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ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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Where to pull the docker image #4646

Closed zcswdt closed 2 years ago

zcswdt commented 3 years ago

❔Question

Additional context

iceisfun commented 3 years ago

Try pulling the current git repo and executing this from within the directory you've checked out

docker build -t yolo .
docker run --rm -it --gpus all --ipc=host -v /sys:/sys yolo

It might also be helpful to map a data directory into your container if your doing custom training

docker run --rm -it --gpus all --ipc=host -v /sys:/sys yolo -v $(realpath ~/custom_training_dataset):/usr/src/app/runs
zcswdt commented 3 years ago

Try pulling the current git repo and executing this from within the directory you've checked out

docker build -t yolo .
docker run --rm -it --gpus all --ipc=host -v /sys:/sys yolo

It might also be helpful to map a data directory into your container if your doing custom training

docker run --rm -it --gpus all --ipc=host -v /sys:/sys yolo -v $(realpath ~/custom_training_dataset):/usr/src/app/runs

I remember that there is an official image. If you use dockerfile directly, you will get an error. image

iceisfun commented 3 years ago

I have built this on a test machine from scratch on ubuntu 20.04 lts desktop

Is it possible your internet provider is not allowing direct https access?

Example build and train -- this is using a custom dataset not provided by yolo, the directory $(realpath dataset) will not exist on your local machine.

$ docker build -t yolo .
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Digest: sha256:a5986639e4cf01eb35c0c0a9ca9fb9c6f905cc1b546966b78de4f69d15b894cf
Status: Downloaded newer image for nvcr.io/nvidia/pytorch:21.05-py3
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Step 2/11 : RUN apt update && apt install -y zip htop screen libgl1-mesa-glx
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The following additional packages will be installed:
  libdrm-amdgpu1 libdrm-common libdrm-intel1 libdrm-nouveau2 libdrm-radeon1
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  libxcb-dri2-0 libxcb-dri3-0 libxcb-glx0 libxcb-present0 libxcb-randr0
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Suggested packages:
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  htop libdrm-amdgpu1 libdrm-common libdrm-intel1 libdrm-nouveau2
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  libglapi-mesa libglvnd0 libglx-mesa0 libglx0 libllvm12 libpciaccess0
  libsensors-config libsensors5 libutempter0 libvulkan1 libwayland-client0
  libx11-6 libx11-data libx11-xcb1 libxau6 libxcb-dri2-0 libxcb-dri3-0
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  libxcb-xfixes0 libxcb1 libxdmcp6 libxext6 libxfixes3 libxshmfence1
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Setting up libsensors-config (1:3.6.0-2ubuntu1) ...
Setting up libxcb-shm0:amd64 (1.14-2) ...
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Setting up libsensors5:amd64 (1:3.6.0-2ubuntu1) ...
Setting up libglapi-mesa:amd64 (21.0.3-0ubuntu0.3~20.04.1) ...
Setting up libvulkan1:amd64 (1.2.131.2-1) ...
Setting up libutempter0:amd64 (1.1.6-4) ...
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Setting up libxcb-randr0:amd64 (1.14-2) ...
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Setting up libdrm-common (2.4.105-3~20.04.1) ...
Setting up libelf1:amd64 (0.176-1.1build1) ...
Setting up libwayland-client0:amd64 (1.18.0-1) ...
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Setting up libxext6:amd64 (2:1.3.4-0ubuntu1) ...
Setting up screen (4.8.0-1ubuntu0.1) ...
debconf: unable to initialize frontend: Dialog
debconf: (TERM is not set, so the dialog frontend is not usable.)
debconf: falling back to frontend: Readline
Setting up libxxf86vm1:amd64 (1:1.1.4-1build1) ...
Setting up libxfixes3:amd64 (1:5.0.3-2) ...
Setting up libdrm2:amd64 (2.4.105-3~20.04.1) ...
Setting up libdrm-amdgpu1:amd64 (2.4.105-3~20.04.1) ...
Setting up mesa-vulkan-drivers:amd64 (21.0.3-0ubuntu0.3~20.04.1) ...
Setting up libdrm-nouveau2:amd64 (2.4.105-3~20.04.1) ...
Setting up libdrm-radeon1:amd64 (2.4.105-3~20.04.1) ...
Setting up libdrm-intel1:amd64 (2.4.105-3~20.04.1) ...
Setting up libgl1-mesa-dri:amd64 (21.0.3-0ubuntu0.3~20.04.1) ...
Setting up libglx-mesa0:amd64 (21.0.3-0ubuntu0.3~20.04.1) ...
Setting up libglx0:amd64 (1.3.2-1~ubuntu0.20.04.1) ...
Setting up libgl1:amd64 (1.3.2-1~ubuntu0.20.04.1) ...
Setting up libgl1-mesa-glx:amd64 (21.0.3-0ubuntu0.3~20.04.1) ...
Processing triggers for libc-bin (2.31-0ubuntu9.2) ...
Processing triggers for mime-support (3.64ubuntu1) ...
Removing intermediate container 4adacae6eecc
 ---> 66164444827c
Step 3/11 : COPY requirements.txt .
 ---> d31373560402
Step 4/11 : RUN python -m pip install --upgrade pip
 ---> Running in 6de3bb4aa417
Collecting pip
  Downloading pip-21.2.4-py3-none-any.whl (1.6 MB)
Installing collected packages: pip
  Attempting uninstall: pip
    Found existing installation: pip 20.2.4
    Uninstalling pip-20.2.4:
      Successfully uninstalled pip-20.2.4
Successfully installed pip-21.2.4
Removing intermediate container 6de3bb4aa417
 ---> b7afd277e4b2
Step 5/11 : RUN pip uninstall -y nvidia-tensorboard nvidia-tensorboard-plugin-dlprof
 ---> Running in 8f673ff7a79e
Found existing installation: nvidia-tensorboard 1.15.0+nv21.4
Uninstalling nvidia-tensorboard-1.15.0+nv21.4:
  Successfully uninstalled nvidia-tensorboard-1.15.0+nv21.4
Found existing installation: nvidia-tensorboard-plugin-dlprof 1.2.0
Uninstalling nvidia-tensorboard-plugin-dlprof-1.2.0:
  Successfully uninstalled nvidia-tensorboard-plugin-dlprof-1.2.0
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
Removing intermediate container 8f673ff7a79e
 ---> a8dfafe5cdfd
Step 6/11 : RUN pip install --no-cache -r requirements.txt coremltools onnx gsutil notebook
 ---> Running in fbd2daff3bce
Collecting coremltools
  Downloading coremltools-4.1-cp38-none-manylinux1_x86_64.whl (3.4 MB)
Requirement already satisfied: onnx in /opt/conda/lib/python3.8/site-packages (1.8.0)
Collecting gsutil
  Downloading gsutil-4.67.tar.gz (2.9 MB)
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Collecting opencv-python>=4.1.2
  Downloading opencv_python-4.5.3.56-cp38-cp38-manylinux2014_x86_64.whl (49.9 MB)
Collecting Pillow>=8.0.0
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Requirement already satisfied: PyYAML>=5.3.1 in /opt/conda/lib/python3.8/site-packages (from -r requirements.txt (line 8)) (5.4.1)
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Collecting tensorboard>=2.4.1
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Collecting seaborn>=0.11.0
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Requirement already satisfied: pandas in /opt/conda/lib/python3.8/site-packages (from -r requirements.txt (line 20)) (1.1.4)
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Collecting attr
  Downloading attr-0.3.1.tar.gz (1.7 kB)
Requirement already satisfied: six>=1.10.0 in /opt/conda/lib/python3.8/site-packages (from coremltools) (1.15.0)
Requirement already satisfied: packaging in /opt/conda/lib/python3.8/site-packages (from coremltools) (20.9)
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  Downloading sympy-1.8-py3-none-any.whl (6.1 MB)
Collecting numpy>=1.18.5
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Requirement already satisfied: attrs in /opt/conda/lib/python3.8/site-packages (from coremltools) (20.3.0)
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Collecting argcomplete>=1.9.4
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Collecting crcmod>=1.7
  Downloading crcmod-1.7.tar.gz (89 kB)
Collecting fasteners>=0.14.1
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Collecting gcs-oauth2-boto-plugin>=2.7
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Collecting google-apitools>=0.5.32
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Collecting httplib2>=0.18
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Collecting google-reauth>=0.1.0
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Collecting mock==2.0.0
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Collecting monotonic>=1.4
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Requirement already satisfied: pyOpenSSL>=0.13 in /opt/conda/lib/python3.8/site-packages (from gsutil) (19.1.0)
Collecting retry_decorator>=1.0.0
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Collecting pbr>=0.11
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Requirement already satisfied: Send2Trash>=1.5.0 in /opt/conda/lib/python3.8/site-packages (from notebook) (1.5.0)
Requirement already satisfied: terminado>=0.8.3 in /opt/conda/lib/python3.8/site-packages (from notebook) (0.9.4)
Requirement already satisfied: prometheus-client in /opt/conda/lib/python3.8/site-packages (from notebook) (0.10.1)
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Requirement already satisfied: argon2-cffi in /opt/conda/lib/python3.8/site-packages (from notebook) (20.1.0)
Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=3.2.2->-r requirements.txt (line 4)) (2.8.1)
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Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=3.2.2->-r requirements.txt (line 4)) (1.3.1)
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Requirement already satisfied: markdown>=2.6.8 in /opt/conda/lib/python3.8/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 15)) (3.3.4)
Collecting tensorboard-plugin-wit>=1.6.0
  Downloading tensorboard_plugin_wit-1.8.0-py3-none-any.whl (781 kB)
Collecting tensorboard-data-server<0.7.0,>=0.6.0
  Downloading tensorboard_data_server-0.6.1-py3-none-manylinux2010_x86_64.whl (4.9 MB)
Collecting google-auth<2,>=1.6.3
  Downloading google_auth-1.35.0-py2.py3-none-any.whl (152 kB)
Collecting google-auth-oauthlib<0.5,>=0.4.1
  Downloading google_auth_oauthlib-0.4.6-py2.py3-none-any.whl (18 kB)
Requirement already satisfied: setuptools>=41.0.0 in /opt/conda/lib/python3.8/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 15)) (50.3.1.post20201107)
Requirement already satisfied: werkzeug>=0.11.15 in /opt/conda/lib/python3.8/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 15)) (1.0.1)
Requirement already satisfied: absl-py>=0.4 in /opt/conda/lib/python3.8/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 15)) (0.12.0)
Requirement already satisfied: grpcio>=1.24.3 in /opt/conda/lib/python3.8/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 15)) (1.37.0)
Requirement already satisfied: requests<3,>=2.21.0 in /opt/conda/lib/python3.8/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 15)) (2.24.0)
Requirement already satisfied: wheel>=0.26 in /opt/conda/lib/python3.8/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 15)) (0.35.1)
Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.8/site-packages (from pandas->-r requirements.txt (line 20)) (2021.1)
Collecting boto>=2.29.1
  Downloading boto-2.49.0-py2.py3-none-any.whl (1.4 MB)
Collecting oauth2client>=2.2.0
  Downloading oauth2client-4.1.3-py2.py3-none-any.whl (98 kB)
Collecting rsa<5,>=3.1.4
  Downloading rsa-4.7.2-py3-none-any.whl (34 kB)
Collecting pyasn1-modules>=0.2.1
  Downloading pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 kB)
Collecting cachetools<5.0,>=2.0.0
  Downloading cachetools-4.2.2-py3-none-any.whl (11 kB)
Collecting requests-oauthlib>=0.7.0
  Downloading requests_oauthlib-1.3.0-py2.py3-none-any.whl (23 kB)
Collecting pyu2f
  Downloading pyu2f-0.1.5.tar.gz (27 kB)
Collecting pyasn1>=0.1.7
  Downloading pyasn1-0.4.8-py2.py3-none-any.whl (77 kB)
Requirement already satisfied: cryptography>=2.8 in /opt/conda/lib/python3.8/site-packages (from pyOpenSSL>=0.13->gsutil) (3.2.1)
Requirement already satisfied: cffi!=1.11.3,>=1.8 in /opt/conda/lib/python3.8/site-packages (from cryptography>=2.8->pyOpenSSL>=0.13->gsutil) (1.14.3)
Requirement already satisfied: pycparser in /opt/conda/lib/python3.8/site-packages (from cffi!=1.11.3,>=1.8->cryptography>=2.8->pyOpenSSL>=0.13->gsutil) (2.20)
Requirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.8/site-packages (from requests<3,>=2.21.0->tensorboard>=2.4.1->-r requirements.txt (line 15)) (2.10)
Requirement already satisfied: chardet<4,>=3.0.2 in /opt/conda/lib/python3.8/site-packages (from requests<3,>=2.21.0->tensorboard>=2.4.1->-r requirements.txt (line 15)) (3.0.4)
Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.8/site-packages (from requests<3,>=2.21.0->tensorboard>=2.4.1->-r requirements.txt (line 15)) (2020.12.5)
Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/conda/lib/python3.8/site-packages (from requests<3,>=2.21.0->tensorboard>=2.4.1->-r requirements.txt (line 15)) (1.25.11)
Collecting oauthlib>=3.0.0
  Downloading oauthlib-3.1.1-py2.py3-none-any.whl (146 kB)
Requirement already satisfied: ptyprocess in /opt/conda/lib/python3.8/site-packages (from terminado>=0.8.3->notebook) (0.7.0)
Requirement already satisfied: ipython>=5.0.0 in /opt/conda/lib/python3.8/site-packages (from ipykernel->notebook) (7.22.0)
Requirement already satisfied: pygments in /opt/conda/lib/python3.8/site-packages (from ipython>=5.0.0->ipykernel->notebook) (2.8.1)
Requirement already satisfied: backcall in /opt/conda/lib/python3.8/site-packages (from ipython>=5.0.0->ipykernel->notebook) (0.2.0)
Requirement already satisfied: pexpect>4.3 in /opt/conda/lib/python3.8/site-packages (from ipython>=5.0.0->ipykernel->notebook) (4.8.0)
Requirement already satisfied: jedi>=0.16 in /opt/conda/lib/python3.8/site-packages (from ipython>=5.0.0->ipykernel->notebook) (0.17.0)
Requirement already satisfied: pickleshare in /opt/conda/lib/python3.8/site-packages (from ipython>=5.0.0->ipykernel->notebook) (0.7.5)
Requirement already satisfied: decorator in /opt/conda/lib/python3.8/site-packages (from ipython>=5.0.0->ipykernel->notebook) (5.0.6)
Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /opt/conda/lib/python3.8/site-packages (from ipython>=5.0.0->ipykernel->notebook) (3.0.17)
Requirement already satisfied: parso>=0.7.0 in /opt/conda/lib/python3.8/site-packages (from jedi>=0.16->ipython>=5.0.0->ipykernel->notebook) (0.8.2)
Requirement already satisfied: wcwidth in /opt/conda/lib/python3.8/site-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=5.0.0->ipykernel->notebook) (0.2.5)
Requirement already satisfied: MarkupSafe>=0.23 in /opt/conda/lib/python3.8/site-packages (from jinja2->notebook) (1.1.1)
Requirement already satisfied: defusedxml in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (0.7.1)
Requirement already satisfied: pandocfilters>=1.4.1 in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (1.4.3)
Requirement already satisfied: testpath in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (0.4.4)
Requirement already satisfied: nbclient<0.6.0,>=0.5.0 in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (0.5.3)
Requirement already satisfied: entrypoints>=0.2.2 in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (0.3)
Requirement already satisfied: jupyterlab-pygments in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (0.1.2)
Requirement already satisfied: bleach in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (3.3.0)
Requirement already satisfied: mistune<2,>=0.8.1 in /opt/conda/lib/python3.8/site-packages (from nbconvert->notebook) (0.8.4)
Requirement already satisfied: nest-asyncio in /opt/conda/lib/python3.8/site-packages (from nbclient<0.6.0,>=0.5.0->nbconvert->notebook) (1.5.1)
Requirement already satisfied: async-generator in /opt/conda/lib/python3.8/site-packages (from nbclient<0.6.0,>=0.5.0->nbconvert->notebook) (1.10)
Requirement already satisfied: jsonschema!=2.5.0,>=2.4 in /opt/conda/lib/python3.8/site-packages (from nbformat->notebook) (3.0.2)
Requirement already satisfied: pyrsistent>=0.14.0 in /opt/conda/lib/python3.8/site-packages (from jsonschema!=2.5.0,>=2.4->nbformat->notebook) (0.17.3)
Requirement already satisfied: webencodings in /opt/conda/lib/python3.8/site-packages (from bleach->nbconvert->notebook) (0.5.1)
Collecting mpmath>=0.19
  Downloading mpmath-1.2.1-py3-none-any.whl (532 kB)
Building wheels for collected packages: gsutil, crcmod, gcs-oauth2-boto-plugin, retry-decorator, attr, pyu2f
  Building wheel for gsutil (setup.py): started
  Building wheel for gsutil (setup.py): finished with status 'done'
  Created wheel for gsutil: filename=gsutil-4.67-py3-none-any.whl size=3695744 sha256=63ba42c4833b4632ad9af17086d5ca98dd4dac54acef32396e590590f130ee2d
  Stored in directory: /tmp/pip-ephem-wheel-cache-gumrwvea/wheels/19/a0/a4/3360fe0d106c606692289c13c83b815ae0b77a95f39e406743
  Building wheel for crcmod (setup.py): started
  Building wheel for crcmod (setup.py): finished with status 'done'
  Created wheel for crcmod: filename=crcmod-1.7-cp38-cp38-linux_x86_64.whl size=36048 sha256=edb04abb94e247d62bfd97dcd8a4d81bcfea994b60fac465d0d64d13d597c6b2
  Stored in directory: /tmp/pip-ephem-wheel-cache-gumrwvea/wheels/ca/5a/02/f3acf982a026f3319fb3e798a8dca2d48fafee7761788562e9
  Building wheel for gcs-oauth2-boto-plugin (setup.py): started
  Building wheel for gcs-oauth2-boto-plugin (setup.py): finished with status 'done'
  Created wheel for gcs-oauth2-boto-plugin: filename=gcs_oauth2_boto_plugin-2.7-py3-none-any.whl size=23202 sha256=51a0b204ee434dc3fca736ea5a023d67645dd17e9dd2df2dc9081f91018dfcf8
  Stored in directory: /tmp/pip-ephem-wheel-cache-gumrwvea/wheels/da/9a/7a/6d71b0db801fc601f42c3c70d009aa2f441089d2f690cf1123
  Building wheel for retry-decorator (setup.py): started
  Building wheel for retry-decorator (setup.py): finished with status 'done'
  Created wheel for retry-decorator: filename=retry_decorator-1.1.1-py2.py3-none-any.whl size=3640 sha256=bfa5eaa77660dad283b3e216fb2e172b3ef03ba7f12b31691a95e8c483420299
  Stored in directory: /tmp/pip-ephem-wheel-cache-gumrwvea/wheels/1e/bb/cb/5d7a05561d7ec60b8c0dc65f156a33909a3eb5c56340959fa9
  Building wheel for attr (setup.py): started
  Building wheel for attr (setup.py): finished with status 'done'
  Created wheel for attr: filename=attr-0.3.1-py3-none-any.whl size=2458 sha256=9cfeb7b4cefbf47630e6141a670c7193b82e408cf6adcf5574f433b2253b5087
  Stored in directory: /tmp/pip-ephem-wheel-cache-gumrwvea/wheels/47/53/81/061bfd275ab8eb923cfe874f1f6cbe1e607092df09d606c982
  Building wheel for pyu2f (setup.py): started
  Building wheel for pyu2f (setup.py): finished with status 'done'
  Created wheel for pyu2f: filename=pyu2f-0.1.5-py3-none-any.whl size=39388 sha256=a225a73c51fd6ca71d2ad34f63654d886b0dbf648b0edf8651033b84df2068b6
  Stored in directory: /tmp/pip-ephem-wheel-cache-gumrwvea/wheels/8d/38/8f/378b4491d760a176f261d56310fcb051e53090a894534acbf0
Successfully built gsutil crcmod gcs-oauth2-boto-plugin retry-decorator attr pyu2f
Installing collected packages: pyasn1, rsa, pyu2f, pyasn1-modules, oauthlib, httplib2, cachetools, retry-decorator, requests-oauthlib, Pillow, pbr, oauth2client, numpy, mpmath, google-reauth, google-auth, fasteners, boto, tensorboard-plugin-wit, tensorboard-data-server, sympy, monotonic, mock, google-auth-oauthlib, google-apitools, gcs-oauth2-boto-plugin, crcmod, attr, argcomplete, thop, tensorboard, seaborn, opencv-python, gsutil, coremltools
  Attempting uninstall: numpy
    Found existing installation: numpy 1.20.1
    Uninstalling numpy-1.20.1:
      Successfully uninstalled numpy-1.20.1
  Attempting uninstall: mock
    Found existing installation: mock 4.0.3
    Uninstalling mock-4.0.3:
      Successfully uninstalled mock-4.0.3
  Attempting uninstall: tensorboard
    Found existing installation: tensorboard 1.15.9999+nv
    Uninstalling tensorboard-1.15.9999+nv:
      Successfully uninstalled tensorboard-1.15.9999+nv
Successfully installed Pillow-8.3.1 argcomplete-1.12.3 attr-0.3.1 boto-2.49.0 cachetools-4.2.2 coremltools-4.1 crcmod-1.7 fasteners-0.16.3 gcs-oauth2-boto-plugin-2.7 google-apitools-0.5.32 google-auth-1.35.0 google-auth-oauthlib-0.4.6 google-reauth-0.1.1 gsutil-4.67 httplib2-0.19.1 mock-2.0.0 monotonic-1.6 mpmath-1.2.1 numpy-1.19.5 oauth2client-4.1.3 oauthlib-3.1.1 opencv-python-4.5.3.56 pbr-5.6.0 pyasn1-0.4.8 pyasn1-modules-0.2.8 pyu2f-0.1.5 requests-oauthlib-1.3.0 retry-decorator-1.1.1 rsa-4.7.2 seaborn-0.11.2 sympy-1.8 tensorboard-2.6.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.0 thop-0.0.31.post2005241907
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
Removing intermediate container fbd2daff3bce
 ---> bfb41e4d8ad3
Step 7/11 : RUN pip install --no-cache -U torch torchvision numpy
 ---> Running in 3466d9b76920
Requirement already satisfied: torch in /opt/conda/lib/python3.8/site-packages (1.9.0a0+2ecb2c7)
Collecting torch
  Downloading torch-1.9.0-cp38-cp38-manylinux1_x86_64.whl (831.4 MB)
Requirement already satisfied: torchvision in /opt/conda/lib/python3.8/site-packages (0.9.0a0)
Collecting torchvision
  Downloading torchvision-0.10.0-cp38-cp38-manylinux1_x86_64.whl (22.1 MB)
Requirement already satisfied: numpy in /opt/conda/lib/python3.8/site-packages (1.19.5)
Collecting numpy
  Downloading numpy-1.21.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (15.8 MB)
Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.8/site-packages (from torch) (3.7.4.3)
Requirement already satisfied: pillow>=5.3.0 in /opt/conda/lib/python3.8/site-packages (from torchvision) (8.3.1)
Installing collected packages: torch, numpy, torchvision
  Attempting uninstall: torch
    Found existing installation: torch 1.9.0a0+2ecb2c7
    Uninstalling torch-1.9.0a0+2ecb2c7:
      Successfully uninstalled torch-1.9.0a0+2ecb2c7
  Attempting uninstall: numpy
    Found existing installation: numpy 1.19.5
    Uninstalling numpy-1.19.5:
      Successfully uninstalled numpy-1.19.5
  Attempting uninstall: torchvision
    Found existing installation: torchvision 0.9.0a0
    Uninstalling torchvision-0.9.0a0:
      Successfully uninstalled torchvision-0.9.0a0
Successfully installed numpy-1.21.2 torch-1.9.0 torchvision-0.10.0
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
torchtext 0.10.0a0 requires torch==1.9.0a0+2ecb2c7, but you have torch 1.9.0 which is incompatible.
coremltools 4.1 requires numpy<1.20,>=1.14.5, but you have numpy 1.21.2 which is incompatible.
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
Removing intermediate container 3466d9b76920
 ---> 65d44ff09c01
Step 8/11 : RUN mkdir -p /usr/src/app
 ---> Running in 7266a2278dee
Removing intermediate container 7266a2278dee
 ---> 59676fe203ef
Step 9/11 : WORKDIR /usr/src/app
 ---> Running in 69ee5e33f563
Removing intermediate container 69ee5e33f563
 ---> a19174ecf06e
Step 10/11 : COPY . /usr/src/app
 ---> f7bccdca23f2
Step 11/11 : ENV HOME=/usr/src/app
 ---> Running in 2056bd13efb0
Removing intermediate container 2056bd13efb0
 ---> 89ed36fa86ba
Successfully built 89ed36fa86ba
Successfully tagged yolo:latest

$ docker run --rm -it --gpus all --ipc=host -v /sys:/sys -v $(realpath dataset):/data yolo

=============
== PyTorch ==
=============

NVIDIA Release 21.05 (build 22595835)
PyTorch Version 1.9.0a0+2ecb2c7

Container image Copyright (c) 2021, NVIDIA CORPORATION.  All rights reserved.

Copyright (c) 2014-2021 Facebook Inc.
Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert)
Copyright (c) 2012-2014 Deepmind Technologies    (Koray Kavukcuoglu)
Copyright (c) 2011-2012 NEC Laboratories America (Koray Kavukcuoglu)
Copyright (c) 2011-2013 NYU                      (Clement Farabet)
Copyright (c) 2006-2010 NEC Laboratories America (Ronan Collobert, Leon Bottou, Iain Melvin, Jason Weston)
Copyright (c) 2006      Idiap Research Institute (Samy Bengio)
Copyright (c) 2001-2004 Idiap Research Institute (Ronan Collobert, Samy Bengio, Johnny Mariethoz)
Copyright (c) 2015      Google Inc.
Copyright (c) 2015      Yangqing Jia
Copyright (c) 2013-2016 The Caffe contributors
All rights reserved.

NVIDIA Deep Learning Profiler (dlprof) Copyright (c) 2021, NVIDIA CORPORATION.  All rights reserved.

Various files include modifications (c) NVIDIA CORPORATION.  All rights reserved.

This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license

ERROR: This container was built for NVIDIA Driver Release 465.19 or later, but
       version 450.142.00 was detected and compatibility mode is UNAVAILABLE.

       [[Forward compatibility was attempted on non supported HW (CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE) cuInit()=804]]

NOTE: MOFED driver for multi-node communication was not detected.
      Multi-node communication performance may be reduced.

root@b645b73cfe8e:~# mkdir runs
root@b645b73cfe8e:~# cp /data/dataset/coco.names runs
root@b645b73cfe8e:~# python3 -m torch.distributed.launch --nproc_per_node 1 train.py \
    --img-size 640 \
    --batch-size 1 \
    --epochs 10 \
    --device 0 \
    --data /data/dataset/coco.yaml \
    --weights yolov5s.pt

/opt/conda/lib/python3.8/site-packages/torch/distributed/launch.py:163: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
  logger.warn(
The module torch.distributed.launch is deprecated and going to be removed in future.Migrate to torch.distributed.run
WARNING:torch.distributed.run:--use_env is deprecated and will be removed in future releases.
 Please read local_rank from `os.environ('LOCAL_RANK')` instead.
INFO:torch.distributed.launcher.api:Starting elastic_operator with launch configs:
  entrypoint       : train.py
  min_nodes        : 1
  max_nodes        : 1
  nproc_per_node   : 1
  run_id           : none
  rdzv_backend     : static
  rdzv_endpoint    : 127.0.0.1:29500
  rdzv_configs     : {'rank': 0, 'timeout': 900}
  max_restarts     : 3
  monitor_interval : 5
  log_dir          : None
  metrics_cfg      : {}

INFO:torch.distributed.elastic.agent.server.local_elastic_agent:log directory set to: /tmp/torchelastic_91xdcp8a/none_oere_ov7
INFO:torch.distributed.elastic.agent.server.api:[default] starting workers for entrypoint: python3
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous'ing worker group
/opt/conda/lib/python3.8/site-packages/torch/distributed/elastic/utils/store.py:52: FutureWarning: This is an experimental API and will be changed in future.
  warnings.warn(
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous complete for workers. Result:
  restart_count=0
  master_addr=127.0.0.1
  master_port=29500
  group_rank=0
  group_world_size=1
  local_ranks=[0]
  role_ranks=[0]
  global_ranks=[0]
  role_world_sizes=[1]
  global_world_sizes=[1]

INFO:torch.distributed.elastic.agent.server.api:[default] Starting worker group
INFO:torch.distributed.elastic.multiprocessing:Setting worker0 reply file to: /tmp/torchelastic_91xdcp8a/none_oere_ov7/attempt_0/0/error.json
Downloading https://ultralytics.com/assets/Arial.ttf to /usr/src/app/Arial.ttf...
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 755k/755k [00:00<00:00, 3.12MB/s]
train: weights=yolov5s.pt, cfg=, data=/data/dataset/coco.yaml, hyp=data/hyps/hyp.scratch.yaml, epochs=10, batch_size=1, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, evolve=None, bucket=, cache=None, image_weights=False, device=0, multi_scale=False, single_cls=False, adam=False, sync_bn=False, workers=8, project=runs/train, entity=None, name=exp, exist_ok=False, quad=False, linear_lr=False, label_smoothing=0.0, upload_dataset=False, bbox_interval=-1, save_period=-1, artifact_alias=latest, local_rank=0, freeze=0, patience=30
github: skipping check (Docker image), for updates see https://github.com/ultralytics/yolov5
YOLOv5 🚀 v5.0-405-gfad57c2 torch 1.9.0+cu102 CUDA:0 (GeForce GTX 1660, 5941.5MB)

Added key: store_based_barrier_key:1 to store for rank: 0
Rank 0: Completed store-based barrier for 1 nodes.
hyperparameters: lr0=0.01, lrf=0.2, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs (RECOMMENDED)
TensorBoard: Start with 'tensorboard --logdir runs/train', view at http://localhost:6006/
Downloading https://github.com/ultralytics/yolov5/releases/download/v5.0/yolov5s.pt to yolov5s.pt...
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 14.1M/14.1M [00:01<00:00, 11.2MB/s]

Overriding model.yaml nc=80 with nc=2

                 from  n    params  module                                  arguments                     
  0                -1  1      3520  models.common.Focus                     [3, 32, 3]                    
  1                -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                
  2                -1  1     18816  models.common.C3                        [64, 64, 1]                   
  3                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               
  4                -1  3    156928  models.common.C3                        [128, 128, 3]                 
  5                -1  1    295424  models.common.Conv                      [128, 256, 3, 2]              
  6                -1  3    625152  models.common.C3                        [256, 256, 3]                 
  7                -1  1   1180672  models.common.Conv                      [256, 512, 3, 2]              
  8                -1  1    656896  models.common.SPP                       [512, 512, [5, 9, 13]]        
  9                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          
 10                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              
 11                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          
 12           [-1, 6]  1         0  models.common.Concat                    [1]                           
 13                -1  1    361984  models.common.C3                        [512, 256, 1, False]          
 14                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              
 15                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          
 16           [-1, 4]  1         0  models.common.Concat                    [1]                           
 17                -1  1     90880  models.common.C3                        [256, 128, 1, False]          
 18                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              
 19          [-1, 14]  1         0  models.common.Concat                    [1]                           
 20                -1  1    296448  models.common.C3                        [256, 256, 1, False]          
 21                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              
 22          [-1, 10]  1         0  models.common.Concat                    [1]                           
 23                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          
 24      [17, 20, 23]  1     18879  models.yolo.Detect                      [2, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model Summary: 283 layers, 7066239 parameters, 7066239 gradients, 16.4 GFLOPs

Transferred 356/362 items from yolov5s.pt
Scaled weight_decay = 0.0005
optimizer: SGD with parameter groups 59 weight, 62 weight (no decay), 62 bias
train: Scanning '/data/dataset/train.cache' images and labels... 2467 found, 0 missing, 420 empty, 0 corrupted: 100%|███████████████████████████████████| 2467/2467 [00:00<?, ?it/s]
train: Scanning '/data/dataset/train.cache' images and labels... 2467 found, 0 missing, 420 empty, 0 corrupted: 100%|███████████████████████████████████| 2467/2467 [00:00<?, ?it/s]
val: Scanning '/data/dataset/val.cache' images and labels... 353 found, 0 missing, 0 empty, 0 corrupted: 100%|████████████████████████████████████████████| 353/353 [00:00<?, ?it/s]
val: Scanning '/data/dataset/val.cache' images and labels... 353 found, 0 missing, 0 empty, 0 corrupted: 100%|████████████████████████████████████████████| 353/353 [00:00<?, ?it/s]
val: Scanning '/data/dataset/val.cache' images and labels... 353 found, 0 missing, 0 empty, 0 corrupted: 100%|████████████████████████████████████████████| 353/353 [00:00<?, ?it/s]
val: Scanning '/data/dataset/val.cache' images and labels... 353 found, 0 missing, 0 empty, 0 corrupted: 100%|████████████████████████████████████████████| 353/353 [00:00<?, ?it/s]

autoanchor: Analyzing anchors... anchors/target = 5.79, Best Possible Recall (BPR) = 1.0000
Image sizes 640 train, 640 val
Using 0 dataloader workers
Logging results to runs/train/exp
Starting training for 10 epochs...

     Epoch   gpu_mem       box       obj       cls    labels  img_size
       0/9    0.801G   0.09358   0.03068   0.02203         4       640:   0%|                                                                    | 1/2456 [00:03<2:03:33,  3.02s/it]Reducer buckets have been rebuilt in this iteration.
       0/9    0.885G   0.08627    0.0287   0.02207         0       640:   5%|███
zcswdt commented 3 years ago 
 Epoch   gpu_mem       box       obj       cls    labels  img_size
   0/9    0.801G   0.09358   0.03068   0.02203         4       640:   0%|                                                                    | 1/2456 [00:03<2:03:33,  3.02s/it]Reducer buckets have been rebuilt in this iteration.
   0/9    0.885G   0.08627    0.0287   0.02207         0       640:   5%|███

my  ubuntu 18.04.5
![image](https://user-images.githubusercontent.com/43515926/131817931-342cc395-6f78-42e4-b49d-0e0bfd0d4bd0.png)
iceisfun commented 3 years ago

I don't have any 18.04 machines left to test on.

zcswdt commented 3 years ago

I don't have any 18.04 machines left to test on.

Is there an official image that can be docker pull?

iceisfun commented 3 years ago

I would guess most people build a custom image, I do not use the provided Dockerfile as we add additional code to the project.

Building the default Dockerfile is easy to verify. Just to make sure I built it on two environments (ubuntu 20.04 server and 20.04 desktop)

If you cannot docker pull and/or apt update/install you might have other issues not related to the provided Dockerfile or code in this repo?

Maybe docker run --rm -it nvcr.io/nvidia/pytorch:21.06-py3 and start running commands one at a time to debug. You should be able to run things like docker pull, git clone, apt update, apt install pip3 install -r requirements.txt, etc

Also if you have another machine to test on it might be helpful.

glenn-jocher commented 3 years ago

@zcswdt @iceisfun see Docker Quickstart guide: https://docs.ultralytics.com/yolov5/environments/docker_image_quickstart_tutorial/

Usage examples are also displayed in the Dockerfile comments: https://github.com/ultralytics/yolov5/blob/fad57c29cd27c0fcbc0038b7b7312b9b6ef922a8/Dockerfile#L28-L52

iceisfun commented 3 years ago

@glenn-jocher Sorry, I did not know about that. I'm still not sure what caused the failure to build from scratch.

zcswdt commented 3 years ago

@zcswdt @iceisfun see Docker Quickstart guide: https://docs.ultralytics.com/yolov5/environments/docker_image_quickstart_tutorial/

Usage examples are also displayed in the Dockerfile comments: https://github.com/ultralytics/yolov5/blob/fad57c29cd27c0fcbc0038b7b7312b9b6ef922a8/Dockerfile#L28-L52

image

I pulled the image and executed docker pull ultralytics/yolov5:latest, but an error was reported when running docker run. image

And execute after entering the container, nvidia-smi, no graphics card information image

glenn-jocher commented 3 years ago

@zcswdt see https://docs.ultralytics.com/yolov5/environments/docker_image_quickstart_tutorial/ for Docker requirements.

github-actions[bot] commented 2 years ago

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

Access additional YOLOv5 🚀 resources:

Access additional Ultralytics ⚡ resources:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐!