initial commit

Author: abhishekiitm

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 EMIT Lab, UW ECE
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -0,0 +1,30 @@
+# Viola Jones Cascade Classifier Training
+This repository provides a Python implementation for training a cascade classifier using Viola-Jones algorithm. The code has been optimized to run almost as fast as the C++ implementation provided by OpenCV.
+
+## Data preparation
+Positive data samples should be placed in a directory
+Background images from which negative data will be generated should be placed in another directory.
+
+## Usage
+### Training
+Training without GA
+```
+python src/traincascade.py -model /path/to/save/cascade_classifier/ \
+ -data_pos /path/to/positive/samples/folder/ \
+-data_neg /path/to/background/samples/folder/ \
+-numPos [NUM POS] -numNeg [NUM POS] -numStages [NUM STAGES] -maxWeakCount [MAX WEAK CLF COUNT] -minHitRate [MIN DETR EACH ROUND] -maxFalseAlarmRate [MAX FPR EACH ROUND] -log_file /path/to/logfile.log
+```
+
+Training with GA
+```
+python src/traincascade_ga.py -model /path/to/save/cascade_classifier/ \
+ -data_pos /path/to/positive/samples/folder/ \
+-data_neg /path/to/background/samples/folder/ \
+-results_dir /path/to/results/folder/
+ -numPos [NUM POS] -numNeg [NUM POS] -numStages [NUM STAGES] -maxWeakCount [MAX WEAK CLF COUNT] -minHitRate [MIN DETR EACH ROUND] -maxFalseAlarmRate [MAX FPR EACH ROUND] -log_file /path/to/logfile.log
+```
+
+### Detection
+```
+python src/inference.py -model /path/to/cascade_classifier/ -image /path/to/image.jpg -stage [STAGE] -min_obj_size [MIN OBJ SIZE] -max_obj_size [MAX OBJ SIZE] 
+```

requirements.txt

@@ -0,0 +1,209 @@
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+_libgcc_mutex=0.1=main
+_openmp_mutex=5.1=1_gnu
+_py-xgboost-mutex=2.0=cpu_0
+asttokens=2.2.1=pyhd8ed1ab_0
+backcall=0.2.0=pyh9f0ad1d_0
+backports=1.0=pyhd8ed1ab_3
+backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0
+blas=1.1=openblas
+bottleneck=1.3.5=py38h7deecbd_0
+brotli=1.0.9=h5eee18b_7
+brotli-bin=1.0.9=h5eee18b_7
+bzip2=1.0.8=h7f98852_4
+c-ares=1.19.1=h5eee18b_0
+ca-certificates=2023.7.22=hbcca054_0
+cairo=1.16.0=h18b612c_1001
+certifi=2023.7.22=pyhd8ed1ab_0
+charset-normalizer=3.0.1=pypi_0
+cloudpickle=2.2.1=pypi_0
+colorama=0.4.6=pyhd8ed1ab_0
+coloredlogs=15.0.1=pyhd8ed1ab_3
+contourpy=1.0.7=pypi_0
+cycler=0.11.0=pyhd3eb1b0_0
+dbus=1.13.18=hb2f20db_0
+debugpy=1.5.1=py38h295c915_0
+decorator=5.1.1=pyhd8ed1ab_0
+eigen=3.4.0=h4bd325d_0
+entrypoints=0.4=pyhd8ed1ab_0
+executing=1.2.0=pyhd8ed1ab_0
+expat=2.2.10=h9c3ff4c_0
+ffmpeg=4.2.2=h20bf706_0
+fftw=3.3.9=h27cfd23_1
+fontconfig=2.14.1=hef1e5e3_0
+fonttools=4.38.0=pypi_0
+freetype=2.10.4=h0708190_1
+giflib=5.2.1=h36c2ea0_2
+glib=2.69.1=he621ea3_2
+gmp=6.2.1=h58526e2_0
+gnutls=3.6.13=h85f3911_1
+graphite2=1.3.14=h295c915_1
+gst-plugins-base=1.14.0=h8213a91_2
+gstreamer=1.14.0=h28cd5cc_2
+harfbuzz=4.3.0=hd55b92a_0
+hdf5=1.10.6=h3ffc7dd_1
+humanfriendly=10.0=py38h578d9bd_4
+icu=58.2=hf484d3e_1000
+idna=3.4=pypi_0
+imageio=2.26.0=pyh24c5eb1_0
+importlib-metadata=4.11.3=py38h06a4308_0
+importlib_metadata=4.11.3=hd3eb1b0_0
+imutils=0.5.4=py38h578d9bd_3
+intel-openmp=2021.4.0=h06a4308_3561
+ipykernel=6.15.0=pyh210e3f2_0
+ipython=8.4.0=py38h578d9bd_0
+jedi=0.18.2=pyhd8ed1ab_0
+joblib=1.1.0=pyhd3eb1b0_0
+jpeg=9e=h166bdaf_1
+jupyter_client=7.0.6=pyhd8ed1ab_0
+jupyter_core=5.3.0=py38h578d9bd_0
+keyutils=1.6.1=h166bdaf_0
+kiwisolver=1.4.4=pypi_0
+krb5=1.20.1=h568e23c_1
+lame=3.100=h7f98852_1001
+lcms2=2.12=h3be6417_0
+ld_impl_linux-64=2.38=h1181459_1
+lerc=3.0=h295c915_0
+libblas=3.9.0=15_linux64_openblas
+libbrotlicommon=1.0.9=h5eee18b_7
+libbrotlidec=1.0.9=h5eee18b_7
+libbrotlienc=1.0.9=h5eee18b_7
+libcblas=3.9.0=15_linux64_openblas
+libclang=10.0.1=default_hb85057a_2
+libcurl=8.2.1=h91b91d3_0
+libdeflate=1.8=h7f8727e_5
+libedit=3.1.20221030=h5eee18b_0
+libev=4.33=h516909a_1
+libevent=2.1.12=h8f2d780_0
+libffi=3.4.2=h6a678d5_6
+libgcc-ng=11.2.0=h1234567_1
+libgfortran-ng=12.2.0=h69a702a_19
+libgfortran5=12.2.0=h337968e_19
+libgomp=11.2.0=h1234567_1
+liblapack=3.9.0=15_linux64_openblas
+libllvm10=10.0.1=he513fc3_3
+libllvm11=11.1.0=h9e868ea_6
+libnghttp2=1.52.0=ha637b67_1
+libopenblas=0.3.20=pthreads_h78a6416_0
+libopus=1.3.1=h7f98852_1
+libpng=1.6.37=hbc83047_0
+libpq=12.15=h37d81fd_1
+libprotobuf=3.20.3=he621ea3_0
+libsodium=1.0.18=h36c2ea0_1
+libssh2=1.10.0=h37d81fd_2
+libstdcxx-ng=11.2.0=h1234567_1
+libtiff=4.4.0=hecacb30_2
+libuuid=2.32.1=h7f98852_1000
+libvpx=1.7.0=h439df22_0
+libwebp=1.2.4=h11a3e52_0
+libwebp-base=1.2.4=h5eee18b_0
+libxcb=1.15=h7f8727e_0
+libxgboost=1.7.3=h6a678d5_0
+libxkbcommon=1.0.3=he3ba5ed_0
+libxml2=2.9.14=h74e7548_0
+libxslt=1.1.35=h4e12654_0
+lightgbm=3.1.1=py38h709712a_0
+llvmlite=0.39.1=py38he621ea3_0
+lz4-c=1.9.3=h9c3ff4c_1
+matplotlib=3.6.3=pypi_0
+matplotlib-base=3.6.2=py38h945d387_0
+matplotlib-inline=0.1.6=pyhd8ed1ab_0
+mkl=2021.4.0=h06a4308_640
+mkl-service=2.4.0=py38h7f8727e_0
+mkl_random=1.2.2=py38h51133e4_0
+mpmath=1.3.0=pyhd8ed1ab_0
+munkres=1.1.4=py_0
+ncurses=6.4=h6a678d5_0
+nest-asyncio=1.5.6=pyhd8ed1ab_0
+nettle=3.6=he412f7d_0
+nspr=4.33=h295c915_0
+nss=3.74=h0370c37_0
+numba=0.56.4=py38h417a72b_0
+numexpr=2.8.4=py38hd2a5715_0
+numpy=1.22.3=py38h99721a1_2
+nvidia-cublas-cu11=11.10.3.66=pypi_0
+nvidia-cuda-nvrtc-cu11=11.7.99=pypi_0
+nvidia-cuda-runtime-cu11=11.7.99=pypi_0
+nvidia-cudnn-cu11=8.5.0.96=pypi_0
+onnxruntime=1.15.1=py38hf70ce4d_0
+openblas=0.3.20=pthreads_h320a7e8_0
+opencv=4.6.0=py38hd653453_2
+openh264=2.1.1=h4ff587b_0
+openjpeg=2.3.1=hf7af979_3
+openssl=1.1.1w=h7f8727e_0
+packaging=21.3=pyhd3eb1b0_0
+pandas=1.4.3=py38h6a678d5_0
+parso=0.8.3=pyhd8ed1ab_0
+pcre=8.45=h9c3ff4c_0
+pexpect=4.8.0=pyh1a96a4e_2
+pickleshare=0.7.5=py_1003
+pillow=9.4.0=pypi_0
+pip=22.3.1=py38h06a4308_0
+pixman=0.38.0=h516909a_1003
+platformdirs=3.5.1=pyhd8ed1ab_0
+ply=3.11=py38_0
+prompt-toolkit=3.0.38=pyha770c72_0
+protobuf=3.20.3=py38h6a678d5_0
+psutil=5.9.0=py38h5eee18b_0
+ptyprocess=0.7.0=pyhd3deb0d_0
+pure_eval=0.2.2=pyhd8ed1ab_0
+py-xgboost=1.7.3=py38h06a4308_0
+pycocotools=2.0.6=pypi_0
+pygad=3.0.1=pypi_0
+pygments=2.15.1=pyhd8ed1ab_0
+pyparsing=3.0.4=pyhd3eb1b0_0
+pyqt=5.15.7=py38h6a678d5_1
+pyqt5-sip=12.11.0=py38h6a678d5_1
+python=3.8.16=h7a1cb2a_2
+python-dateutil=2.8.2=pyhd3eb1b0_0
+python-flatbuffers=23.5.26=pyhd8ed1ab_0
+python_abi=3.8=2_cp38
+pytz=2022.1=py38h06a4308_0
+pyvww=0.1.1=pypi_0
+pyzmq=19.0.2=py38ha71036d_2
+qt-main=5.15.2=h327a75a_7
+qt-webengine=5.15.9=hd2b0992_4
+qtwebkit=5.212=h4eab89a_4
+readline=8.2=h5eee18b_0
+requests=2.28.2=pypi_0
+scikit-learn=1.1.1=py38h6a678d5_0
+scipy=1.7.3=py38hf838250_2
+seaborn=0.11.2=pyhd3eb1b0_0
+setuptools=65.6.3=py38h06a4308_0
+sip=6.6.2=py38h6a678d5_0
+six=1.16.0=pyhd3eb1b0_1
+sqlite=3.40.1=h5082296_0
+stack_data=0.6.2=pyhd8ed1ab_0
+sympy=1.12=pyh04b8f61_3
+tbb=2021.6.0=hdb19cb5_1
+threadpoolctl=2.2.0=pyh0d69192_0
+tk=8.6.12=h1ccaba5_0
+toml=0.10.2=pyhd3eb1b0_0
+torch=1.13.1=pypi_0
+torchvision=0.14.1=pypi_0
+tornado=6.1=py38h27cfd23_0
+tqdm=4.64.1=pyhd8ed1ab_0
+traitlets=5.9.0=pyhd8ed1ab_0
+typing-extensions=4.4.0=pypi_0
+typing_extensions=4.5.0=pyha770c72_0
+urllib3=1.26.14=pypi_0
+wcwidth=0.2.6=pyhd8ed1ab_0
+wheel=0.37.1=pyhd3eb1b0_0
+x264=1!157.20191217=h7b6447c_0
+xorg-kbproto=1.0.7=h7f98852_1002
+xorg-libice=1.0.10=h7f98852_0
+xorg-libsm=1.2.3=hd9c2040_1000
+xorg-libx11=1.7.2=h7f98852_0
+xorg-libxext=1.3.4=h7f98852_1
+xorg-libxrender=0.9.10=h7f98852_1003
+xorg-renderproto=0.11.1=h7f98852_1002
+xorg-xextproto=7.3.0=h7f98852_1002
+xorg-xproto=7.0.31=h7f98852_1007
+xz=5.2.10=h5eee18b_1
+yapf=0.32.0=pyhd8ed1ab_0
+zeromq=4.3.4=h9c3ff4c_1
+zipp=3.11.0=py38h06a4308_0
+zlib=1.2.13=h5eee18b_0
+zstd=1.5.2=ha4553b6_0