def test_info(self):
if not torch.cuda.is_available():
return
from mmcv.ops import get_compiler_version, get_compiling_cuda_version
cv = get_compiler_version()
ccv = get_compiling_cuda_version()
assert cv is not None
assert ccv is not None
def collect_env():
"""Collect the information of the running environments."""
env_info = {}
env_info['sys.platform'] = sys.platform
env_info['Python'] = sys.version.replace('\n', '')
cuda_available = torch.cuda.is_available()
env_info['CUDA available'] = cuda_available
if cuda_available:
if mmcv.__version__ < '1.3.11':
from mmcv.utils.parrots_wrapper import CUDA_HOME
else:
from mmcv.utils.parrots_wrapper import _get_cuda_home
CUDA_HOME = _get_cuda_home()
env_info['CUDA_HOME'] = CUDA_HOME
if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
try:
nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
nvcc = subprocess.check_output(
'"{}" -V | tail -n1'.format(nvcc), shell=True)
nvcc = nvcc.decode('utf-8').strip()
except subprocess.SubprocessError:
nvcc = 'Not Available'
env_info['NVCC'] = nvcc
devices = defaultdict(list)
for k in range(torch.cuda.device_count()):
devices[torch.cuda.get_device_name(k)].append(str(k))
for devname, devids in devices.items():
env_info['GPU ' + ','.join(devids)] = devname
gcc = subprocess.check_output('gcc --version | head -n1', shell=True)
gcc = gcc.decode('utf-8').strip()
env_info['GCC'] = gcc
env_info['PyTorch'] = torch.__version__
env_info['PyTorch compiling details'] = get_build_config()
env_info['TorchVision'] = torchvision.__version__
env_info['OpenCV'] = cv2.__version__
env_info['MMCV'] = mmcv.__version__
env_info['MMGen'] = f'{ mmgen.__version__ }+{get_git_hash()[:7]}'
try:
from mmcv.ops import get_compiler_version, get_compiling_cuda_version
env_info['MMCV Compiler'] = get_compiler_version()
env_info['MMCV CUDA Compiler'] = get_compiling_cuda_version()
except ImportError:
env_info['MMCV Compiler'] = 'n/a'
env_info['MMCV CUDA Compiler'] = 'n/a'
return env_info
def collect_env():
"""Collect the information of the running environments."""
env_info = {}
env_info['sys.platform'] = sys.platform
env_info['Python'] = sys.version.replace('\n', '')
cuda_available = torch.cuda.is_available()
env_info['CUDA available'] = cuda_available
if cuda_available:
from torch.utils.cpp_extension import CUDA_HOME
env_info['CUDA_HOME'] = CUDA_HOME
if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
try:
nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
nvcc = subprocess.check_output(
f'"{nvcc}" -V | tail -n1', shell=True)
nvcc = nvcc.decode('utf-8').strip()
except subprocess.SubprocessError:
nvcc = 'Not Available'
env_info['NVCC'] = nvcc
devices = defaultdict(list)
for k in range(torch.cuda.device_count()):
devices[torch.cuda.get_device_name(k)].append(str(k))
for name, devids in devices.items():
env_info['GPU ' + ','.join(devids)] = name
gcc = subprocess.check_output('gcc --version | head -n1', shell=True)
gcc = gcc.decode('utf-8').strip()
env_info['GCC'] = gcc
env_info['PyTorch'] = torch.__version__
env_info['PyTorch compiling details'] = get_build_config()
env_info['TorchVision'] = torchvision.__version__
env_info['OpenCV'] = cv2.__version__
env_info['MMCV'] = mmcv.__version__
env_info['MMDetection'] = mmdet.__version__,
from mmcv.ops import get_compiler_version, get_compiling_cuda_version
env_info['MMDetection Compiler'] = get_compiler_version()
env_info['MMDetection CUDA Compiler'] = get_compiling_cuda_version()
return env_info
def collect_env():
"""Collect the information of the running environments.
Returns:
dict: The environment information. The following fields are contained.
- sys.platform: The variable of ``sys.platform``.
- Python: Python version.
- CUDA available: Bool, indicating if CUDA is available.
- GPU devices: Device type of each GPU.
- CUDA_HOME (optional): The env var ``CUDA_HOME``.
- NVCC (optional): NVCC version.
- GCC: GCC version, "n/a" if GCC is not installed.
- PyTorch: PyTorch version.
- PyTorch compiling details: The output of \
``torch.__config__.show()``.
- TorchVision (optional): TorchVision version.
- OpenCV: OpenCV version.
- MMCV: MMCV version.
- MMCV Compiler: The GCC version for compiling MMCV ops.
- MMCV CUDA Compiler: The CUDA version for compiling MMCV ops.
"""
env_info = {}
env_info['sys.platform'] = sys.platform
env_info['Python'] = sys.version.replace('\n', '')
cuda_available = torch.cuda.is_available()
env_info['CUDA available'] = cuda_available
if cuda_available:
devices = defaultdict(list)
for k in range(torch.cuda.device_count()):
devices[torch.cuda.get_device_name(k)].append(str(k))
for name, device_ids in devices.items():
env_info['GPU ' + ','.join(device_ids)] = name
from mmcv.utils.parrots_wrapper import CUDA_HOME
env_info['CUDA_HOME'] = CUDA_HOME
if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
try:
nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
nvcc = subprocess.check_output(f'"{nvcc}" -V | tail -n1',
shell=True)
nvcc = nvcc.decode('utf-8').strip()
except subprocess.SubprocessError:
nvcc = 'Not Available'
env_info['NVCC'] = nvcc
try:
gcc = subprocess.check_output('gcc --version | head -n1', shell=True)
gcc = gcc.decode('utf-8').strip()
env_info['GCC'] = gcc
except subprocess.CalledProcessError: # gcc is unavailable
env_info['GCC'] = 'n/a'
env_info['PyTorch'] = torch.__version__
env_info['PyTorch compiling details'] = get_build_config()
try:
import torchvision
env_info['TorchVision'] = torchvision.__version__
except ModuleNotFoundError:
pass
env_info['OpenCV'] = cv2.__version__
env_info['MMCV'] = mmcv.__version__
try:
from mmcv.ops import get_compiler_version, get_compiling_cuda_version
except ModuleNotFoundError:
env_info['MMCV Compiler'] = 'n/a'
env_info['MMCV CUDA Compiler'] = 'n/a'
else:
env_info['MMCV Compiler'] = get_compiler_version()
env_info['MMCV CUDA Compiler'] = get_compiling_cuda_version()
return env_info
!pip install Pillow==7.0.0 # kiểm tra xem việc thiết lập có ok hay chưa # Check Pytorch installation import torch, torchvision print(torch.__version__, torch.cuda.is_available()) # Check MMDetection installation import mmdet print(mmdet.__version__) # Check mmcv installation from mmcv.ops import get_compiling_cuda_version, get_compiler_version print(get_compiling_cuda_version()) print(get_compiler_version()) import copy import os.path as osp import mmcv import numpy as np import pickle from mmcv import Config from mmdet.apis import set_random_seed from mmdet.datasets.builder import DATASETS from mmdet.datasets.custom import CustomDataset from mmdet.apis import inference_detector, init_detector, show_result_pyplot from mmdet.datasets import build_dataset from mmdet.models import build_detector from mmdet.apis import train_detector
def collect_env():
"""Collect the information of the running environments.
Returns:
dict: The environment information. The following fields are contained.
- sys.platform: The variable of ``sys.platform``.
- Python: Python version.
- CUDA available: Bool, indicating if CUDA is available.
- GPU devices: Device type of each GPU.
- CUDA_HOME (optional): The env var ``CUDA_HOME``.
- NVCC (optional): NVCC version.
- GCC: GCC version, "n/a" if GCC is not installed.
- MSVC: Microsoft Virtual C++ Compiler version, Windows only.
- PyTorch: PyTorch version.
- PyTorch compiling details: The output of \
``torch.__config__.show()``.
- TorchVision (optional): TorchVision version.
- OpenCV: OpenCV version.
- MMCV: MMCV version.
- MMCV Compiler: The GCC version for compiling MMCV ops.
- MMCV CUDA Compiler: The CUDA version for compiling MMCV ops.
"""
env_info = {}
env_info['sys.platform'] = sys.platform
env_info['Python'] = sys.version.replace('\n', '')
cuda_available = torch.cuda.is_available()
env_info['CUDA available'] = cuda_available
if cuda_available:
devices = defaultdict(list)
for k in range(torch.cuda.device_count()):
devices[torch.cuda.get_device_name(k)].append(str(k))
for name, device_ids in devices.items():
env_info['GPU ' + ','.join(device_ids)] = name
from mmcv.utils.parrots_wrapper import _get_cuda_home
CUDA_HOME = _get_cuda_home()
env_info['CUDA_HOME'] = CUDA_HOME
if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
try:
nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
nvcc = subprocess.check_output(f'"{nvcc}" -V', shell=True)
nvcc = nvcc.decode('utf-8').strip()
release = nvcc.rfind('Cuda compilation tools')
build = nvcc.rfind('Build ')
nvcc = nvcc[release:build].strip()
except subprocess.SubprocessError:
nvcc = 'Not Available'
env_info['NVCC'] = nvcc
try:
# Check C++ Compiler.
# For Unix-like, sysconfig has 'CC' variable like 'gcc -pthread ...',
# indicating the compiler used, we use this to get the compiler name
import sysconfig
cc = sysconfig.get_config_var('CC')
if cc:
cc = osp.basename(cc.split()[0])
cc_info = subprocess.check_output(f'{cc} --version', shell=True)
env_info['GCC'] = cc_info.decode('utf-8').partition(
'\n')[0].strip()
else:
# on Windows, cl.exe is not in PATH. We need to find the path.
# distutils.ccompiler.new_compiler() returns a msvccompiler
# object and after initialization, path to cl.exe is found.
import locale
from distutils.ccompiler import new_compiler
ccompiler = new_compiler()
ccompiler.initialize()
cc = subprocess.check_output(f'{ccompiler.cc}',
stderr=subprocess.STDOUT,
shell=True)
encoding = locale.getdefaultlocale()[1]
env_info['MSVC'] = cc.decode(encoding).partition('\n')[0].strip()
env_info['GCC'] = 'n/a'
except subprocess.CalledProcessError:
env_info['GCC'] = 'n/a'
env_info['PyTorch'] = torch.__version__
env_info['PyTorch compiling details'] = get_build_config()
try:
import torchvision
env_info['TorchVision'] = torchvision.__version__
except ModuleNotFoundError:
pass
env_info['OpenCV'] = cv2.__version__
env_info['MMCV'] = mmcv.__version__
try:
from mmcv.ops import get_compiler_version, get_compiling_cuda_version
except ModuleNotFoundError:
env_info['MMCV Compiler'] = 'n/a'
env_info['MMCV CUDA Compiler'] = 'n/a'
else:
env_info['MMCV Compiler'] = get_compiler_version()
env_info['MMCV CUDA Compiler'] = get_compiling_cuda_version()
return env_info
logger = mmcv.utils.get_logger(name=__file__, log_level=logging.DEBUG)
import matplotlib.pyplot as plt
import numpy as np
# Check Pytorch installation
import torch, torchvision
print(torch.__version__, torch.cuda.is_available())
# Check MMDetection installation
import mmdet
logger.debug(f'mmdet.version={mmdet.__version__}')
# Check mmcv installation
from mmcv.ops import get_compiling_cuda_version, get_compiler_version
logger.debug(get_compiling_cuda_version())
logger.debug(get_compiler_version())
from pprint import pprint, pformat
from mmdet.datasets import build_dataset
from mmdet.apis import train_detector
from mmcv import Config
from mmdet.apis import set_random_seed
from pathlib import Path
import os.path as osp
import os
import mmcv
from mmcv.runner import load_checkpoint
from mmdet.apis import inference_detector, show_result_pyplot
from mmdet.models import build_detector
