create dockerfile

.devcontainer.json

@@ -0,0 +1,31 @@
+// For format details, see https://aka.ms/vscode-remote/devcontainer.json or this file's README at:
+// https://github.com/microsoft/vscode-dev-containers/tree/v0.117.0/containers/docker-existing-dockerfile
+{
+	"name": "PyT Docker FerAtt",
+
+	// Sets the run context to one level up instead of the .devcontainer folder.
+	"context": ".",
+
+	// Update the 'dockerFile' property if you aren't using the standard 'Dockerfile' filename.
+	"dockerFile": "Dockerfile",
+
+	// Set *default* container specific settings.json values on container create.
+	"settings": {
+		"terminal.integrated.shell.linux": null
+	},
+
+	// Add the IDs of extensions you want installed when the container is created.
+	"extensions": [],
+
+	// Use 'forwardPorts' to make a list of ports inside the container available locally.
+	"forwardPorts": [8097],
+
+	// Uncomment the next line to run commands after the container is created - for example installing git.
+	// "postCreateCommand": "apt-get update && apt-get install -y git",
+
+	"runArgs": [ "--ipc=host", "--gpus=all"],
+	"mounts": [ "source=${HOME}.datasets,target=/root/.datasets,type=bind" ],
+
+	// Uncomment to connect as a non-root user. See https://aka.ms/vscode-remote/containers/non-root.
+	// "remoteUser": "vscode"
+}

.dockerignore

@@ -0,0 +1,25 @@
+**/__pycache__
+**/.classpath
+**/.dockerignore
+**/.env
+**/.git
+**/.gitignore
+**/.project
+**/.settings
+**/.toolstarget
+**/.vs
+**/.vscode
+**/*.*proj.user
+**/*.dbmdl
+**/*.jfm
+**/azds.yaml
+**/bin
+**/charts
+**/docker-compose*
+**/Dockerfile*
+**/node_modules
+**/npm-debug.log
+**/obj
+**/secrets.dev.yaml
+**/values.dev.yaml
+README.md

.vscode/settings.json

@@ -9,5 +9,7 @@
     ],
     "python.testing.pytestEnabled": false,
     "python.testing.nosetestsEnabled": false,
-    "python.testing.unittestEnabled": true
+    "python.testing.unittestEnabled": true,
+    "files.trimFinalNewlines": true,
+    "files.trimTrailingWhitespace": true
 }

Dockerfile

@@ -0,0 +1,40 @@
+FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu16.04
+ARG PYTHON_VERSION=3.7
+ARG WITH_TORCHVISION=1
+
+RUN apt-get update && apt-get -y upgrade && apt-get install -y --no-install-recommends \
+         build-essential \
+         cmake \
+         vim \
+         git \
+         curl \
+         ca-certificates \
+         libgtk2.0-dev \
+         libjpeg-dev \
+         libpng-dev && \
+     rm -rf /var/lib/apt/lists/*
+
+RUN curl -o ~/miniconda.sh -L -O  https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh  && \
+     chmod +x ~/miniconda.sh && \
+     ~/miniconda.sh -b -p /opt/conda && \
+     rm ~/miniconda.sh && \
+     /opt/conda/bin/conda install -y python=$PYTHON_VERSION numpy pyyaml scipy ipython mkl mkl-include ninja cython typing && \
+     /opt/conda/bin/conda install -y -c pytorch magma-cuda100 && \
+     /opt/conda/bin/conda clean -ya
+ENV PATH /opt/conda/bin:$PATH
+
+RUN /opt/conda/bin/conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
+
+WORKDIR /opt
+RUN git clone https://github.com/pedrodiamel/pytorchvision.git && cd pytorchvision && python setup.py install
+
+RUN pip install --upgrade pip
+
+RUN apt-get update -y && apt-get upgrade -y && apt-get install -y vim emacs nano htop
+
+# WORKDIR /.datasets
+# RUN chmod -R a+w .
+
+WORKDIR /workspace
+ADD requirements.txt .
+RUN pip install -r requirements.txt

README.md

@@ -44,6 +44,11 @@ Installation
     $python setup.py install
     $pip install -r installation.txt
 
+Docker:
+
+    docker build -f "Dockerfile" -t feratt:latest .
+    ./run_docker.sh
+
 ### Visualize result with Visdom
 
 We now support Visdom for real-time loss visualization during training!
@@ -87,4 +92,3 @@ Acknowledgments
 ------------
 
 Gratefully acknowledge financial support from the Brazilian government agency FACEPE.
-

requirements.txt

@@ -1,5 +1,5 @@
 scikit-image
 sklearn
-scikit-fmm
 h5py
-pandas
+pandas
+scikit-fmm

run_docker.sh

@@ -0,0 +1,9 @@
+
+docker run -ti \
+--gpus=all \
+--ipc=host \
+-v $HOME/.datasets:/root/.datasets \
+-v $PWD:/workspace \
+-p 8097:8097 \
+--name feratt-run feratt:latest \
+/bin/bash

runs/eval.sh

@@ -1,6 +1,5 @@
 #!/bin/bash
 
-
 PATHDATASET='~/.datasets/'
 NAMEDATASET='affectnet' #bu3dfe, ferblack, ck, affectnetdark, affectnet, ferp
 PROJECT='../out'
@@ -9,9 +8,8 @@ FILENAME='result.txt'
 PATHMODEL='models'
 NAMEMODEL='chk000080.pth.tar' #'model_best.pth.tar' #'chk000565.pth.tar'
 
-
 PROJECTNAME='att_attgmmnet_ferattentiongmm_attloss_adam_affectnetdark_dim64_cvgg13x32_fold0_000'
-MODEL=$PROJECT/$PROJECTNAME/$PATHMODEL/$NAMEMODEL  
+MODEL=$PROJECT/$PROJECTNAME/$PATHMODEL/$NAMEMODEL
 
 python ../eval.py \
 --project=$PROJECT \
@@ -21,5 +19,3 @@ python ../eval.py \
 --pathnameout=$PATHNAMEOUT \
 --filename=$FILENAME \
 --model=$MODEL \
-
-

runs/represent.sh

@@ -8,7 +8,7 @@ PATHNAMEOUT='../out'
 FILENAME='result.txt'
 PATHMODEL='models'
 NAMEMODEL='model_best.pth.tar' #'model_best.pth.tar' #'chk000565.pth.tar'
-MODEL=$PROJECT/$PROJECTNAME/$PATHMODEL/$NAMEMODEL  
+MODEL=$PROJECT/$PROJECTNAME/$PATHMODEL/$NAMEMODEL
 
 python ../represent.py \
 --project=$PROJECT \
@@ -18,4 +18,3 @@ python ../represent.py \
 --pathnameout=$PATHNAMEOUT \
 --filename=$FILENAME \
 --model=$MODEL \
-

runs/train.sh

@@ -19,7 +19,7 @@ NAMEMETHOD='attnet' # attnet, attstnnet, attgmmnet, attgmmstnnet
 ARCH='ferattention' # ferattention, ferattentionstn, ferattentiongmm, ferattentiongmmstn
 LOSS='attloss'
 OPT='adam'
-SCHEDULER='plateau' #step, plateau
+SCHEDULER='fixed' #fixed, step, plateau
 NUMCLASS=8 #6, 7, 8
 NUMCHANNELS=3
 DIM=32
@@ -33,8 +33,8 @@ EXP_NAME='feratt_'$NAMEMETHOD'_'$ARCH'_'$LOSS'_'$OPT'_'$NAMEDATASET'_dim'$DIM'_b
 
 rm -rf $PROJECT/$EXP_NAME/$EXP_NAME.log
 rm -rf $PROJECT/$EXP_NAME/
-mkdir $PROJECT
-mkdir $PROJECT/$EXP_NAME
+mkdir -p $PROJECT
+mkdir -p $PROJECT/$EXP_NAME
 
 #0,1,2,3
 CUDA_VISIBLE_DEVICES=0  python ../train.py \

runs/train_bu3dfe.sh

@@ -19,7 +19,7 @@ NAMEMETHOD='attnet' #attnet, attstnnet, attgmmnet, attgmmstnnet
 ARCH='ferattention' #ferattention, ferattentiongmm, ferattentionstn
 LOSS='attloss'
 OPT='adam'
-SCHEDULER='step'
+SCHEDULER='fixed'
 NUMCLASS=7 #6, 7, 8
 NUMCHANNELS=3
 DIM=32
@@ -31,11 +31,10 @@ BACKBONE='preactresnet' #preactresnet, resnet, cvgg
 
 EXP_NAME='feratt_'$NAMEMETHOD'_'$ARCH'_'$LOSS'_'$OPT'_'$NAMEDATASET'_dim'$DIM'_bb'$BACKBONE'_fold'$KFOLD'_000'
 
-
 rm -rf $PROJECT/$EXP_NAME/$EXP_NAME.log
 rm -rf $PROJECT/$EXP_NAME/
-mkdir $PROJECT
-mkdir $PROJECT/$EXP_NAME
+mkdir -p $PROJECT
+mkdir -p $PROJECT/$EXP_NAME
 
 
 CUDA_VISIBLE_DEVICES=0 python ../train.py \

runs/train_ck.sh

@@ -19,7 +19,7 @@ NAMEMETHOD='attnet' #attnet, attstnnet, attgmmnet, attgmmstnnet
 ARCH='ferattention' #ferattention, ferattentiongmm, ferattentionstn
 LOSS='attloss'
 OPT='adam'
-SCHEDULER='step'
+SCHEDULER='fixed'
 NUMCLASS=8 #6, 7, 8
 NUMCHANNELS=3
 DIM=32
@@ -31,11 +31,10 @@ BACKBONE='preactresnet' #preactresnet, resnet, cvgg
 
 EXP_NAME='feratt_'$NAMEMETHOD'_'$ARCH'_'$LOSS'_'$OPT'_'$NAMEDATASET'_dim'$DIM'_bb'$BACKBONE'_fold'$KFOLD'_000'
 
-
 rm -rf $PROJECT/$EXP_NAME/$EXP_NAME.log
 rm -rf $PROJECT/$EXP_NAME/
-mkdir $PROJECT
-mkdir $PROJECT/$EXP_NAME
+mkdir -p $PROJECT
+mkdir -p $PROJECT/$EXP_NAME
 
 
 CUDA_VISIBLE_DEVICES=0 python ../train.py \

runs/train_mitosis.sh

@@ -30,8 +30,8 @@ EXP_NAME='mitosis_att_'$NAMEMETHOD'_'$ARCH'_'$LOSS'_'$OPT'_'$NAMEDATASET'_dim'$D
 
 # rm -rf $PROJECT/$EXP_NAME/$EXP_NAME.log
 # rm -rf $PROJECT/$EXP_NAME/
-# mkdir $PROJECT    
-# mkdir $PROJECT/$EXP_NAME  
+# mkdir -p $PROJECT
+# mkdir -p $PROJECT/$EXP_NAME
 
 
 CUDA_VISIBLE_DEVICES=0,1,2,3 python ../train_mitosis.py \
@@ -63,4 +63,3 @@ $DATA \
 --parallel \
 --finetuning \
 2>&1 | tee -a $PROJECT/$EXP_NAME/$EXP_NAME.log \
-

test/data/test_data_generator.py

@@ -1,24 +1,26 @@
-import unittest
-import sys
+
 import os
+import sys
 import numpy as np
 import cv2
-import matplotlib.pyplot as plt
+import unittest
 
 from pytvision.datasets import imageutl as imutl
 from pytvision.transforms import functional as F
 
-sys.path.append('../../')
+sys.path.append('../')
 from torchlib.transforms.ferrender import Generator
 from torchlib.datasets.factory import FactoryDataset
 from torchlib.datasets.fersynthetic import SyntheticFaceDataset
 
+import matplotlib.pyplot as plt
+
 
 def test_dataset_synthetic():
 
     data=FactoryDataset.factory(
         pathname='~/.datasets/',
-        name=FactoryDataset.bu3dfe,
+        name=FactoryDataset.ck,
         subset=FactoryDataset.training,
         download=True
         )
@@ -31,7 +33,7 @@ def test_dataset_synthetic():
     )
 
     img, mask, label = dataset[ np.random.randint( len(dataset) )  ]
-    #print( len(dataset) )
+    print( len(dataset) )
 
     plt.figure()
     plt.subplot(121)
@@ -45,8 +47,8 @@ def test_dataset_synthetic():
 def test_dataset_generator():
 
     data=FactoryDataset.factory(
-        pathname='~/.datasets/',
-        name=FactoryDataset.bu3dfe,
+        pathname= os.path.expanduser('~/.datasets/'),
+        name=FactoryDataset.ck,
         subset=FactoryDataset.training,
         download=True
         )
@@ -56,7 +58,7 @@ def test_dataset_generator():
     img = np.stack((img,img,img),axis=2)
 
     idx=1
-    pathname = os.path.expanduser( '~/.datasets/photo' )
+    pathname = os.path.expanduser( '~/.datasets/coco' )
     data_back = imutl.imageProvide( pathname, ext='jpg');
     back = data_back[ (idx)%len(data_back)  ]
     back = F.resize_image(back, 640, 1024, resize_mode='crop', interpolate_mode=cv2.INTER_LINEAR);
@@ -67,18 +69,18 @@ def test_dataset_generator():
     print(img.shape, img.max())
     print(back.shape, back.max())
 
-    image, mask = ren.generate(img, back )
+    image, image_ilu, mask, h = ren.generate(img, back )
     print( image.shape, image.max() )
     print( mask.shape, mask.max() )
 
-    plt.figure()
-    plt.subplot(121)
-    plt.imshow(image.mean(axis=2), cmap='gray' )
-    plt.subplot(122)
-    plt.imshow( mask[:,:,0] )
-    plt.show()
+    # plt.figure()
+    # plt.subplot(121)
+    # plt.imshow(image.mean(axis=2), cmap='gray' )
+    # plt.subplot(122)
+    # plt.imshow( mask[:,:,0] )
+    # plt.show()
 
 
 
-# test_dataset_generator()
-test_dataset_synthetic()
+test_dataset_generator()
+# test_dataset_synthetic()

test/test_model.py

@@ -1,11 +1,14 @@
-from torchlib import models as md
-import torch.nn as nn
+# python -m unittest test_model.py
+
+import os
+import sys
+
 import torch
+import torch.nn as nn
 import unittest
-import sys
-import os
 
 sys.path.append('../')
+from torchlib import models as md
 
 
 class TestModel(unittest.TestCase):