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pig-instance-segmentation

https://github.com/zijihu/pig-instance-segmentation

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (6.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: zijihu
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 18.5 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

sys.platform: linux Python: 3.8.16 (default, Mar 2 2023, 03:21:46) [GCC 11.2.0] CUDA available: True GPU 0: NVIDIA GeForce RTX 3090 CUDAHOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.1, V11.1.105 GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.8.0 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v1.7.0 (Git Hash 7aed236906b1f7a05c0917e5257a1af05e9ff683) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute37,code=sm37;-gencode;arch=compute50,code=sm50;-gencode;arch=compute60,code=sm60;-gencode;arch=compute61,code=sm61;-gencode;arch=compute70,code=sm70;-gencode;arch=compute75,code=sm75;-gencode;arch=compute80,code=sm80;-gencode;arch=compute86,code=sm86;-gencode;arch=compute37,code=compute37 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLASINFO=mkl, BUILDTYPE=Release, CUDAVERSION=11.1, CUDNNVERSION=8.0.5, CXXCOMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXXFLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSEPTHREADPOOL -fopenmp -DNDEBUG -DUSEKINETO -DUSEFBGEMM -DUSEQNNPACK -DUSEPYTORCHQNNPACK -DUSEXNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACKINFO=mkl, PERFWITHAVX=1, PERFWITHAVX2=1, PERFWITHAVX512=1, TORCHVERSION=1.8.0, USECUDA=ON, USECUDNN=ON, USEEXCEPTIONPTR=1, USEGFLAGS=OFF, USEGLOG=OFF, USEMKL=ON, USEMKLDNN=ON, USEMPI=OFF, USENCCL=ON, USENNPACK=ON, USEOPENMP=ON,

TorchVision: 0.9.0

OpenCV: 4.6.0

MMCV: 1.7.1

MMCV Compiler: GCC 7.3

MMCV CUDA Compiler: 11.1

MMDetection: 2.28.2+

数据集百度网盘下载链接 链接：https://pan.baidu.com/s/1X4DuWucPE7cgkxh8raj17A?pwd=pigs 提取码：pigs

data下载放到项目根目录data文件

workdirs 下载解压放到 workdirs目录

``` 2023-07-24 07:10:21,248 - mmdet - INFO - Distributed training: False 2023-07-24 07:10:21,671 - mmdet - INFO - Config: datasettype = 'CocoDataset' dataroot = 'data/qiangjicoco/' imgnormcfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], torgb=True) trainpipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', withbbox=True, withmask=True), dict(type='Resize', imgscale=(1920, 1080), keepratio=True), dict(type='RandomFlip', flipratio=0.5), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], torgb=True), dict(type='Pad', sizedivisor=32), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gtbboxes', 'gtlabels', 'gtmasks']) ] testpipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', imgscale=(1920, 1080), flip=False, transforms=[ dict(type='Resize', keepratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], torgb=True), dict(type='Pad', size_divisor=32), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ])

```

Owner

  • Login: zijihu
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - name: "MMDetection Contributors"
title: "OpenMMLab Detection Toolbox and Benchmark"
date-released: 2018-08-22
url: "https://github.com/open-mmlab/mmdetection"
license: Apache-2.0

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Dependencies

requirements/albu.txt pypi
  • albumentations >=0.3.2
requirements/build.txt pypi
  • cython *
  • numpy *
requirements/docs.txt pypi
  • docutils ==0.16.0
  • markdown >=3.4.0
  • myst-parser *
  • sphinx ==5.3.0
  • sphinx-copybutton *
  • sphinx_markdown_tables >=0.0.17
  • sphinx_rtd_theme *
requirements/mminstall.txt pypi
  • mmcv-full >=1.3.17
requirements/optional.txt pypi
  • cityscapesscripts *
  • imagecorruptions *
  • scikit-learn *
requirements/readthedocs.txt pypi
  • mmcv *
  • scipy *
  • torch *
  • torchvision *
requirements/runtime.txt pypi
  • matplotlib *
  • numpy *
  • pycocotools *
  • scipy *
  • six *
  • terminaltables *
requirements/tests.txt pypi
  • asynctest * test
  • codecov * test
  • flake8 * test
  • interrogate * test
  • isort ==4.3.21 test
  • kwarray * test
  • onnx ==1.7.0 test
  • onnxruntime >=1.8.0 test
  • protobuf <=3.20.1 test
  • pytest * test
  • ubelt * test
  • xdoctest >=0.10.0 test
  • yapf * test
requirements.txt pypi
setup.py pypi