Merge pull request #1 from facebookresearch/master

Add dockerfile (fix facebookresearch#14)

.gitignore

@@ -1,6 +1,12 @@
 # output dir
 output
 instant_test_output
+inference_test_output
+
+
+*.jpg
+*.png
+*.txt
 
 # compilation and distribution
 __pycache__

Dockerfile

@@ -0,0 +1,36 @@
+FROM nvidia/cuda:10.1-cudnn7-devel
+# To use this Dockerfile:
+# 1. `nvidia-docker build -t detectron2:v0 .`
+# 2. `nvidia-docker run -it --name detectron2 detectron2:v0`
+
+
+ENV DEBIAN_FRONTEND noninteractive
+RUN apt-get update && apt-get install -y \
+	libpng-dev libjpeg-dev python3-opencv ca-certificates \
+	python3-dev build-essential pkg-config git curl wget automake libtool && \
+  rm -rf /var/lib/apt/lists/*
+
+RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py && \
+	python3 get-pip.py && \
+	rm get-pip.py
+
+# install dependencies
+# See https://pytorch.org/ for other options if you use a different version of CUDA
+RUN pip install torch torchvision cython \
+	'git+https://github.com/facebookresearch/fvcore'
+RUN pip install 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
+
+# install detectron2
+RUN git clone https://github.com/facebookresearch/detectron2 /detectron2_repo
+ENV FORCE_CUDA="1"
+RUN pip install -e /detectron2_repo
+
+WORKDIR /detectron2_repo
+
+# run it, for example:
+# wget http://images.cocodataset.org/val2017/000000439715.jpg -O input.jpg
+# python3 demo/demo.py  \
+	#--config-file configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml \
+	#--input input.jpg \
+	#--opts MODEL.WEIGHTS detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl
+

docs/conf.py

@@ -63,6 +63,7 @@
     "pycocotools",
     "pycocotools.mask",
     "pycocotools.coco",
+    "pycocotools.cocoeval",
 ]:
     sys.modules[m] = mock.Mock(name=m)
 sys.modules["cv2"].__version__ = "3.4"

setup.py

@@ -23,7 +23,7 @@ def get_extensions():
     extra_compile_args = {"cxx": []}
     define_macros = []
 
-    if torch.cuda.is_available() and CUDA_HOME is not None:
+    if (torch.cuda.is_available() and CUDA_HOME is not None) or os.getenv("FORCE_CUDA", "0") == "1":
         extension = CUDAExtension
         sources += source_cuda
         define_macros += [("WITH_CUDA", None)]