File size: 1,963 Bytes
7b36907
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
# Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
FROM nvcr.io/nvidia/pytorch:20.12-py3

# Install linux packages
RUN apt update && apt install -y zip screen libgl1-mesa-glx

# RUN apt-get install vim

# Install python dependencies
RUN python -m pip install --upgrade pip
COPY requirements.txt .
RUN pip install -r requirements.txt gsutil

# Create working directory
RUN mkdir -p /usr/src/app
WORKDIR /usr/src/app

# Copy contents
COPY . /usr/src/app

RUN git config --global --add safe.directory /usr/src/app

RUN git config --global credential.helper stores

# Copy weights
#RUN python3 -c "from models import *; \
#attempt_download('weights/yolov5s.pt'); \
#attempt_download('weights/yolov5m.pt'); \
#attempt_download('weights/yolov5l.pt')"


# ---------------------------------------------------  Extras Below  ---------------------------------------------------

# Build and Push
# t=ultralytics/yolov5:latest && sudo docker build -t $t . && sudo docker push $t
# for v in {300..303}; do t=ultralytics/coco:v$v && sudo docker build -t $t . && sudo docker push $t; done

# Pull and Run
# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all $t

# Pull and Run with local directory access
# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/coco:/usr/src/coco $t

# Kill all
# sudo docker kill $(sudo docker ps -q)

# Kill all image-based
# sudo docker kill $(sudo docker ps -qa --filter ancestor=ultralytics/yolov5:latest)

# Bash into running container
# sudo docker exec -it 5a9b5863d93d bash

# Bash into stopped container
# id=$(sudo docker ps -qa) && sudo docker start $id && sudo docker exec -it $id bash

# Send weights to GCP
# python -c "from utils.general import *; strip_optimizer('runs/train/exp0_*/weights/best.pt', 'tmp.pt')" && gsutil cp tmp.pt gs://*.pt

# Clean up
# docker system prune -a --volumes