yolov5_trainning.py

# -*- coding: utf-8 -*-
"""yolov5_trainning.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/###

# **사전 설치**
"""

from google.colab import drive
drive.mount('/content/drive')

!git clone https://github.com/ultralytics/yolov5

# Commented out IPython magic to ensure Python compatibility.
# %cd yolov5
# %pip install -qr requirements.txt

"""# **데이터셋 가져오기**


"""

!curl -L "#########--insert your URL--###########" > roboflow.zip; 
!unzip roboflow.zip; rm roboflow.zip

"""# **이미지 한번에 긁어모으기 위한 glob 모듈 사용**"""

from glob import glob
tra_img_list = glob('/content/yolov5/train/images/*.jpg') # train 이미지 경로
val_img_list = glob('/content/yolov5/test/images/*.jpg') # 테스트 이미지 경로

with open('/content/yolov5/train.txt', 'w') as f:
  f.write('\n'.join(tra_img_list) + '\n')

with open('/content/yolov5/test.txt', 'w') as f:
  f.write('\n'.join(val_img_list) + '\n')

"""# **커스텀 학습**"""

!python train.py --img 416 --batch 16 --epochs 40 --data /content/yolov5/data.yaml --weights yolov5m.pt --name result_fire --cfg ./models/yolov5m.yaml

"""# **학습 결과를 다운로드하고 싶다면, 내용 모두 압축하여 저장**"""

!zip -r ../drive/MyDrive/Colab_Notebooks/custom_train_result_ver10.zip runs/train/result_fire3

"""# **검증하기는 생략, 바로 적용해보기**
테스트 결과는 ```/runs/detect/exp``` 경로에 저장
"""

!python detect.py --weights "/content/yolov5/runs/train/result_fire3/weights/best.pt" --source 'https://www.youtube.com/watch?v=ai0-jT6kuoA'  # YouTube

!zip -r test_result.zip runs/detect/exp

"""# **코랩 유지에 필요한 코드(F12 Javascript)**"""

function ClickConnect(){
console.log("Working"); 
document.querySelector("colab-toolbar-button#connect").click() 
}setInterval(ClickConnect, 450000)