Image Segmentation 코딩

Udemy 강의

https://www.udemy.com/course/yolov8-the-ultimate-course-for-object-detection-tracking/

 

matplotlib으로 이미지를 표시하지 않으려면 Ipython.display를 사용한다.

from IPython.display import Image

Image명령으로 표시 가능

Image('/content/image1.jpg')

 

웹화면에서 비디오를 보여주는 방법

from IPython.display import HTML

from base64 import b64encode

import os

# Input video path

save_path = '/content/runs/segment/predict3/demo.mp4'

# Compressed video path

compressed_path = "/content/result_compressed.mp4"

os.system(f"ffmpeg -i {save_path} -vcodec libx264 {compressed_path}")

# Show video

mp4 = open(compressed_path,'rb').read()

data_url = "data:video/mp4;base64," + b64encode(mp4).decode()

HTML("""

<video width=400 controls>

      <source src="%s" type="video/mp4">

</video>

""" % data_url)

 

파이썬 내에서 처리하는 방법

from ultralytics import YOLO

model = YOLO("yolov8m-seg.pt")

model.predict(source='/content/image1.jpg',  save=True, conf=0.5,save_txt=True)

Image('/content/runs/segment/predict4/image1.jpg')

 

model = YOLO("yolov8m-seg.pt")

model.predict(source='/content/demo.mp4',  save=True, conf=0.5, save_txt = False)

 

from IPython.display import HTML

from base64 import b64encode

import os

# Input video path

save_path = '/content/runs/segment/predict5/demo.mp4'

# Compressed video path

compressed_path = "/content/result_compressed.mp4"

os.system(f"ffmpeg -i {save_path} -vcodec libx264 {compressed_path}")

# Show video

mp4 = open(compressed_path,'rb').read()

data_url = "data:video/mp4;base64," + b64encode(mp4).decode()

HTML("""

<video width=400 controls>

      <source src="%s" type="video/mp4">

</video>

""" % data_url)

 

model = YOLO("yolov8m-seg.pt")

model.export(format="onnx")

torch 모델 파일은 다음에서 모델 구성을 확인할 수 있다.

https://netron.app

Netron

pt파일을 불러들이면...

 

구성을 확인가능하다.