├── .devcontainer
├── devcontainer.json
├── docker-compose.yml
└── readme
├── Dockerfile
├── LICENSE
├── README.md
├── config.py
├── docs
├── overall.jpg
└── results.jpg
├── model
├── __init__.py
└── mysegformer
│ ├── PotCrackSeg.py
│ ├── __init__.py
│ ├── decoders
│ └── Decoder.py
│ └── encoders
│ ├── dual_segformer.py
│ └── one_segformer.py
├── run_demo.py
├── train.py
└── util
├── MY_dataset.py
├── __init__.py
├── augmentation.py
├── init_func.py
├── load_utils.py
├── lr_policy.py
└── util.py
/.devcontainer/devcontainer.json:
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1 | // For format details, see https://aka.ms/devcontainer.json. For config options, see the README at:
2 | // https://github.com/microsoft/vscode-dev-containers/tree/v0.163.1/containers/docker-from-docker-compose
3 | {
4 | "name": "potcrackseg",
5 | "dockerComposeFile": "docker-compose.yml",
6 | "service": "potcrackseg",
7 | "workspaceFolder": "/workspace"
8 |
9 | // // Use this environment variable if you need to bind mount your local source code into a new container.
10 | // "remoteEnv": {
11 | // "LOCAL_WORKSPACE_FOLDER": "${localWorkspaceFolder}"
12 | // },
13 |
14 | // // Set *default* container specific settings.json values on container create.
15 | // "settings": {
16 | // "terminal.integrated.shell.linux": "/bin/bash"
17 | // },
18 |
19 | // // Add the IDs of extensions you want installed when the container is created.
20 | // "extensions": [
21 | // "ms-azuretools.vscode-docker"
22 | // ],
23 |
24 | // // Use 'forwardPorts' to make a list of ports inside the container available locally.
25 | // // "forwardPorts": [],
26 |
27 | // // Use 'postCreateCommand' to run commands after the container is created.
28 | // // "postCreateCommand": "docker --version",
29 |
30 | // // Comment out connect as root instead. More info: https://aka.ms/vscode-remote/containers/non-root.
31 | // "remoteUser": "vscode"
32 | }
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/.devcontainer/docker-compose.yml:
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1 | version: '2.3'
2 | services:
3 | potcrackseg:
4 | # Uncomment the next line to use a non-root user for all processes. You can also
5 | # simply use the "remoteUser" property in devcontainer.json if you just want VS Code
6 | # and its sub-processes (terminals, tasks, debugging) to execute as the user. On Linux,
7 | # you may need to update USER_UID and USER_GID in .devcontainer/Dockerfile to match your
8 | # user if not 1000. See https://aka.ms/vscode-remote/containers/non-root for details.
9 | # user: vscode
10 | runtime: nvidia
11 | image: docker_image_drcnet # The name of the docker image
12 | ports:
13 | - '11011:6006'
14 | volumes:
15 | # Update this to wherever you want VS Code to mount the folder of your project
16 | - ..:/workspace:cached # Do not change!
17 | # - /home/sun/somefolder/:/somefolder # folder_in_local_computer:folder_in_docker_container
18 |
19 | # Forwards the local Docker socket to the container.
20 | - /var/run/docker.sock:/var/run/docker-host.sock
21 | shm_size: 32g
22 | devices:
23 | - /dev/nvidia0
24 | # - /dev/nvidia1 # Please note this line, if your computer has only one GPU
25 |
26 | # Uncomment the next four lines if you will use a ptrace-based debuggers like C++, Go, and Rust.
27 | # cap_add:
28 | # - SYS_PTRACE
29 | # security_opt:
30 | # - seccomp:unconfined
31 |
32 | # Overrides default command so things don't shut down after the process ends.
33 | #entrypoint: /usr/local/share/docker-init.sh
34 | command: sleep infinity
35 |
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/.devcontainer/readme:
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1 |
2 |
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/Dockerfile:
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1 | FROM nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04
2 | ENV DEBIAN_FRONTEND=noninteractive
3 | #RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 'A4B469963BF863CC'
4 |
5 | RUN apt-key del 7fa2af80
6 | RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
7 | RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu2004/x86_64/7fa2af80.pub
8 |
9 |
10 | RUN apt-get update && apt-get install -y vim python3 python3-pip
11 |
12 | RUN pip3 install --upgrade pip
13 | RUN pip3 install setuptools>=40.3.0
14 |
15 | RUN pip3 install -U scipy scikit-learn
16 | RUN pip3 install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
17 | RUN pip3 install torchsummary
18 | RUN pip3 install tensorboard==2.11.0
19 | RUN pip3 install einops
20 |
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/LICENSE:
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1 | MIT License
2 |
3 | Copyright (c) 2023 Autonomous Systems Lab
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
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/README.md:
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1 | # PotCrackSeg
2 | The official pytorch implementation of **Segmentation of Road Negative Obstacles Based on Dual Semantic-feature Complementary Fusion for Autonomous Driving**. ([TIV](https://ieeexplore.ieee.org/document/10468640/))
3 |
4 |
5 | We test our code in Python 3.8, CUDA 11.3, cuDNN 8, and PyTorch 1.12.1. We provide `Dockerfile` to build the docker image we used. You can modify the `Dockerfile` as you want.
6 |
7 |
8 |
15 |