-
大小: 49.27MB文件类型: .gz金币: 1下载: 0 次发布日期: 2023-08-08
- 语言: 其他
- 标签: EfficientNet PyTorch 图像分类 深度学习
资源简介
EfficientNet是目前图像分类中最好的网络之一了,参数数量小(较VGG和Inception都小好几倍),运行速度快。由于github上下载参数文件速度奇慢。本资源打包已下载的efficientnet-b3参数文件,并稍微修改了源码以允许本地参数文件加载,节省各位的时间,供各位参考学习。
代码片段和文件信息
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Note: To use the ‘upload‘ functionality of this file you must:
# $ pipenv install twine --dev
import io
import os
import sys
from shutil import rmtree
from setuptools import find_packages setup Command
# Package meta-data.
NAME = ‘efficientnet_pytorch‘
DEscriptION = ‘EfficientNet implemented in PyTorch.‘
URL = ‘https://github.com/lukemelas/efficientnet_pytorch‘
EMAIL = ‘lmelaskyriazi@college.harvard.edu‘
AUTHOR = ‘Luke‘
REQUIRES_PYTHON = ‘>=3.5.0‘
VERSION = ‘0.5.1‘
# What packages are required for this module to be executed?
REQUIRED = [
‘torch‘
]
# What packages are optional?
EXTRAS = {
# ‘fancy feature‘: [‘django‘]
}
# The rest you shouldn‘t have to touch too much :)
# ------------------------------------------------
# Except perhaps the License and Trove Classifiers!
# If you do change the License remember to change the Trove Classifier for that!
here = os.path.abspath(os.path.dirname(__file__))
# Import the README and use it as the long-description.
# Note: this will only work if ‘README.md‘ is present in your MANIFEST.in file!
try:
with io.open(os.path.join(here ‘README.md‘) encoding=‘utf-8‘) as f:
long_description = ‘\n‘ + f.read()
except FileNotFoundError:
long_description = DEscriptION
# Load the package‘s __version__.py module as a dictionary.
about = {}
if not VERSION:
project_slug = NAME.lower().replace(“-“ “_“).replace(“ “ “_“)
with open(os.path.join(here project_slug ‘__version__.py‘)) as f:
exec(f.read() about)
else:
about[‘__version__‘] = VERSION
class UploadCommand(Command):
“““Support setup.py upload.“““
description = ‘Build and publish the package.‘
user_options = []
@staticmethod
def status(s):
“““Prints things in bold.“““
print(‘\033[1m{0}\033[0m‘.format(s))
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
try:
self.status(‘Removing previous builds…‘)
rmtree(os.path.join(here ‘dist‘))
except OSError:
pass
self.status(‘Building Source and Wheel (universal) distribution…‘)
os.system(‘{0} setup.py sdist bdist_wheel --universal‘.format(sys.executable))
self.status(‘Uploading the package to PyPI via Twine…‘)
os.system(‘twine upload dist/*‘)
self.status(‘Pushing git tags…‘)
os.system(‘git tag v{0}‘.format(about[‘__version__‘]))
os.system(‘git push --tags‘)
sys.exit()
# Where the magic happens:
setup(
name=NAME
version=about[‘__version__‘]
description=DEscriptION
long_description=long_description
long_description_content_type=‘text/markdown‘
author=AUTHOR
author_email=EMAIL
python_requires=REQUIRES_PYTHON
url=URL
packages=find_packages(exclude=[“tests“ “*.tests“ “*.tests.*“ “tests.*“])
# py_modules=[‘model‘] # If your package is a single
相关资源
- pytorch_yolov3_2.zip
- 地基云分类相关文献
- gpt2_chinese_poetry.rar
- pytorch .pt格式的MNIST数据集
- PyTorch Recipes A Problem-Solution Approach 20
- 深度学习框架-PyTorch: 入门与实践(陈
- knowledge_representation_pytorch.zip
- opencv SVM图分类训练图片和测试图片
- Deep Reinforcement Learning Hands-On pdf
- 交通标志数据集分类和GAN.zip
- BEGAN-pyTorch实现
- torch-1.4.0+cpu-cp36-cp36m-win_amd64.whl
- Darknet53-pytorch
- 目标检测模型YOLOv1-v3系列,ssd的pyto
- 《PyTorch深度学习实战侯宜军 著》&《
- 深度学习框架PyTorch:入门与实践.陈云
- pytorch resnet 152 模型参数数据
- 深度学习框架Pytorch 入门与实践高清
- 稀疏字典表示、OMP算法高光谱图像分
- NLP之pytorch实战含pdf+源码+中文笔记
- vgg16_reducedfc.pth
- 动手学深度学习Pytorch版.zip
- PyTorch深度学习.pdf
- 深度学习之PyTorch实战计算机视觉
- Natural_Language_Processing_with_PyTorch.pdf
- 深度学习框架PyTorch:入门与实践 PD
- pytorch tutorials v1.0.0.dev20181002 官方文档
- 深度学习框架PyTorch:入门与实践陈云
- opencv+svm实现图像分类代码+训练图片
- 卷积神经网络CNN进行图像分类
评论
共有 条评论