- Host system with NVIDIA GPU
- 10 - 20GB of storage space
- Host system with internet connection
- Tested on Ubuntu 19.04 and 19.10
-
git clone this repository
-
image-annotator/ directory to be placed in image-annotator-docker/
- git clone image-annotator/ to image-annotator-docker/ from https://bitbucket.org/JialinYuan/image-annotator/src/master/ (no install needed)
- Download and extract model.zip to image-annotator-docker/image-annotator/deep_interactive/
-
Modify image-annotator-docker/image-annotator/config.py
- find line:
__C.PosNeg_Model_weight_Path = './deep_interactive/model/PASCAL/pos_neg/model.ckpt-80000'
and change it to:__C.PosNeg_Model_weight_Path = '/image-annotator/deep_interactive/model/PASCAL/pos_neg/model.ckpt-80000
- find line:
-
cuDNN 7.1.4 and place "cudnn-9.0-linux-x64-v7.1.tgz" in image-annotator-docker/
- https://developer.nvidia.com/rdp/cudnn-archive
- Select "Download cuDNN v7.1.4 (May 16, 2018), for CUDA 9.0"
- Download "cuDNN v7.1.4 Library for Linux"
-
Docker to be installed on host machine
- https://docs.docker.com/engine/install/ubuntu/
- Complete postinstall steps: https://docs.docker.com/engine/install/linux-postinstall/
-
nvidia-docker (2.0) installed on host machine (For Ubuntu os, it is debian based distribution)
- $
./start_img_ann
(wait a long time for the build) - Open browser to 0.0.0.0:5000/