diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml new file mode 100644 index 0000000..f7cb92b --- /dev/null +++ b/.github/workflows/docs.yml @@ -0,0 +1,51 @@ +# Simple workflow for deploying static content to GitHub Pages +name: Deploy docs to Pages + +on: + # Runs on pushes targeting the default branch + push: + branches: ["master"] + + # Allows you to run this workflow manually from the Actions tab + workflow_dispatch: + +# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages +permissions: + contents: read + pages: write + id-token: write + +# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued. +# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete. +concurrency: + group: "pages" + cancel-in-progress: false + +jobs: + # Single deploy job since we're just deploying + deploy: + environment: + name: github-pages + url: ${{ steps.deployment.outputs.page_url }} + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Setup Pages + uses: actions/configure-pages@v3 + - name: Setup Python + uses: actions/setup-python@v3.1.4 + - name: Install requirements + run: pip install -r requirements.txt + working-directory: ./docs + - name: Build docs + run: make html + working-directory: ./docs + - name: Upload artifact + uses: actions/upload-pages-artifact@v1 + with: + # Upload entire repository + path: './docs/build/html/' + - name: Deploy to GitHub Pages + id: deployment + uses: actions/deploy-pages@v2 diff --git a/.gitignore b/.gitignore index abd78ed..26d218c 100644 --- a/.gitignore +++ b/.gitignore @@ -3,7 +3,6 @@ *.dSYM *.csv *.out -*.png *.so *.exe *.dll @@ -11,6 +10,10 @@ *.dylib *.pyc *~ +chart*.png +bad*.list +anchors.txt +counters_per_class.txt mnist/ caffe/ grasp/ @@ -19,6 +22,7 @@ opencv/ convnet/ decaf/ submission/ +dataset/ temp/ build/darknet/* @@ -29,6 +33,9 @@ vcpkg_installed/ !build/darknet/YoloWrapper.cs .fuse* *.weights +*.db +*.sqlite + build/*.cmake build/*.ninja build/*.txt @@ -53,9 +60,6 @@ Thumbs.db .vs/ .vscode/ -# Managed by CMake -#src/version.h - # Build artifacts lib/ share/ @@ -63,5 +67,168 @@ include/darknet/ uselib uselib_track darknet -lightNet +lightnet vcpkg/ + +docs/build/ + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..a97b960 --- /dev/null +++ b/LICENSE @@ -0,0 +1,12 @@ + YOLO LICENSE + Version 2, July 29 2016 + +THIS SOFTWARE LICENSE IS PROVIDED "ALL CAPS" SO THAT YOU KNOW IT IS SUPER +SERIOUS AND YOU DON'T MESS AROUND WITH COPYRIGHT LAW BECAUSE YOU WILL GET IN +TROUBLE HERE ARE SOME OTHER BUZZWORDS COMMONLY IN THESE THINGS WARRANTIES +LIABILITY CONTRACT TORT LIABLE CLAIMS RESTRICTION MERCHANTABILITY. NOW HERE'S +THE REAL LICENSE: + +0. Darknet is public domain. +1. Do whatever you want with it. +2. Stop emailing me about it! \ No newline at end of file diff --git a/Makefile b/Makefile index 43c23be..4d189b6 100644 --- a/Makefile +++ b/Makefile @@ -8,6 +8,7 @@ LIBSO=0 ZED_CAMERA=0 ZED_CAMERA_v2_8=0 +#* GPU=0, OPENCV=0 is not supported # set GPU=1 and CUDNN=1 to speedup on GPU # set CUDNN_HALF=1 to further speedup 3 x times (Mixed-precision on Tensor Cores) GPU: Volta, Xavier, Turing and higher # set AVX=1 and OPENMP=1 to speedup on CPU (if error occurs then set AVX=0) @@ -54,7 +55,7 @@ ARCH= -gencode arch=compute_86,code=[sm_86,compute_86] VPATH=./src/ -EXEC=lightNet +EXEC=lightnet OBJDIR=./obj/ ifeq ($(LIBSO), 1) diff --git a/README.md b/README.md index ddba184..80093fc 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ -# LightNet +# Lightnet -LightNet is a deep learning framework based on the popular darknet platform, designed to create efficient and high-speed Convolutional Neural Networks (CNNs) for computer vision tasks. The framework has been improved and optimized to provide a more versatile and powerful solution for various deep learning challenges. +lightnet is a deep learning framework based on the popular darknet platform, designed to create efficient and high-speed Convolutional Neural Networks (CNNs) for computer vision tasks. The framework has been improved and optimized to provide a more versatile and powerful solution for various deep learning challenges. ## Table of Contents @@ -65,12 +65,12 @@ You can find examples of using LightNet's features in the examples directory. Th ### Inference for Detection ``` -./lightNet detector [test/demo] data/bdd100k.data cfg/lightNet-BDD100K-1280x960.cfg weights/lightNet-BDD100K-1280x960.weights [image_name/video_name] +./lightnet detector [test/demo] data/bdd100k.data cfg/lightNet-BDD100K-1280x960.cfg weights/lightNet-BDD100K-1280x960.weights [image_name/video_name] ``` ### Inference for Segmentation ``` -./lightNet segmenter [test/demo] data/bdd100k-semseg.data cfg/lightSeg-BDD100K-laneMarker-1280x960.cfg weights/lightSeg-BDD100K-laneMarker-1280x960.weights [image_name/video_name] +./lightnet segmenter [test/demo] data/bdd100k-semseg.data cfg/lightSeg-BDD100K-laneMarker-1280x960.cfg weights/lightSeg-BDD100K-laneMarker-1280x960.weights [image_name/video_name] ``` ## Results @@ -85,4 +85,4 @@ You can find examples of using LightNet's features in the examples directory. Th ## License -LightNet is released under the same YOLO license as darknet. You are free to use, modify, and distribute the code as long as you retain the license notice. +lightnet is released under the same YOLO license as darknet. You are free to use, modify, and distribute the code as long as you retain the license notice. diff --git a/cfg/lightNet-BDD100K-640x640-scratch.cfg b/cfg/lightNet-BDD100K-640x640-scratch.cfg new file mode 100644 index 0000000..a455f84 --- /dev/null +++ b/cfg/lightNet-BDD100K-640x640-scratch.cfg @@ -0,0 +1,917 @@ +[net] +batch=8 +# subdivisions=1 +# width=1280 +# height=960 +width = 640 +height = 640 +channels=3 +momentum=0.9 +decay=0.0005 +angle=0 +saturation = 1.5 +exposure = 1.5 +hue=.1 + +learning_rate=0.001 +burn_in=500 +max_batches = 2625000 +policy=steps + +steps=437500, 875000, 1312500, 1750000 +scales=.5,.5,.5,.5 +gaussian_noise=1 +flip=1 + +##sparse=1 : 2:4 structured sparsity + +[convolutional] +batch_normalize=1 +filters=32 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=relu + + +################################## + +### ASPPCSP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +### ASPP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=3 +activation=relu + +[route] +layers=-4 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=5 +activation=relu + +[route] +layers=-1,-3,-5,-6 +### End ASPP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -10,-1 + +# 44 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu +### End ASPPCSP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 30 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + + +# 56 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 20 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=128 +activation=relu + +[route] +layers = -1,67 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=256 +activation=relu + +[route] +layers = -1,53 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +############################# + +# ============ End of Neck ============ # + +# ============ Head ============ # + + +# P3 +[route] +layers = 80 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=128 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=45 +#activation=linear +activation=logistic + +[yolo] +mask = 0,1,2 +anchors = 7, 14, 17, 21, 11, 38, 31, 40, 21, 84, 57, 69, 87,130, 148,198, 215,337 +classes=10 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +#random=1 +resize=1.5 +new_coords=1 +counters_per_class=8, 2, 2, 1, 2, 1, 8, 1, 8, 4 +cls_normalizer=0.25 +iou_normalizer=0.05 +iou_loss=ciou + +# P4 +[route] +layers = 91 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=45 +#activation=linear +activation=logistic + +[yolo] +mask = 3,4,5 +anchors = 7, 14, 17, 21, 11, 38, 31, 40, 21, 84, 57, 69, 87,130, 148,198, 215,337 +classes=10 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +counters_per_class=8, 2, 2, 1, 2, 1, 8, 1, 8, 4 +cls_normalizer=0.25 +iou_normalizer=0.05 +iou_loss=ciou + + +# P5 +[route] +layers = 102 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=45 +#activation=linear +activation=logistic + +[yolo] +mask = 6,7,8 +anchors = 7, 14, 17, 21, 11, 38, 31, 40, 21, 84, 57, 69, 87,130, 148,198, 215,337 +classes=10 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +counters_per_class=8, 2, 2, 1, 2, 1, 8, 1, 8, 4 +cls_normalizer=0.25 +iou_normalizer=0.05 +iou_loss=ciou + diff --git a/cfg/lightNet-crowdhuman-1024x768.cfg b/cfg/lightNet-crowdhuman-1024x768.cfg new file mode 100644 index 0000000..647e80d --- /dev/null +++ b/cfg/lightNet-crowdhuman-1024x768.cfg @@ -0,0 +1,909 @@ +[net] +batch=256 +subdivisions=16 +width=1024 +height=768 +channels=3 +momentum=0.9 +decay=0.0005 +angle=0 +saturation = 1.5 +exposure = 1.5 +hue=.1 + +learning_rate=0.001 +burn_in=50 +max_batches = 2000 +policy=steps + +steps=100,400,800,1600 +scales=.5,.5,.5,.5 +gaussian_noise=1 +flip=1 + +##sparse=1 : 2:4 structured sparsity + +[convolutional] +batch_normalize=1 +filters=32 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=relu + + +################################## + +### ASPPCSP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +### ASPP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=3 +activation=relu + +[route] +layers=-4 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=5 +activation=relu + +[route] +layers=-1,-3,-5,-6 +### End ASPP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -10,-1 + +# 44 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu +### End ASPPCSP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 30 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + + +# 56 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 20 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=128 +activation=relu + +[route] +layers = -1,67 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=256 +activation=relu + +[route] +layers = -1,53 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +############################# + +# ============ End of Neck ============ # + +# ============ Head ============ # + + +# P3 +[route] +layers = 80 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=128 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=21 +#activation=linear +activation=logistic + +[yolo] +mask = 0,1,2 +anchors = 8, 11, 20, 31, 34, 66, 64, 93, 54,184, 120,174, 97,334, 176,448, 344,564 +classes=2 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +#random=1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +# iou_loss=ciou + +# P4 +[route] +layers = 91 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=21 +#activation=linear +activation=logistic + +[yolo] +mask = 3,4,5 +anchors = 8, 11, 20, 31, 34, 66, 64, 93, 54,184, 120,174, 97,334, 176,448, 344,564 +classes=2 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +# iou_loss=ciou + + +# P5 +[route] +layers = 102 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=21 +#activation=linear +activation=logistic + +[yolo] +mask = 6,7,8 +anchors = 8, 11, 20, 31, 34, 66, 64, 93, 54,184, 120,174, 97,334, 176,448, 344,564 +classes=2 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .7 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +iou_loss=ciou + diff --git a/cfg/lightNet-crowdhuman-640x640.cfg b/cfg/lightNet-crowdhuman-640x640.cfg new file mode 100644 index 0000000..9101929 --- /dev/null +++ b/cfg/lightNet-crowdhuman-640x640.cfg @@ -0,0 +1,909 @@ +[net] +batch=64 +subdivisions=4 +width=640 +height=640 +channels=3 +momentum=0.9 +decay=0.0005 +angle=0 +saturation = 1.5 +exposure = 1.5 +hue=.1 + +learning_rate=0.001 +burn_in=500 +max_batches = 70000 +policy=steps + +steps=12000,24000,35000,50000 +scales=.5,.5,.5,.5 +gaussian_noise=1 +flip=1 + +##sparse=1 : 2:4 structured sparsity + +[convolutional] +batch_normalize=1 +filters=32 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=relu + + +################################## + +### ASPPCSP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +### ASPP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=3 +activation=relu + +[route] +layers=-4 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=5 +activation=relu + +[route] +layers=-1,-3,-5,-6 +### End ASPP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -10,-1 + +# 44 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu +### End ASPPCSP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 30 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + + +# 56 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 20 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=128 +activation=relu + +[route] +layers = -1,67 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=256 +activation=relu + +[route] +layers = -1,53 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +############################# + +# ============ End of Neck ============ # + +# ============ Head ============ # + + +# P3 +[route] +layers = 80 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=128 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=21 +#activation=linear +activation=logistic + +[yolo] +mask = 0,1,2 +anchors = 5, 10, 13, 29, 23, 62, 32,139, 52, 92, 54,232, 94,270, 109,436, 225,477 +classes=2 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +#random=1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +# iou_loss=ciou + +# P4 +[route] +layers = 91 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=21 +#activation=linear +activation=logistic + +[yolo] +mask = 3,4,5 +anchors = 5, 10, 13, 29, 23, 62, 32,139, 52, 92, 54,232, 94,270, 109,436, 225,477 +classes=2 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +# iou_loss=ciou + + +# P5 +[route] +layers = 102 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=21 +#activation=linear +activation=logistic + +[yolo] +mask = 6,7,8 +anchors = 5, 10, 13, 29, 23, 62, 32,139, 52, 92, 54,232, 94,270, 109,436, 225,477 +classes=2 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .7 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +iou_loss=ciou + diff --git a/cfg/lightNet-wider_face-1024x768.cfg b/cfg/lightNet-wider_face-1024x768.cfg new file mode 100644 index 0000000..d4c3367 --- /dev/null +++ b/cfg/lightNet-wider_face-1024x768.cfg @@ -0,0 +1,909 @@ +[net] +batch=256 +subdivisions=64 +width=1024 +height=768 +channels=3 +momentum=0.9 +decay=0.0005 +angle=0 +saturation = 1.5 +exposure = 1.5 +hue=.1 + +learning_rate=0.001 +burn_in=100 +max_batches = 1000 +policy=steps + +steps=50,200,400,800 +scales=.5,.5,.5,.5 +gaussian_noise=1 +flip=1 + +#sparse=1 : 2:4 structured sparsity + +[convolutional] +batch_normalize=1 +filters=32 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=relu + + +################################## + +### ASPPCSP ### +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +### ASPP ### +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=3 +activation=relu + +[route] +layers=-4 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=5 +activation=relu + +[route] +layers=-1,-3,-5,-6 +### End ASPP ### + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -10,-1 + +# 44 +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu +### End ASPPCSP ### + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 30 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + + +# 56 +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 20 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + + +[convolutional] +sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=128 +activation=relu + +[route] +layers = -1,67 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=256 +activation=relu + +[route] +layers = -1,53 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +############################# + +# ============ End of Neck ============ # + +# ============ Head ============ # + + +# P3 +[route] +layers = 80 + +[convolutional] +sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=128 +activation=relu + +[convolutional] +#sparse=1 +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 0,1,2 +anchors = 7, 8, 12, 16, 20, 28, 33, 45, 53, 70, 92,110, 151,187, 268,292, 451,446 +classes=1 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +#random=1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +# iou_loss=ciou + +# P4 +[route] +layers = 91 + +[convolutional] +sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=relu + +[convolutional] +#sparse=1 +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 3,4,5 +anchors = 7, 8, 12, 16, 20, 28, 33, 45, 53, 70, 92,110, 151,187, 268,292, 451,446 +classes=1 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +# iou_loss=ciou + + +# P5 +[route] +layers = 102 + +[convolutional] +sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=relu + +[convolutional] +#sparse=1 +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 6,7,8 +anchors = 7, 8, 12, 16, 20, 28, 33, 45, 53, 70, 92,110, 151,187, 268,292, 451,446 +classes=1 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +# iou_loss=ciou + diff --git a/cfg/lightNet-wider_face-640x640.cfg b/cfg/lightNet-wider_face-640x640.cfg new file mode 100644 index 0000000..45e2904 --- /dev/null +++ b/cfg/lightNet-wider_face-640x640.cfg @@ -0,0 +1,908 @@ +[net] +batch=8 +width=640 +height=640 +channels=3 +momentum=0.9 +decay=0.0005 +angle=0 +saturation = 1.5 +exposure = 1.5 +hue=.1 + +learning_rate=0.001 +burn_in=500 +max_batches = 483000 +policy=steps + +steps=24000,96000,192000,384000 +scales=.5,.5,.5,.5 +gaussian_noise=1 +flip=1 + +##sparse=1 : 2:4 structured sparsity + +[convolutional] +batch_normalize=1 +filters=32 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=2 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=relu + + +################################## + +### ASPPCSP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +### ASPP ### +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=3 +activation=relu + +[route] +layers=-4 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +dilation=5 +activation=relu + +[route] +layers=-1,-3,-5,-6 +### End ASPP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -10,-1 + +# 44 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu +### End ASPPCSP ### + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 30 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + + +# 56 +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[upsample] +stride=2 + +[route] +layers = 20 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=128 +activation=relu + +[route] +layers = -1,67 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=256 +activation=relu + +[route] +layers = -1,53 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[route] +layers=-2 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=relu + +[route] +layers = -1,-3,-5,-7 + +[convolutional] +#sparse=1 +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=relu + +############################# + +# ============ End of Neck ============ # + +# ============ Head ============ # + + +# P3 +[route] +layers = 80 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=128 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 0,1,2 +anchors = 4, 7, 7, 14, 12, 23, 20, 36, 32, 56, 54, 86, 84,145, 148,218, 254,338 +classes=1 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +#random=1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +iou_loss=ciou + +# P4 +[route] +layers = 91 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 3,4,5 +anchors = 4, 7, 7, 14, 12, 23, 20, 36, 32, 56, 54, 86, 84,145, 148,218, 254,338 +classes=1 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +iou_loss=ciou + + +# P5 +[route] +layers = 102 + +[convolutional] +#sparse=1 +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=relu + +[convolutional] +##sparse=1 +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 6,7,8 +anchors = 4, 7, 7, 14, 12, 23, 20, 36, 32, 56, 54, 86, 84,145, 148,218, 254,338 +classes=1 +num=9 +jitter=.3 +scale_x_y = 2.0 +ignore_thresh = .5 +truth_thresh = 1 +resize=1.5 +new_coords=1 +iou_normalizer=0.05 +iou_loss=ciou + diff --git a/cfg/yolov7x-wider_face.cfg b/cfg/yolov7x-wider_face.cfg new file mode 100644 index 0000000..bf597b9 --- /dev/null +++ b/cfg/yolov7x-wider_face.cfg @@ -0,0 +1,1152 @@ +[net] +# Testing +#batch=1 +#subdivisions=1 +# Training +batch=8 +subdivisions=4 +width=640 +height=640 +channels=3 +momentum=0.9 +decay=0.0005 +angle=0 +saturation = 1.5 +exposure = 1.5 +hue=.1 + +learning_rate=0.000261 +burn_in=1000 + +max_batches = 2000200 +policy=steps +steps=1600000,1800000 +scales=.1,.1 + + +# 0 +[convolutional] +batch_normalize=1 +filters=40 +size=3 +stride=1 +pad=1 +activation=swish + + +# 1 +[convolutional] +batch_normalize=1 +filters=80 +size=3 +stride=2 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=80 +size=3 +stride=1 +pad=1 +activation=swish + + +# 3 +[convolutional] +batch_normalize=1 +filters=160 +size=3 +stride=2 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 14 +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + + +[maxpool] +size=2 +stride=2 + +[convolutional] +batch_normalize=1 +filters=160 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-3 + +[convolutional] +batch_normalize=1 +filters=160 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=160 +size=3 +stride=2 +pad=1 +activation=swish + +# 20 +[route] +layers = -1,-4 + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 31 +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + + +[maxpool] +size=2 +stride=2 + +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-3 + +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=320 +size=3 +stride=2 +pad=1 +activation=swish + +# 37 +[route] +layers = -1,-4 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 48 +[convolutional] +batch_normalize=1 +filters=1280 +size=1 +stride=1 +pad=1 +activation=swish + + +[maxpool] +size=2 +stride=2 + +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-3 + +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=640 +size=3 +stride=2 +pad=1 +activation=swish + +# 54 +[route] +layers = -1,-4 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 65 +[convolutional] +batch_normalize=1 +filters=1280 +size=1 +stride=1 +pad=1 +activation=swish + +################################## + +### SPPCSP ### +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers = -2 + +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=640 +activation=swish + +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + +### SPP ### +[maxpool] +stride=1 +size=5 + +[route] +layers=-2 + +[maxpool] +stride=1 +size=9 + +[route] +layers=-4 + +[maxpool] +stride=1 +size=13 + +[route] +layers=-6,-5,-3,-1 +### End SPP ### + +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=640 +activation=swish + +[route] +layers = -1, -13 + +# 80 +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + + +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + +[upsample] +stride=2 + +[route] +layers = 48 + +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3 + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 96 +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + + +[convolutional] +batch_normalize=1 +filters=160 +size=1 +stride=1 +pad=1 +activation=swish + +[upsample] +stride=2 + +[route] +layers = 31 + +[convolutional] +batch_normalize=1 +filters=160 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3 + + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 112 +[convolutional] +batch_normalize=1 +filters=160 +size=1 +stride=1 +pad=1 +activation=swish + + +[maxpool] +size=2 +stride=2 + +[convolutional] +batch_normalize=1 +filters=160 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-3 + +[convolutional] +batch_normalize=1 +filters=160 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=160 +size=3 +stride=2 +pad=1 +activation=swish + +[route] +layers = -1,-4,96 + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 129 +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + + +[maxpool] +size=2 +stride=2 + +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-3 + +[convolutional] +batch_normalize=1 +filters=320 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=320 +size=3 +stride=2 +pad=1 +activation=swish + +[route] +layers = -1,-4,80 + + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=swish + +[route] +layers=-2 + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=swish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=swish + +[route] +layers = -1,-3,-5,-7,-9 + +# 146 +[convolutional] +batch_normalize=1 +filters=640 +size=1 +stride=1 +pad=1 +activation=swish + +############################# + +# ============ End of Neck ============ # + +# ============ Head ============ # + + +# P3 +[route] +layers = 112 + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=320 +activation=swish + +[convolutional] +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 0,1,2 +anchors = 4, 7, 7, 13, 12, 22, 19, 35, 31, 54, 52, 82, 80,139, 141,207, 258,346 +classes=1 +num=9 +jitter=.1 +scale_x_y = 2.0 +objectness_smooth=1 +ignore_thresh = .7 +truth_thresh = 1 +#random=1 +# resize=1.5 +iou_thresh=0.2 +iou_normalizer=0.05 +cls_normalizer=0.5 +obj_normalizer=1.0 +iou_loss=ciou +nms_kind=diounms +beta_nms=0.6 +new_coords=1 +max_delta=2 + + +# P4 +[route] +layers = 129 + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=640 +activation=swish + +[convolutional] +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 3,4,5 +anchors = 4, 7, 7, 13, 12, 22, 19, 35, 31, 54, 52, 82, 80,139, 141,207, 258,346 +classes=1 +num=9 +jitter=.1 +scale_x_y = 2.0 +objectness_smooth=1 +ignore_thresh = .7 +truth_thresh = 1 +#random=1 +# resize=1.5 +iou_thresh=0.2 +iou_normalizer=0.05 +cls_normalizer=0.5 +obj_normalizer=1.0 +iou_loss=ciou +nms_kind=diounms +beta_nms=0.6 +new_coords=1 +max_delta=2 + + +# P5 +[route] +layers = 146 + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=1280 +activation=swish + +[convolutional] +size=1 +stride=1 +pad=1 +filters=18 +#activation=linear +activation=logistic + +[yolo] +mask = 6,7,8 +anchors = 4, 7, 7, 13, 12, 22, 19, 35, 31, 54, 52, 82, 80,139, 141,207, 258,346 +classes=1 +num=9 +jitter=.1 +scale_x_y = 2.0 +objectness_smooth=1 +ignore_thresh = .7 +truth_thresh = 1 +#random=1 +# resize=1.5 +iou_thresh=0.2 +iou_normalizer=0.05 +cls_normalizer=0.5 +obj_normalizer=1.0 +iou_loss=ciou +nms_kind=diounms +beta_nms=0.6 +new_coords=1 +max_delta=2 \ No newline at end of file diff --git a/semseg.data b/data/bdd100k_semseg.data similarity 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'futura-normal' +font = 'Ubuntu' def make_labels(s): l = string.printable diff --git a/data/wider_face.data b/data/wider_face.data new file mode 100644 index 0000000..bc3a024 --- /dev/null +++ b/data/wider_face.data @@ -0,0 +1,5 @@ +classes = 1 +train = dataset/wider_face/data/WIDER_train/train.lst +valid = dataset/wider_face/data/WIDER_val/val.lst +names = data/wider_face.names +backup = weights \ No newline at end of file diff --git a/data/wider_face.names b/data/wider_face.names new file mode 100644 index 0000000..54429d9 --- /dev/null +++ b/data/wider_face.names @@ -0,0 +1 @@ +face \ No newline at end of file diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..d0c3cbf --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line, and also +# from the environment for the first two. +SPHINXOPTS ?= +SPHINXBUILD ?= sphinx-build +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 0000000..747ffb7 --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,35 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=source +set BUILDDIR=build + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.https://www.sphinx-doc.org/ + exit /b 1 +) + +if "%1" == "" goto help + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% + +:end +popd diff --git a/docs/requirements.txt b/docs/requirements.txt new file mode 100644 index 0000000..52d8ed4 --- /dev/null +++ b/docs/requirements.txt @@ -0,0 +1,3 @@ +Sphinx==6.2.1 +sphinx-rtd-theme==1.2.2 +myst-parser==2.0.0 diff --git a/docs/source/conf.py b/docs/source/conf.py new file mode 100644 index 0000000..9dae425 --- /dev/null +++ b/docs/source/conf.py @@ -0,0 +1,28 @@ +# Configuration file for the Sphinx documentation builder. +# +# For the full list of built-in configuration values, see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +# -- Project information ----------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information + +project = 'lightnet' +copyright = '2023, yunkai1841' +author = 'yunkai1841' + +# -- General configuration --------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration + +extensions = ['myst_parser', 'sphinx_rtd_theme'] + +templates_path = ['_templates'] +exclude_patterns = [] + +# language = 'ja' +language = 'en' + +# -- Options for HTML output ------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output + +html_theme = 'sphinx_rtd_theme' +html_static_path = ['_static'] diff --git a/docs/source/index.rst b/docs/source/index.rst new file mode 100644 index 0000000..c1cdfc6 --- /dev/null +++ b/docs/source/index.rst @@ -0,0 +1,22 @@ +.. lightnet documentation master file, created by + sphinx-quickstart on Sat Jun 17 14:45:26 2023. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +Welcome to lightnet's documentation! +==================================== + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + installation + training + + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/docs/source/installation.md b/docs/source/installation.md new file mode 100644 index 0000000..62b1ea1 --- /dev/null +++ b/docs/source/installation.md @@ -0,0 +1,24 @@ +# Installation + +## Requirements + +Currently, NVIDIA GPUs are required to use this library. + +- NVIDIA driver, CUDA toolkit is required. Please refer to [NVIDIA CUDA Installation Guide](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html) for installation. +- OpenCV is required for processing images. +- SQLite3 is required for training logs. + +```bash +sudo apt install libopencv-dev libsqlite3-dev +``` + +## Build + +```bash +git clone https://github.com/yunkai1841/lightnet.git +cd lightnet +make -j 4 +``` + +build artifact will be located at `./lightnet` + diff --git a/docs/source/training.md b/docs/source/training.md new file mode 100644 index 0000000..c3b0f83 --- /dev/null +++ b/docs/source/training.md @@ -0,0 +1,148 @@ +# Training + +## Prepare the data + +### directory structure + +Your need to prepare training data and validation data in darknet format. The directory structure should be like this: + +``` +base_dir +├── train +│   ├── JPEGImages +│   │   ├── 000001.jpg +│   │   ├── 000002.jpg +│   │   ├── 000003.jpg +| | ... +│   ├── labels +│   │   ├── 000001.txt +│   │   ├── 000002.txt +│   │   ├── 000003.txt +| | ... +└── val + ├── JPEGImages + │   ├── 000001.jpg + │   ├── 000002.jpg + │   ├── 000003.jpg + | ... + ├── labels + │   ├── 000001.txt + │   ├── 000002.txt + │   ├── 000003.txt + | ... +``` + +All the images should be in `JPEGImages` directory, and all the labels should be in `labels` directory. The label file name should be the same as the image file name, except the extension name. For example, the label file for `000001.jpg` should be `000001.txt`. + +### label format + +The label format is the same as darknet. Each line in the label file represents a bounding box for the corresponding image. The format is: + +```shell + +``` + +- object-class: the class index of the object in the image, starts from 0 +- x, y: the center of the bounding box, normalized by the width and height of the image +- width, height: the width and height of the bounding box, normalized by the width and height of the image +- Note: the coordinates of the bounding box are normalized by the width and height of the image, so they should be in the range [0, 1] + +### convert to darknet format + +In many cases, the annotation of open dataset is not in darknet format. You can write a script to convert the dataset to darknet format. +*If there are bbox outside the image boundary, you need to handle it.* + +```python +def convert_bbox(img_wh, bbox): + (width, height) = img_wh + (x, y, w, h) = bbox + # handle bbox outside the image boundary + if x < 0: + w += x + x = 0 + if y < 0: + h += y + y = 0 + if x + w > width: + w = width - x + if y + h > height: + h = height - y + + x /= width + y /= height + w /= width + h /= height + x += w / 2 + y += h / 2 + return x, y, w, h + +def validate_bbox(bbox): + (x, y, w, h) = bbox + if w <= 0 or h <= 0: + return False + if x <= 0 or y <= 0: + return False + return True +``` + +### generate train.lst and val.lst + +After you prepare the data, you need to generate `train.lst` and `val.lst` for training and validation. Each line in the `train.lst` and `val.lst` represents an image. The format is: + +```shell + # full path is recommended + + +... +``` + +You can use the following script to generate `train.lst` and `val.lst`: + +```shell +base_dir=/path/to/your/data +find $base_dir/train/JPEGImages -name "*.jpg" > $base_dir/train/train.lst +find $base_dir/val/JPEGImages -name "*.jpg" > $base_dir/val/val.lst +``` + +### ~.names and ~.data + +~.names is the class name file, each line represents a class name. List all the class names from class 0. + +~.data is the dataset config file, the format is: + +```shell +classes = class_num +train = /path/to/train.lst +valid = /path/to/val.lst +names = /path/to/~.names +backup = /path/to/training/backup +``` + +Find example in `data/bdd100k.names` and `data/bdd100k.data`. + + +## Config the training + +Write a config file for training. Find example in `cfg` dir. + +Read [darknet wiki](https://github.com/AlexeyAB/darknet/wiki) for more details. + +### cfg for custom dataset + + +Under construction... + + +## Start training + +Train from scratch + +```shell +./darknet detector train data/bdd100k.data cfg/yolov3-bdd100k.cfg -map -dont_show -clear +``` + +Resume training + +```shell +./lightNet detector train data/bdd100k.data cfg/lightNet-BDD100K-1280x960.cfg lightNet-BDD100K-1280x960.weights -map -dont_show +``` \ No newline at end of file diff --git a/src/.#detector.c b/src/.#detector.c deleted file mode 120000 index 8f95c52..0000000 --- a/src/.#detector.c +++ /dev/null @@ -1 +0,0 @@ -umedan@user01-System-Product-Name.263723:1678871480 \ No newline at end of file diff --git a/src/.#route_layer.c b/src/.#route_layer.c deleted file mode 120000 index b5e261d..0000000 --- a/src/.#route_layer.c +++ /dev/null @@ -1 +0,0 @@ -umedan@user01-System-Product-Name.1429171:1672891380 \ No newline at end of file diff --git a/src/.editorconfig b/src/.editorconfig deleted file mode 100644 index 2eb162b..0000000 --- a/src/.editorconfig +++ /dev/null @@ -1,8 +0,0 @@ -root=true - -[*] -trim_trailing_whitespace = true -indent_style = space -indent_size = 4 - - diff --git a/src/csharp/CMakeLists.txt b/src/csharp/CMakeLists.txt deleted file mode 100644 index 1b591a1..0000000 --- a/src/csharp/CMakeLists.txt +++ /dev/null @@ -1,19 +0,0 @@ - -project(YoloCSharpWrapper LANGUAGES CSharp) -include(CSharpUtilities) - -add_library(${PROJECT_NAME} - ${PROJECT_NAME}.cs -) - -target_link_libraries(${PROJECT_NAME} PRIVATE dark) - -set_property(TARGET ${PROJECT_NAME} PROPERTY VS_DOTNET_REFERENCES - "System" - "System.Runtime.InteropServices" -) - -install(TARGETS ${PROJECT_NAME} - RUNTIME DESTINATION "${INSTALL_BIN_DIR}" - COMPONENT dev -) diff --git a/src/csharp/YoloCSharpWrapper.cs b/src/csharp/YoloCSharpWrapper.cs deleted file mode 100644 index 8fc8567..0000000 --- a/src/csharp/YoloCSharpWrapper.cs +++ /dev/null @@ -1,89 +0,0 @@ -using System; -using System.Runtime.InteropServices; - -namespace Darknet -{ - public class YoloWrapper : IDisposable - { - private const string YoloLibraryName = "darknet.dll"; - private const int MaxObjects = 1000; - - [DllImport(YoloLibraryName, EntryPoint = "init")] - private static extern int InitializeYolo(string configurationFilename, string weightsFilename, int gpu, int batch_size); - - [DllImport(YoloLibraryName, EntryPoint = "detect_image")] - private static extern int DetectImage(string filename, ref BboxContainer container); - - [DllImport(YoloLibraryName, EntryPoint = "detect_mat")] - private static extern int DetectImage(IntPtr pArray, int nSize, ref BboxContainer container); - - [DllImport(YoloLibraryName, EntryPoint = "dispose")] - private static extern int DisposeYolo(); - - [StructLayout(LayoutKind.Sequential)] - public struct bbox_t - { - public UInt32 x, y, w, h; // (x,y) - top-left corner, (w, h) - width & height of bounded box - public float prob; // confidence - probability that the object was found correctly - public UInt32 obj_id; // class of object - from range [0, classes-1] - public UInt32 track_id; // tracking id for video (0 - untracked, 1 - inf - tracked object) - public UInt32 frames_counter; - public float x_3d, y_3d, z_3d; // 3-D coordinates, if there is used 3D-stereo camera - }; - - [StructLayout(LayoutKind.Sequential)] - public struct BboxContainer - { - [MarshalAs(UnmanagedType.ByValArray, SizeConst = MaxObjects)] - public bbox_t[] candidates; - } - - public YoloWrapper(string configurationFilename, string weightsFilename, int gpu, int batch_size = 1) - { - InitializeYolo(configurationFilename, weightsFilename, gpu, batch_size); - } - - public void Dispose() - { - DisposeYolo(); - } - - public bbox_t[] Detect(string filename) - { - var container = new BboxContainer(); - var count = DetectImage(filename, ref container); - - return container.candidates; - } - - public bbox_t[] Detect(byte[] imageData) - { - var container = new BboxContainer(); - - var size = Marshal.SizeOf(imageData[0]) * imageData.Length; - var pnt = Marshal.AllocHGlobal(size); - - try - { - // Copy the array to unmanaged memory. - Marshal.Copy(imageData, 0, pnt, imageData.Length); - var count = DetectImage(pnt, imageData.Length, ref container); - if (count == -1) - { - throw new NotSupportedException($"{YoloLibraryName} has no OpenCV support"); - } - } - catch (Exception exception) - { - return null; - } - finally - { - // Free the unmanaged memory. - Marshal.FreeHGlobal(pnt); - } - - return container.candidates; - } - } -} diff --git a/src/detector.c b/src/detector.c index 830a58c..b5455d7 100644 --- a/src/detector.c +++ b/src/detector.c @@ -193,7 +193,7 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i double time_remaining, avg_time = -1, alpha_time = 0.01; char db_name[4096]; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); sqlite3 *db = open_db(db_name); create_loss_table(db); create_eval_detection(db); @@ -977,7 +977,7 @@ float validate_detector_map(char *datacfg, char *cfgfile, char *weightfile, floa char *train_images = option_find_str(options, "train", "data/train.txt"); list *plist_train = get_paths(train_images); int train_images_num = plist_train->size; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); if (!db) { db = open_db(db_name); } @@ -1482,7 +1482,7 @@ float validate_detector_per_image(char *datacfg, char *cfgfile, char *weightfile char *train_images = option_find_str(options, "train", "data/train.txt"); list *plist_train = get_paths(train_images); int train_images_num = plist_train->size; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); if (!db) { db = open_db(db_name); } @@ -2511,7 +2511,7 @@ void calc_sensitivity(char *datacfg, char *cfgfile, char *weightfile, char *file network net = parse_network_cfg_custom(cfgfile, 1, 1); // set batch=1 int i; char db_name[4096]; - sprintf(db_name, "%s/%s_sensitivity_analysis.db", backup_directory, base); + sprintf(db_name, "%s/%s_sensitivity_analysis.sqlite", backup_directory, base); sqlite3 *db = open_db(db_name); create_eval_detection(db); @@ -2611,7 +2611,7 @@ void calibrate(char *datacfg, char *cfgfile, char *weightfile, float thresh_calc char *backup_directory = option_find_str(options, "backup", "/backup/"); char *train_images = option_find_str(options, "train", "data/train.txt"); list *plist_train = get_paths(train_images); - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); if (!db) { db = open_db(db_name); } diff --git a/src/regression.c b/src/regression.c index db66d66..db00924 100644 --- a/src/regression.c +++ b/src/regression.c @@ -305,7 +305,7 @@ void train_regression(char *datacfg, char *cfgfile, char *weightfile, int *gpus, double time_remaining, avg_time = -1, alpha_time = 0.01; char db_name[4096]; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); sqlite3 *db = open_db(db_name); create_loss_table(db); create_eval_segmentation(db); @@ -1039,7 +1039,7 @@ float validate_regression_iou(char *datacfg, char *cfgfile, char *weightfile, fl char *train_images = option_find_str(options, "train", "data/train.txt"); list *plist_train = get_paths(train_images); int train_images_num = plist_train->size; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); int flg_open_db = false; if (!db) { flg_open_db = true; @@ -1253,7 +1253,7 @@ float uncertain_regression_iou(char *datacfg, char *cfgfile, char *weightfile, f char *train_images = option_find_str(options, "train", "data/train.txt"); list *plist_train = get_paths(train_images); int train_images_num = plist_train->size; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); int flg_open_db = false; if (!db) { flg_open_db = true; diff --git a/src/segmenter.c b/src/segmenter.c index d3b78ee..18345a6 100644 --- a/src/segmenter.c +++ b/src/segmenter.c @@ -319,7 +319,7 @@ void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus, double time_remaining, avg_time = -1, alpha_time = 0.01; char db_name[4096]; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); sqlite3 *db = open_db(db_name); create_loss_table(db); create_eval_segmentation(db); @@ -1053,7 +1053,7 @@ float validate_segmenter_iou(char *datacfg, char *cfgfile, char *weightfile, flo char *train_images = option_find_str(options, "train", "data/train.txt"); list *plist_train = get_paths(train_images); int train_images_num = plist_train->size; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); int flg_open_db = false; if (!db) { flg_open_db = true; @@ -1267,7 +1267,7 @@ float uncertain_segmenter_iou(char *datacfg, char *cfgfile, char *weightfile, fl char *train_images = option_find_str(options, "train", "data/train.txt"); list *plist_train = get_paths(train_images); int train_images_num = plist_train->size; - sprintf(db_name, "%s/%s.db",backup_directory, base); + sprintf(db_name, "%s/%s.sqlite",backup_directory, base); int flg_open_db = false; if (!db) { flg_open_db = true; diff --git a/src/version.h.in b/src/version.h.in deleted file mode 100644 index e908119..0000000 --- a/src/version.h.in +++ /dev/null @@ -1,3 +0,0 @@ -#define MAJOR_VERSION @Darknet_MAJOR_VERSION@ -#define MINOR_VERSION @Darknet_MINOR_VERSION@ -#define PATCH_VERSION @Darknet_PATCH_VERSION@ diff --git a/weights/.gitkeep b/weights/.gitkeep new file mode 100644 index 0000000..e69de29