の腕組みの様子が正確にとらえられるようになってる
GPU使う
以前と同様に、GPU使うPyTorchをインストールする。
先に現状の確認。
import torch
torch.__version__
'2.1.2+cpu'
やっぱりCPU使う版になってる。
GPU版をインストールする。
!pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 --upgrade --force-reinstall
Looking in indexes: https://download.pytorch.org/whl/cu118
Collecting torch
Downloading https://download.pytorch.org/whl/cu118/torch-2.1.2%2Bcu118-cp310-cp310-win_amd64.whl (2722.7 MB)
---------------------------------------- 0.0/2.7 GB ? eta -:--:--
---------------------------------------- 0.0/2.7 GB 11.5 MB/s eta 0:03:56
...
--------------------------------------- 2.7/2.7 GB 14.9 MB/s eta 0:00:01
--------------------------------------- 2.7/2.7 GB 14.9 MB/s eta 0:00:01
--------------------------------------- 2.7/2.7 GB 14.9 MB/s eta 0:00:01
---------------------------------------- 2.7/2.7 GB 1.0 MB/s eta 0:00:00
Collecting torchvision
Downloading https://download.pytorch.org/whl/cu118/torchvision-0.16.2%2Bcu118-cp310-cp310-win_amd64.whl (4.9 MB)
---------------------------------------- 0.0/4.9 MB ? eta -:--:--
--- ------------------------------------ 0.4/4.9 MB 8.5 MB/s eta 0:00:01
------ --------------------------------- 0.7/4.9 MB 9.5 MB/s eta 0:00:01
-------- ------------------------------- 1.1/4.9 MB 7.8 MB/s eta 0:00:01
------------ --------------------------- 1.5/4.9 MB 7.8 MB/s eta 0:00:01
---------------- ----------------------- 2.0/4.9 MB 8.6 MB/s eta 0:00:01
----------------------- ---------------- 2.9/4.9 MB 10.2 MB/s eta 0:00:01
----------------------------- ---------- 3.6/4.9 MB 10.8 MB/s eta 0:00:01
------------------------------------ --- 4.5/4.9 MB 12.0 MB/s eta 0:00:01
---------------------------------------- 4.9/4.9 MB 12.0 MB/s eta 0:00:00
Collecting torchaudio
Downloading https://download.pytorch.org/whl/cu118/torchaudio-2.1.2%2Bcu118-cp310-cp310-win_amd64.whl (3.9 MB)
---------------------------------------- 0.0/3.9 MB ? eta -:--:--
-------- ------------------------------- 0.8/3.9 MB 16.8 MB/s eta 0:00:01
--------------- ------------------------ 1.6/3.9 MB 16.4 MB/s eta 0:00:01
----------------------- ---------------- 2.3/3.9 MB 16.2 MB/s eta 0:00:01
------------------------------- -------- 3.0/3.9 MB 16.2 MB/s eta 0:00:01
----------------------------------- ---- 3.5/3.9 MB 14.7 MB/s eta 0:00:01
------------------------------------- -- 3.6/3.9 MB 12.9 MB/s eta 0:00:01
--------------------------------------- 3.9/3.9 MB 11.9 MB/s eta 0:00:01
---------------------------------------- 3.9/3.9 MB 11.4 MB/s eta 0:00:00
Collecting filelock (from torch)
Downloading https://download.pytorch.org/whl/filelock-3.9.0-py3-none-any.whl (9.7 kB)
Collecting typing-extensions (from torch)
Downloading https://download.pytorch.org/whl/typing_extensions-4.4.0-py3-none-any.whl (26 kB)
Collecting sympy (from torch)
Downloading https://download.pytorch.org/whl/sympy-1.12-py3-none-any.whl (5.7 MB)
---------------------------------------- 0.0/5.7 MB ? eta -:--:--
---- ----------------------------------- 0.7/5.7 MB 15.0 MB/s eta 0:00:01
------- -------------------------------- 1.1/5.7 MB 12.1 MB/s eta 0:00:01
------------- -------------------------- 2.0/5.7 MB 13.8 MB/s eta 0:00:01
------------------- -------------------- 2.8/5.7 MB 15.1 MB/s eta 0:00:01
------------------------ --------------- 3.5/5.7 MB 15.9 MB/s eta 0:00:01
--------------------------- ------------ 3.9/5.7 MB 14.8 MB/s eta 0:00:01
------------------------------ --------- 4.4/5.7 MB 14.1 MB/s eta 0:00:01
---------------------------------- ----- 5.0/5.7 MB 13.8 MB/s eta 0:00:01
--------------------------------------- 5.7/5.7 MB 13.4 MB/s eta 0:00:01
---------------------------------------- 5.7/5.7 MB 12.7 MB/s eta 0:00:00
Collecting networkx (from torch)
Downloading https://download.pytorch.org/whl/networkx-3.0-py3-none-any.whl (2.0 MB)
---------------------------------------- 0.0/2.0 MB ? eta -:--:--
-------------- ------------------------- 0.7/2.0 MB 15.4 MB/s eta 0:00:01
---------------------------- ----------- 1.4/2.0 MB 15.4 MB/s eta 0:00:01
---------------------------------------- 2.0/2.0 MB 16.3 MB/s eta 0:00:00
Collecting jinja2 (from torch)
Downloading https://download.pytorch.org/whl/Jinja2-3.1.2-py3-none-any.whl (133 kB)
---------------------------------------- 0.0/133.1 kB ? eta -:--:--
---------------------------------------- 133.1/133.1 kB ? eta 0:00:00
Collecting fsspec (from torch)
Downloading https://download.pytorch.org/whl/fsspec-2023.4.0-py3-none-any.whl (153 kB)
---------------------------------------- 0.0/154.0 kB ? eta -:--:--
---------------------------------------- 154.0/154.0 kB ? eta 0:00:00
Collecting numpy (from torchvision)
Downloading https://download.pytorch.org/whl/numpy-1.24.1-cp310-cp310-win_amd64.whl (14.8 MB)
---------------------------------------- 0.0/14.8 MB ? eta -:--:--
-- ------------------------------------- 0.8/14.8 MB 24.4 MB/s eta 0:00:01
--- ------------------------------------ 1.4/14.8 MB 14.9 MB/s eta 0:00:01
----- ---------------------------------- 2.2/14.8 MB 15.4 MB/s eta 0:00:01
------- -------------------------------- 2.9/14.8 MB 16.9 MB/s eta 0:00:01
---------- ----------------------------- 3.9/14.8 MB 16.8 MB/s eta 0:00:01
------------ --------------------------- 4.8/14.8 MB 16.9 MB/s eta 0:00:01
-------------- ------------------------- 5.3/14.8 MB 16.2 MB/s eta 0:00:01
---------------- ----------------------- 6.2/14.8 MB 17.1 MB/s eta 0:00:01
------------------ --------------------- 6.8/14.8 MB 16.8 MB/s eta 0:00:01
-------------------- ------------------- 7.5/14.8 MB 16.5 MB/s eta 0:00:01
---------------------- ----------------- 8.4/14.8 MB 16.7 MB/s eta 0:00:01
------------------------ --------------- 9.1/14.8 MB 16.7 MB/s eta 0:00:01
-------------------------- ------------ 10.0/14.8 MB 16.8 MB/s eta 0:00:01
---------------------------- ---------- 10.6/14.8 MB 16.4 MB/s eta 0:00:01
----------------------------- --------- 11.4/14.8 MB 16.8 MB/s eta 0:00:01
------------------------------- ------- 11.9/14.8 MB 16.4 MB/s eta 0:00:01
--------------------------------- ----- 12.6/14.8 MB 16.4 MB/s eta 0:00:01
---------------------------------- ---- 13.1/14.8 MB 15.6 MB/s eta 0:00:01
----------------------------------- --- 13.5/14.8 MB 15.2 MB/s eta 0:00:01
------------------------------------ -- 13.9/14.8 MB 14.6 MB/s eta 0:00:01
------------------------------------- - 14.3/14.8 MB 14.2 MB/s eta 0:00:01
-------------------------------------- 14.5/14.8 MB 13.4 MB/s eta 0:00:01
--------------------------------------- 14.8/14.8 MB 12.8 MB/s eta 0:00:00
Collecting requests (from torchvision)
Downloading https://download.pytorch.org/whl/requests-2.28.1-py3-none-any.whl (62 kB)
---------------------------------------- 0.0/62.8 kB ? eta -:--:--
---------------------------------------- 62.8/62.8 kB 3.3 MB/s eta 0:00:00
Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)
Downloading https://download.pytorch.org/whl/Pillow-9.3.0-cp310-cp310-win_amd64.whl (2.5 MB)
---------------------------------------- 0.0/2.5 MB ? eta -:--:--
------ --------------------------------- 0.4/2.5 MB 12.6 MB/s eta 0:00:01
---------------- ----------------------- 1.0/2.5 MB 12.9 MB/s eta 0:00:01
--------------------- ------------------ 1.3/2.5 MB 10.6 MB/s eta 0:00:01
---------------------------------- ----- 2.1/2.5 MB 12.2 MB/s eta 0:00:01
---------------------------------------- 2.5/2.5 MB 12.1 MB/s eta 0:00:00
Collecting MarkupSafe>=2.0 (from jinja2->torch)
Downloading https://download.pytorch.org/whl/MarkupSafe-2.1.3-cp310-cp310-win_amd64.whl (17 kB)
Collecting charset-normalizer<3,>=2 (from requests->torchvision)
Downloading https://download.pytorch.org/whl/charset_normalizer-2.1.1-py3-none-any.whl (39 kB)
Collecting idna<4,>=2.5 (from requests->torchvision)
Downloading https://download.pytorch.org/whl/idna-3.4-py3-none-any.whl (61 kB)
---------------------------------------- 0.0/61.5 kB ? eta -:--:--
---------------------------------------- 61.5/61.5 kB ? eta 0:00:00
Collecting urllib3<1.27,>=1.21.1 (from requests->torchvision)
Downloading https://download.pytorch.org/whl/urllib3-1.26.13-py2.py3-none-any.whl (140 kB)
---------------------------------------- 0.0/140.6 kB ? eta -:--:--
---------------------------------------- 140.6/140.6 kB ? eta 0:00:00
Collecting certifi>=2017.4.17 (from requests->torchvision)
Downloading https://download.pytorch.org/whl/certifi-2022.12.7-py3-none-any.whl (155 kB)
---------------------------------------- 0.0/155.3 kB ? eta -:--:--
---------------------------------------- 155.3/155.3 kB ? eta 0:00:00
Collecting mpmath>=0.19 (from sympy->torch)
Downloading https://download.pytorch.org/whl/mpmath-1.3.0-py3-none-any.whl (536 kB)
---------------------------------------- 0.0/536.2 kB ? eta -:--:--
------------------------------------ 522.2/536.2 kB 16.5 MB/s eta 0:00:01
------------------------------------- 536.2/536.2 kB 11.2 MB/s eta 0:00:00
Installing collected packages: mpmath, urllib3, typing-extensions, sympy, pillow, numpy, networkx, MarkupSafe, idna, fsspec, filelock, charset-normalizer, certifi, requests, jinja2, torch, torchvision, torchaudio
Attempting uninstall: mpmath
Found existing installation: mpmath 1.3.0
Uninstalling mpmath-1.3.0:
Successfully uninstalled mpmath-1.3.0
Attempting uninstall: urllib3
Found existing installation: urllib3 2.1.0
Uninstalling urllib3-2.1.0:
Successfully uninstalled urllib3-2.1.0
Attempting uninstall: typing-extensions
Found existing installation: typing_extensions 4.9.0
Uninstalling typing_extensions-4.9.0:
Successfully uninstalled typing_extensions-4.9.0
Attempting uninstall: sympy
Found existing installation: sympy 1.12
Uninstalling sympy-1.12:
Successfully uninstalled sympy-1.12
Attempting uninstall: pillow
Found existing installation: pillow 10.2.0
Uninstalling pillow-10.2.0:
Successfully uninstalled pillow-10.2.0
Attempting uninstall: numpy
Found existing installation: numpy 1.26.3
Uninstalling numpy-1.26.3:
Successfully uninstalled numpy-1.26.3
Attempting uninstall: networkx
Found existing installation: networkx 3.2.1
Uninstalling networkx-3.2.1:
Successfully uninstalled networkx-3.2.1
Attempting uninstall: MarkupSafe
Found existing installation: MarkupSafe 2.1.4
Uninstalling MarkupSafe-2.1.4:
Successfully uninstalled MarkupSafe-2.1.4
Attempting uninstall: idna
Found existing installation: idna 3.6
Uninstalling idna-3.6:
Successfully uninstalled idna-3.6
Attempting uninstall: fsspec
Found existing installation: fsspec 2023.12.2
Uninstalling fsspec-2023.12.2:
Successfully uninstalled fsspec-2023.12.2
Attempting uninstall: filelock
Found existing installation: filelock 3.13.1
Uninstalling filelock-3.13.1:
Successfully uninstalled filelock-3.13.1
Attempting uninstall: charset-normalizer
Found existing installation: charset-normalizer 3.3.2
Uninstalling charset-normalizer-3.3.2:
Successfully uninstalled charset-normalizer-3.3.2
Attempting uninstall: certifi
Found existing installation: certifi 2023.11.17
Uninstalling certifi-2023.11.17:
Successfully uninstalled certifi-2023.11.17
Attempting uninstall: requests
Found existing installation: requests 2.31.0
Uninstalling requests-2.31.0:
Successfully uninstalled requests-2.31.0
Attempting uninstall: jinja2
Found existing installation: Jinja2 3.1.3
Uninstalling Jinja2-3.1.3:
Successfully uninstalled Jinja2-3.1.3
Attempting uninstall: torch
Found existing installation: torch 2.1.2
Uninstalling torch-2.1.2:
Successfully uninstalled torch-2.1.2
Attempting uninstall: torchvision
Found existing installation: torchvision 0.16.2
Uninstalling torchvision-0.16.2:
Successfully uninstalled torchvision-0.16.2
Successfully installed MarkupSafe-2.1.3 certifi-2022.12.7 charset-normalizer-2.1.1 filelock-3.9.0 fsspec-2023.4.0 idna-3.4 jinja2-3.1.2 mpmath-1.3.0 networkx-3.0 numpy-1.24.1 pillow-9.3.0 requests-2.28.1 sympy-1.12 torch-2.1.2+cu118 torchaudio-2.1.2+cu118 torchvision-0.16.2+cu118 typing-extensions-4.4.0 urllib3-1.26.13
WARNING: Failed to remove contents in a temporary directory 'C:\Users\a\.conda\envs\yolov8\Lib\site-packages\~umpy.libs'.
You can safely remove it manually.
WARNING: Failed to remove contents in a temporary directory 'C:\Users\a\.conda\envs\yolov8\Lib\site-packages\~umpy'.
You can safely remove it manually.
WARNING: Failed to remove contents in a temporary directory 'C:\Users\a\.conda\envs\yolov8\Lib\site-packages\~orch'.
You can safely remove it manually.
前と違って、2.4GHzのWiFiに接続してしまってたので、時間が長くなってしまった。
ネットワーク環境大事。
↓ 前回
↓ 今回
pip showでの確認と、パッケージをインポートしてのバージョン確認。
!pip show torch
Name: torch
Version: 2.1.2+cu118
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email: packages@pytorch.org
License: BSD-3
Location: c:\users\a\.conda\envs\yolov8\lib\site-packages
Requires: filelock, fsspec, jinja2, networkx, sympy, typing-extensions
Required-by: thop, torchaudio, torchvision, ultralytics
import torch
torch.__version__
'2.1.2+cpu'
jupyterカーネル再起動しないとダメか？
import torch
torch.__version__
'2.1.2+cu118'
できたよう。
GPU使って推論
上と同じ、一番重いモデルでの姿勢推定やってみる。
!yolo pose predict model=yolov8x-pose.pt source='https://ultralytics.com/images/bus.jpg'
Ultralytics YOLOv8.1.5 🚀 Python-3.10.13 torch-2.1.2+cu118 CUDA:0 (NVIDIA GeForce RTX 3060 Laptop GPU, 6144MiB)
YOLOv8x-pose summary (fused): 287 layers, 69462204 parameters, 0 gradients, 263.2 GFLOPs
Found https://ultralytics.com/images/bus.jpg locally at bus.jpg
image 1/1 c:\work\yolo_test\yolov8\bus.jpg: 640x480 4 persons, 110.8ms
Speed: 6.1ms preprocess, 110.8ms inference, 13.7ms postprocess per image at shape (1, 3, 640, 480)
Results saved to [1mruns\pose\predict3[0m
💡 Learn more at https://docs.ultralytics.com/modes/predict
推論時間は、594.3ms -> 110.8msとかなり速くなった。 姿勢推定の結果は、特に変わらない。当然か。
以上
YOLOで簡単に姿勢推定を動かせて、性能もそれなりに出そうということが分かった。
