์ฝ˜ํ…์ธ ๋กœ ๊ฑด๋„ˆ๋›ฐ๊ธฐ

A Guide on How to Use JupyterLab to Train Your YOLO11 Models

Building deep learning models can be tough, especially when you don't have the right tools or environment to work with. If you are facing this issue, JupyterLab might be the right solution for you. JupyterLab is a user-friendly, web-based platform that makes coding more flexible and interactive. You can use it to handle big datasets, create complex models, and even collaborate with others, all in one place.

You can use JupyterLab to work on projects related to Ultralytics YOLO11 models. JupyterLab is a great option for efficient model development and experimentation. It makes it easy to start experimenting with and training YOLO11 models right from your computer. Let's dive deeper into JupyterLab, its key features, and how you can use it to train YOLO11 models.

์ฃผํ”ผํ„ฐ๋žฉ์ด๋ž€ ๋ฌด์—‡์ธ๊ฐ€์š”?

JupyterLab์€ Jupyter ๋…ธํŠธ๋ถ, ์ฝ”๋“œ, ๋ฐ์ดํ„ฐ ์ž‘์—…์„ ์œ„ํ•ด ์„ค๊ณ„๋œ ์˜คํ”ˆ ์†Œ์Šค ์›น ๊ธฐ๋ฐ˜ ํ”Œ๋žซํผ์ž…๋‹ˆ๋‹ค. ๊ธฐ์กด Jupyter ๋…ธํŠธ๋ถ ์ธํ„ฐํŽ˜์ด์Šค์—์„œ ์—…๊ทธ๋ ˆ์ด๋“œ๋˜์–ด ๋”์šฑ ๋‹ค์–‘ํ•˜๊ณ  ๊ฐ•๋ ฅํ•œ ์‚ฌ์šฉ์ž ๊ฒฝํ—˜์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.

JupyterLab allows you to work with notebooks, text editors, terminals, and other tools all in one place. Its flexible design lets you organize your workspace to fit your needs and makes it easier to perform tasks like data analysis, visualization, and machine learning. JupyterLab also supports real-time collaboration, making it ideal for team projects in research and data science.

์ฃผํ”ผํ„ฐ๋žฉ์˜ ์ฃผ์š” ๊ธฐ๋Šฅ

๋‹ค์Œ์€ ๋ชจ๋ธ ๊ฐœ๋ฐœ ๋ฐ ์‹คํ—˜์„ ์œ„ํ•œ ํ›Œ๋ฅญํ•œ ์˜ต์…˜์ธ JupyterLab์˜ ์ฃผ์š” ๊ธฐ๋Šฅ ์ค‘ ์ผ๋ถ€์ž…๋‹ˆ๋‹ค:

  • ์˜ฌ์ธ์› ์ž‘์—… ๊ณต๊ฐ„: JupyterLab์€ ๋ฐ์ดํ„ฐ ๊ณผํ•™์— ํ•„์š”ํ•œ ๋ชจ๋“  ๊ฒƒ์„ ์›์Šคํ†ฑ์œผ๋กœ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ํ…์ŠคํŠธ ํŽธ์ง‘, ํ„ฐ๋ฏธ๋„ ์•ก์„ธ์Šค, ๋…ธํŠธ๋ถ์„ ์œ„ํ•œ ๋ณ„๋„์˜ ์ธํ„ฐํŽ˜์ด์Šค๊ฐ€ ์žˆ๋˜ ๊ธฐ์กด Jupyter Notebook๊ณผ ๋‹ฌ๋ฆฌ, JupyterLab์€ ์ด๋Ÿฌํ•œ ๋ชจ๋“  ๊ธฐ๋Šฅ์„ ํ•˜๋‚˜์˜ ์ผ๊ด€๋œ ํ™˜๊ฒฝ์œผ๋กœ ํ†ตํ•ฉํ•ฉ๋‹ˆ๋‹ค. JPEG, PDF, CSV ๋“ฑ ๋‹ค์–‘ํ•œ ํŒŒ์ผ ํ˜•์‹์„ JupyterLab ๋‚ด์—์„œ ๋ฐ”๋กœ ๋ณด๊ณ  ํŽธ์ง‘ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ฌ์ธ์› ์ž‘์—… ๊ณต๊ฐ„์„ ํ†ตํ•ด ํ•„์š”ํ•œ ๋ชจ๋“  ๊ธฐ๋Šฅ์— ๊ฐ„ํŽธํ•˜๊ฒŒ ์•ก์„ธ์Šคํ•  ์ˆ˜ ์žˆ์–ด ์›Œํฌํ”Œ๋กœ์šฐ๊ฐ€ ๊ฐ„์†Œํ™”๋˜๊ณ  ์‹œ๊ฐ„์ด ์ ˆ์•ฝ๋ฉ๋‹ˆ๋‹ค.
  • ์œ ์—ฐํ•œ ๋ ˆ์ด์•„์›ƒ: ์ฃผํ”ผํ„ฐ๋žฉ์˜ ๋›ฐ์–ด๋‚œ ๊ธฐ๋Šฅ ์ค‘ ํ•˜๋‚˜๋Š” ์œ ์—ฐํ•œ ๋ ˆ์ด์•„์›ƒ์ž…๋‹ˆ๋‹ค. ํƒญ์„ ๋“œ๋ž˜๊ทธ ์•ค ๋“œ๋กญํ•˜๊ณ  ํฌ๊ธฐ๋ฅผ ์กฐ์ •ํ•˜์—ฌ ๋ณด๋‹ค ํšจ์œจ์ ์œผ๋กœ ์ž‘์—…ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐœ์ธํ™”๋œ ๋ ˆ์ด์•„์›ƒ์„ ๋งŒ๋“ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ ‘์„ ์ˆ˜ ์žˆ๋Š” ์™ผ์ชฝ ์‚ฌ์ด๋“œ๋ฐ”๋Š” ํŒŒ์ผ ๋ธŒ๋ผ์šฐ์ €, ์‹คํ–‰ ์ค‘์ธ ์ปค๋„, ๋ช…๋ น ํŒ”๋ ˆํŠธ์™€ ๊ฐ™์€ ํ•„์ˆ˜ ํƒญ์„ ์†์ด ๋‹ฟ๋Š” ๊ณณ์— ๋ณด๊ด€ํ•ฉ๋‹ˆ๋‹ค. ํ•œ ๋ฒˆ์— ์—ฌ๋Ÿฌ ๊ฐœ์˜ ์ฐฝ์„ ์—ด์–ด ๋ฉ€ํ‹ฐํƒœ์Šคํ‚น์„ ํ•˜๊ณ  ํ”„๋กœ์ ํŠธ๋ฅผ ๋” ํšจ๊ณผ์ ์œผ๋กœ ๊ด€๋ฆฌํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
  • ๋Œ€ํ™”ํ˜• ์ฝ”๋“œ ์ฝ˜์†”: JupyterLab์˜ ์ฝ”๋“œ ์ฝ˜์†”์€ ์ฝ”๋“œ๋‚˜ ํ•จ์ˆ˜ ์Šค๋‹ˆํŽซ์„ ํ…Œ์ŠคํŠธํ•ด ๋ณผ ์ˆ˜ ์žˆ๋Š” ๋Œ€ํ™”ํ˜• ๊ณต๊ฐ„์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ ๋…ธํŠธ๋ถ ๋‚ด์—์„œ ์ˆ˜ํ–‰ํ•œ ๊ณ„์‚ฐ์˜ ๋กœ๊ทธ ์—ญํ• ๋„ ํ•ฉ๋‹ˆ๋‹ค. ๋…ธํŠธ๋ถ์— ์ƒˆ ์ฝ˜์†”์„ ๋งŒ๋“ค๊ณ  ๋ชจ๋“  ์ปค๋„ ํ™œ๋™์„ ๋ณด๋Š” ๊ฒƒ์€ ๊ฐ„๋‹จํ•ฉ๋‹ˆ๋‹ค. ์ด ๊ธฐ๋Šฅ์€ ์ƒˆ๋กœ์šด ์•„์ด๋””์–ด๋ฅผ ์‹คํ—˜ํ•˜๊ฑฐ๋‚˜ ์ฝ”๋“œ์˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•  ๋•Œ ํŠนํžˆ ์œ ์šฉํ•ฉ๋‹ˆ๋‹ค.
  • Markdown ๋ฏธ๋ฆฌ๋ณด๊ธฐ: Markdown ํŒŒ์ผ ์ž‘์—…์€ ๋™์‹œ ๋ฏธ๋ฆฌ๋ณด๊ธฐ ๊ธฐ๋Šฅ ๋•๋ถ„์— JupyterLab์—์„œ ๋” ํšจ์œจ์ ์œผ๋กœ ์ž‘์—…ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. Markdown ํŒŒ์ผ์„ ์ž‘์„ฑํ•˜๊ฑฐ๋‚˜ ํŽธ์ง‘ํ•  ๋•Œ ํ˜•์‹์ด ์ง€์ •๋œ ๊ฒฐ๊ณผ๋ฌผ์„ ์‹ค์‹œ๊ฐ„์œผ๋กœ ํ™•์ธํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฌธ์„œ๊ฐ€ ์™„๋ฒฝํ•˜๊ฒŒ ๋ณด์ด๋Š”์ง€ ๋‹ค์‹œ ํ•œ ๋ฒˆ ๋” ์‰ฝ๊ฒŒ ํ™•์ธํ•  ์ˆ˜ ์žˆ์–ด ํŽธ์ง‘ ๋ชจ๋“œ์™€ ๋ฏธ๋ฆฌ๋ณด๊ธฐ ๋ชจ๋“œ ์‚ฌ์ด๋ฅผ ์™”๋‹ค ๊ฐ”๋‹ค ํ•  ํ•„์š”๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค.
  • ํ…์ŠคํŠธ ํŒŒ์ผ์—์„œ ์ฝ”๋“œ ์‹คํ–‰: ์ฝ”๋“œ๊ฐ€ ํฌํ•จ๋œ ํ…์ŠคํŠธ ํŒŒ์ผ์„ ๊ณต์œ ํ•˜๋Š” ๊ฒฝ์šฐ, JupyterLab์„ ์‚ฌ์šฉํ•˜๋ฉด ํ”Œ๋žซํผ ๋‚ด์—์„œ ๋ฐ”๋กœ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ฝ”๋“œ๋ฅผ ๊ฐ•์กฐ ํ‘œ์‹œํ•˜๊ณ  Shift + Enter๋ฅผ ๋ˆŒ๋Ÿฌ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ฝ”๋“œ ์Šค๋‹ˆํŽซ์„ ๋น ๋ฅด๊ฒŒ ๊ฒ€์ฆํ•˜๋Š” ๋ฐ ์œ ์šฉํ•˜๋ฉฐ ๊ณต์œ ํ•œ ์ฝ”๋“œ๊ฐ€ ์ œ๋Œ€๋กœ ์ž‘๋™ํ•˜๊ณ  ์˜ค๋ฅ˜๊ฐ€ ์—†๋Š”์ง€ ํ™•์ธํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค.

Why Should You Use JupyterLab for Your YOLO11 Projects?

๋จธ์‹ ๋Ÿฌ๋‹ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ๋Š” ํ”Œ๋žซํผ์€ ์—ฌ๋Ÿฌ ๊ฐ€์ง€๊ฐ€ ์žˆ๋Š”๋ฐ, JupyterLab์ด ๋‹๋ณด์ด๋Š” ์ด์œ ๋Š” ๋ฌด์—‡์ผ๊นŒ์š”? ๋จธ์‹  ๋Ÿฌ๋‹ ํ”„๋กœ์ ํŠธ๋ฅผ ์œ„ํ•ด JupyterLab์ด ์ œ๊ณตํ•˜๋Š” ๋ช‡ ๊ฐ€์ง€ ๋…ํŠนํ•œ ์ธก๋ฉด์„ ์‚ดํŽด๋ณด์„ธ์š”:

  • ๊ฐ„ํŽธํ•œ ์…€ ๊ด€๋ฆฌ: ์ฃผํ”ผํ„ฐ๋žฉ์—์„œ ์…€์„ ๊ด€๋ฆฌํ•˜๋Š” ๊ฒƒ์€ ๋งค์šฐ ์‰ฝ์Šต๋‹ˆ๋‹ค. ๋ฒˆ๊ฑฐ๋กœ์šด ์ž˜๋ผ๋‚ด๊ธฐ ๋ฐ ๋ถ™์—ฌ๋„ฃ๊ธฐ ๋ฐฉ์‹ ๋Œ€์‹  ์…€์„ ๋Œ์–ด๋‹ค ๋†“๊ธฐ๋งŒ ํ•˜๋ฉด ์…€์„ ์žฌ๋ฐฐ์น˜ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
  • ๋…ธํŠธ๋ถ ๊ฐ„ ์…€ ๋ณต์‚ฌ: JupyterLab์„ ์‚ฌ์šฉํ•˜๋ฉด ๋‹ค๋ฅธ ๋…ธํŠธ๋ถ ๊ฐ„์— ์…€์„ ๊ฐ„ํŽธํ•˜๊ฒŒ ๋ณต์‚ฌํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํ•œ ๋…ธํŠธ๋ถ์—์„œ ๋‹ค๋ฅธ ๋…ธํŠธ๋ถ์œผ๋กœ ์…€์„ ๋Œ์–ด๋‹ค ๋†“์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
  • ํด๋ž˜์‹ ๋…ธํŠธ๋ถ ๋ณด๊ธฐ๋กœ ๊ฐ„ํŽธํ•˜๊ฒŒ ์ „ํ™˜: ํด๋ž˜์‹ Jupyter ๋…ธํŠธ๋ถ ์ธํ„ฐํŽ˜์ด์Šค๋ฅผ ๊ทธ๋ฆฌ์›Œํ•˜๋Š” ๋ถ„๋“ค์„ ์œ„ํ•ด JupyterLab์€ ๊ฐ„ํŽธํ•˜๊ฒŒ ๋‹ค์‹œ ์ „ํ™˜ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ๋Šฅ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๊ฐ„๋‹จํžˆ ๊ต์ฒดํ•˜์„ธ์š”. /lab ๋ฅผ URL์— /tree ์„ ํด๋ฆญํ•ด ์ต์ˆ™ํ•œ ๋…ธํŠธ๋ถ ๋ณด๊ธฐ๋กœ ๋Œ์•„๊ฐ‘๋‹ˆ๋‹ค.
  • ๋‹ค์ค‘ ๋ณด๊ธฐ: JupyterLab์€ ๋™์ผํ•œ ๋…ธํŠธ๋ถ์˜ ์—ฌ๋Ÿฌ ๋ณด๊ธฐ๋ฅผ ์ง€์›ํ•˜๋ฏ€๋กœ, ํŠนํžˆ ๊ธด ๋…ธํŠธ๋ถ์— ์œ ์šฉํ•ฉ๋‹ˆ๋‹ค. ์„œ๋กœ ๋‹ค๋ฅธ ์„น์…˜์„ ๋‚˜๋ž€ํžˆ ์—ด์–ด ๋น„๊ตํ•˜๊ฑฐ๋‚˜ ํƒ์ƒ‰ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ํ•œ ๋ณด๊ธฐ์—์„œ ๋ณ€๊ฒฝํ•œ ๋‚ด์šฉ์€ ๋‹ค๋ฅธ ๋ณด๊ธฐ์—๋„ ๋ฐ˜์˜๋ฉ๋‹ˆ๋‹ค.
  • ์‚ฌ์šฉ์ž ์ง€์ • ๊ฐ€๋Šฅํ•œ ํ…Œ๋งˆ: ์ฃผํ”ผํ„ฐ๋žฉ์—๋Š” ๋…ธํŠธ๋ถ์— ๋‚ด์žฅ๋œ ๋‹คํฌ ํ…Œ๋งˆ๊ฐ€ ํฌํ•จ๋˜์–ด ์žˆ์–ด ๋Šฆ์€ ๋ฐค ์ฝ”๋”ฉ ์„ธ์…˜์— ์ ํ•ฉํ•ฉ๋‹ˆ๋‹ค. ํ…์ŠคํŠธ ํŽธ์ง‘๊ธฐ์™€ ํ„ฐ๋ฏธ๋„์— ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ํ…Œ๋งˆ๋„ ์žˆ์–ด ์ „์ฒด ์ž‘์—… ๊ณต๊ฐ„์˜ ๋ชจ์–‘์„ ์‚ฌ์šฉ์ž ์ง€์ •ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

์ฃผํ”ผํ„ฐ๋žฉ ์ž‘์—… ์‹œ ๋ฐœ์ƒํ•˜๋Š” ์ผ๋ฐ˜์ ์ธ ๋ฌธ์ œ

Kaggle๋กœ ์ž‘์—…ํ•  ๋•Œ ๋ช‡ ๊ฐ€์ง€ ์ผ๋ฐ˜์ ์ธ ๋ฌธ์ œ์— ์ง๋ฉดํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋‹ค์Œ์€ ํ”Œ๋žซํผ์„ ์›ํ™œํ•˜๊ฒŒ ํƒ์ƒ‰ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ๋ช‡ ๊ฐ€์ง€ ํŒ์ž…๋‹ˆ๋‹ค:

  • ์ปค๋„ ๊ด€๋ฆฌํ•˜๊ธฐ: ์ปค๋„์€ JupyterLab์—์„œ ์ž‘์„ฑํ•œ ์ฝ”๋“œ์™€ ์ฝ”๋“œ๊ฐ€ ์‹คํ–‰๋˜๋Š” ํ™˜๊ฒฝ ์‚ฌ์ด์˜ ์—ฐ๊ฒฐ์„ ๊ด€๋ฆฌํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋งค์šฐ ์ค‘์š”ํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ ๋…ธํŠธ๋ถ ๊ฐ„์— ๋ฐ์ดํ„ฐ๋ฅผ ์•ก์„ธ์Šคํ•˜๊ณ  ๊ณต์œ ํ•  ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค. ๋‹ค๋ฅธ ๋…ธํŠธ๋ถ์—์„œ ์ปค๋„์„ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ์„ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— Jupyter ๋…ธํŠธ๋ถ์„ ๋‹ซ์•„๋„ ์ปค๋„์€ ๊ณ„์† ์‹คํ–‰ ์ค‘์ผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ปค๋„์„ ์™„์ „ํžˆ ์ข…๋ฃŒํ•˜๋ ค๋ฉด ์ปค๋„์„ ์„ ํƒํ•˜๊ณ  ๋งˆ์šฐ์Šค ์˜ค๋ฅธ์ชฝ ๋ฒ„ํŠผ์„ ํด๋ฆญํ•œ ๋‹ค์Œ ํŒ์—… ๋ฉ”๋‰ด์—์„œ "์ปค๋„ ์ข…๋ฃŒ"๋ฅผ ์„ ํƒํ•˜๋ฉด ๋ฉ๋‹ˆ๋‹ค.
  • Python ํŒจํ‚ค์ง€ ์„ค์น˜: ์„œ๋ฒ„์— ์‚ฌ์ „ ์„ค์น˜๋˜์ง€ ์•Š์€ Python ํŒจํ‚ค์ง€๊ฐ€ ์ถ”๊ฐ€๋กœ ํ•„์š”ํ•œ ๊ฒฝ์šฐ๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค. ๋‹ค์Œ ๋ช…๋ น์„ ์‚ฌ์šฉํ•˜์—ฌ ํ™ˆ ๋””๋ ‰ํ† ๋ฆฌ ๋˜๋Š” ๊ฐ€์ƒ ํ™˜๊ฒฝ์— ์ด๋Ÿฌํ•œ ํŒจํ‚ค์ง€๋ฅผ ์‰ฝ๊ฒŒ ์„ค์น˜ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. python -m pip install package-name. ์„ค์น˜๋œ ๋ชจ๋“  ํŒจํ‚ค์ง€๋ฅผ ๋ณด๋ ค๋ฉด python -m pip list.
  • ํฌ์ง€ํŠธ ์ปค๋„ฅํŠธ์— ํ”Œ๋ผ์Šคํฌ/FastAPI API ๋ฐฐํฌํ•˜๊ธฐ: ํ„ฐ๋ฏธ๋„์—์„œ rsconnect-python ํŒจํ‚ค์ง€๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ Flask ๋ฐ FastAPI API๋ฅผ Posit Connect์— ๋ฐฐํฌํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋ ‡๊ฒŒ ํ•˜๋ฉด ์›น ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์„ JupyterLab๊ณผ ๋” ์‰ฝ๊ฒŒ ํ†ตํ•ฉํ•˜๊ณ  ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค๊ณผ ๊ณต์œ ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
  • ์ฃผํ”ผํ„ฐ๋žฉ ํ™•์žฅ ํ”„๋กœ๊ทธ๋žจ ์„ค์น˜ํ•˜๊ธฐ: ์ฃผํ”ผํ„ฐ๋žฉ์€ ๊ธฐ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ํ™•์žฅ ๊ธฐ๋Šฅ์„ ์ง€์›ํ•ฉ๋‹ˆ๋‹ค. ํ•„์š”์— ๋”ฐ๋ผ ์ด๋Ÿฌํ•œ ํ™•์žฅ ๊ธฐ๋Šฅ์„ ์„ค์น˜ํ•˜๊ณ  ์‚ฌ์šฉ์ž ์ง€์ •ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ž์„ธํ•œ ์ง€์นจ์€ JupyterLab ํ™•์žฅ ํ”„๋กœ๊ทธ๋žจ ๊ฐ€์ด๋“œ๋ฅผ ์ฐธ์กฐํ•˜์„ธ์š”.
  • Python ์˜ ์—ฌ๋Ÿฌ ๋ฒ„์ „ ์‚ฌ์šฉํ•˜๊ธฐ: Python ์˜ ๋‹ค๋ฅธ ๋ฒ„์ „์œผ๋กœ ์ž‘์—…ํ•ด์•ผ ํ•˜๋Š” ๊ฒฝ์šฐ ๋‹ค๋ฅธ Python ๋ฒ„์ „์œผ๋กœ ๊ตฌ์„ฑ๋œ Jupyter ์ปค๋„์„ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

How to Use JupyterLab to Try Out YOLO11

JupyterLab makes it easy to experiment with YOLO11. To get started, follow these simple steps.

1๋‹จ๊ณ„: ์ฃผํ”ผํ„ฐ๋žฉ ์„ค์น˜ํ•˜๊ธฐ

๋จผ์ € JupyterLab์„ ์„ค์น˜ํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ํ„ฐ๋ฏธ๋„์„ ์—ด๊ณ  ๋ช…๋ น์„ ์‹คํ–‰ํ•ฉ๋‹ˆ๋‹ค:

์„ค์น˜

# Install the required package for JupyterLab
pip install jupyterlab

Step 2: Download the YOLO11 Tutorial Notebook

๊ทธ๋Ÿฐ ๋‹ค์Œ Ultralytics GitHub ๋ฆฌํฌ์ง€ํ† ๋ฆฌ์—์„œ tutorial.ipynb ํŒŒ์ผ์„ ๋‹ค์šด๋กœ๋“œํ•ฉ๋‹ˆ๋‹ค. ์ด ํŒŒ์ผ์„ ๋กœ์ปฌ ์ปดํ“จํ„ฐ์˜ ์•„๋ฌด ๋””๋ ‰ํ„ฐ๋ฆฌ์—๋‚˜ ์ €์žฅํ•ฉ๋‹ˆ๋‹ค.

3๋‹จ๊ณ„: JupyterLab ์‹œ์ž‘ํ•˜๊ธฐ

ํ„ฐ๋ฏธ๋„์„ ์‚ฌ์šฉํ•ด ๋…ธํŠธ๋ถ ํŒŒ์ผ์„ ์ €์žฅํ•œ ๋””๋ ‰ํ† ๋ฆฌ๋กœ ์ด๋™ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Ÿฐ ๋‹ค์Œ ๋‹ค์Œ ๋ช…๋ น์„ ์‹คํ–‰ํ•˜์—ฌ JupyterLab์„ ์‹œ์ž‘ํ•ฉ๋‹ˆ๋‹ค:

์‚ฌ์šฉ๋ฒ•

jupyter lab

์ด ๋ช…๋ น์„ ์‹คํ–‰ํ•˜๋ฉด ์•„๋ž˜์™€ ๊ฐ™์ด ๊ธฐ๋ณธ ์›น ๋ธŒ๋ผ์šฐ์ €์—์„œ JupyterLab์ด ์—ด๋ฆฝ๋‹ˆ๋‹ค.

๋ธŒ๋ผ์šฐ์ €์—์„œ ์ฃผํ”ผํ„ฐ๋žฉ์ด ์—ด๋ฆฌ๋Š” ๋ชจ์Šต์„ ๋ณด์—ฌ์ฃผ๋Š” ์ด๋ฏธ์ง€

4๋‹จ๊ณ„: ์‹คํ—˜ ์‹œ์ž‘

In JupyterLab, open the tutorial.ipynb notebook. You can now start running the cells to explore and experiment with YOLO11.

Image Showing Opened YOLO11 Notebook in JupyterLab

JupyterLab's interactive environment allows you to modify code, visualize outputs, and document your findings all in one place. You can try out different configurations and understand how YOLO11 works.

For a detailed understanding of the model training process and best practices, refer to the YOLO11 Model Training guide. This guide will help you get the most out of your experiments and ensure you're using YOLO11 effectively.

์ฃผํ”ผํ„ฐ๋žฉ์— ๋Œ€ํ•ด ๊ณ„์† ์•Œ์•„๋ณด๊ธฐ

์ฃผํ”ผํ„ฐ๋žฉ์— ๋Œ€ํ•ด ์ž์„ธํžˆ ์•Œ์•„๋ณด๊ณ  ์‹ถ์œผ์‹œ๋‹ค๋ฉด ์‹œ์ž‘์— ๋„์›€์ด ๋˜๋Š” ๋ช‡ ๊ฐ€์ง€ ํ›Œ๋ฅญํ•œ ๋ฆฌ์†Œ์Šค๋ฅผ ํ™•์ธํ•ด๋ณด์„ธ์š”:

  • ์ฃผํ”ผํ„ฐ๋žฉ ๋ฌธ์„œ: ์ฃผํ”ผํ„ฐ๋žฉ ๊ณต์‹ ๋ฌธ์„œ๋ฅผ ํ†ตํ•ด ์ฃผํ”ผํ„ฐ๋žฉ์˜ ํŠน์ง•๊ณผ ๊ธฐ๋Šฅ์„ ์‚ดํŽด๋ณด์„ธ์š”. ์ด ๊ฐ•๋ ฅํ•œ ๋„๊ตฌ๋ฅผ ์ตœ๋Œ€ํ•œ ํ™œ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ดํ•ดํ•  ์ˆ˜ ์žˆ๋Š” ์ข‹์€ ๋ฐฉ๋ฒ•์ž…๋‹ˆ๋‹ค.
  • ๋ฐ”์ธ๋”๋กœ ์‚ฌ์šฉํ•ด ๋ณด๊ธฐ: ๋ธŒ๋ผ์šฐ์ €์—์„œ ๋ฐ”๋กœ ๋ผ์ด๋ธŒ JupyterLab ์ธ์Šคํ„ด์Šค๋ฅผ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” Binder๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์•„๋ฌด๊ฒƒ๋„ ์„ค์น˜ํ•˜์ง€ ์•Š๊ณ ๋„ JupyterLab์„ ์‹คํ—˜ํ•ด ๋ณด์„ธ์š”. ์ฆ‰์‹œ ์‹คํ—˜์„ ์‹œ์ž‘ํ•  ์ˆ˜ ์žˆ๋Š” ์ข‹์€ ๋ฐฉ๋ฒ•์ž…๋‹ˆ๋‹ค.
  • ์„ค์น˜ ๊ฐ€์ด๋“œ: ๋กœ์ปฌ ์ปดํ“จํ„ฐ์— ์ฃผํ”ผํ„ฐ๋žฉ์„ ์„ค์น˜ํ•˜๋Š” ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๋‹จ๊ณ„๋ณ„ ๊ฐ€์ด๋“œ๋Š” ์„ค์น˜ ๊ฐ€์ด๋“œ๋ฅผ ์ฐธ์กฐํ•˜์„ธ์š”.

์š”์•ฝ

We've explored how JupyterLab can be a powerful tool for experimenting with Ultralytics YOLO11 models. Using its flexible and interactive environment, you can easily set up JupyterLab on your local machine and start working with YOLO11. JupyterLab makes it simple to train and evaluate your models, visualize outputs, and document your findings all in one place.

์ž์„ธํ•œ ๋‚ด์šฉ์€ ์ฃผํ”ผํ„ฐ๋žฉ FAQ ํŽ˜์ด์ง€์—์„œ ํ™•์ธํ•˜์„ธ์š”.

Interested in more YOLO11 integrations? Check out the Ultralytics integration guide to explore additional tools and capabilities for your machine learning projects.

์ž์ฃผ ๋ฌป๋Š” ์งˆ๋ฌธ

How do I use JupyterLab to train a YOLO11 model?

To train a YOLO11 model using JupyterLab:

  1. ์ฃผํ”ผํ„ฐ๋žฉ๊ณผ Ultralytics ํŒจํ‚ค์ง€๋ฅผ ์„ค์น˜ํ•ฉ๋‹ˆ๋‹ค:

    pip install jupyterlab ultralytics
    
  2. JupyterLab์„ ์‹คํ–‰ํ•˜๊ณ  ์ƒˆ ๋…ธํŠธ๋ถ์„ ์—ฝ๋‹ˆ๋‹ค.

  3. YOLO ๋ชจ๋ธ์„ ๊ฐ€์ ธ์™€์„œ ๋ฏธ๋ฆฌ ํ•™์Šต๋œ ๋ชจ๋ธ์„ ๋กœ๋“œํ•ฉ๋‹ˆ๋‹ค:

    from ultralytics import YOLO
    
    model = YOLO("yolo11n.pt")
    
  4. ์‚ฌ์šฉ์ž ์ง€์ • ๋ฐ์ดํ„ฐ ์„ธํŠธ์—์„œ ๋ชจ๋ธ์„ ํ•™์Šต์‹œํ‚ต๋‹ˆ๋‹ค:

    results = model.train(data="path/to/your/data.yaml", epochs=100, imgsz=640)
    
  5. ์ฃผํ”ผํ„ฐ๋žฉ์— ๋‚ด์žฅ๋œ ํ”Œ๋กœํŒ… ๊ธฐ๋Šฅ์„ ์‚ฌ์šฉํ•˜์—ฌ ํ›ˆ๋ จ ๊ฒฐ๊ณผ๋ฅผ ์‹œ๊ฐํ™”ํ•˜์„ธ์š”:

    %matplotlib inline
    from ultralytics.utils.plotting import plot_results
    plot_results(results)
    

์ฃผํ”ผํ„ฐ๋žฉ์˜ ๋Œ€ํ™”ํ˜• ํ™˜๊ฒฝ์„ ์‚ฌ์šฉํ•˜๋ฉด ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์‰ฝ๊ฒŒ ์ˆ˜์ •ํ•˜๊ณ , ๊ฒฐ๊ณผ๋ฅผ ์‹œ๊ฐํ™”ํ•˜๋ฉฐ, ๋ชจ๋ธ ํ•™์Šต ํ”„๋กœ์„ธ์Šค๋ฅผ ๋ฐ˜๋ณตํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

What are the key features of JupyterLab that make it suitable for YOLO11 projects?

JupyterLab offers several features that make it ideal for YOLO11 projects:

  1. Interactive code execution: Test and debug YOLO11 code snippets in real-time.
  2. ํ†ตํ•ฉ ํŒŒ์ผ ๋ธŒ๋ผ์šฐ์ €: ๋ฐ์ดํ„ฐ ์„ธํŠธ, ๋ชจ๋ธ ๊ฐ€์ค‘์น˜, ๊ตฌ์„ฑ ํŒŒ์ผ์„ ์‰ฝ๊ฒŒ ๊ด€๋ฆฌํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
  3. ์œ ์—ฐํ•œ ๋ ˆ์ด์•„์›ƒ: ์—ฌ๋Ÿฌ ๊ฐœ์˜ ๋…ธํŠธ๋ถ, ๋‹จ๋ง๊ธฐ, ์ถœ๋ ฅ ์ฐฝ์„ ๋‚˜๋ž€ํžˆ ๋ฐฐ์น˜ํ•ด ํšจ์œจ์ ์ธ ์›Œํฌํ”Œ๋กœ์šฐ๋ฅผ ๋งŒ๋“œ์„ธ์š”.
  4. Rich output display: Visualize YOLO11 detection results, training curves, and model performance metrics inline.
  5. Markdown support: Document your YOLO11 experiments and findings with rich text and images.
  6. ํ™•์žฅ ํ”„๋กœ๊ทธ๋žจ ์—์ฝ”์‹œ์Šคํ…œ: ๋ฒ„์ „ ๊ด€๋ฆฌ, ์›๊ฒฉ ์ปดํ“จํŒ… ๋“ฑ์„ ์œ„ํ•œ ํ™•์žฅ ๊ธฐ๋Šฅ์œผ๋กœ ๊ธฐ๋Šฅ์„ ํ–ฅ์ƒํ•˜์„ธ์š”.

These features allow for a seamless development experience when working with YOLO11 models, from data preparation to model deployment.

How can I optimize YOLO11 model performance using JupyterLab?

To optimize YOLO11 model performance in JupyterLab:

  1. ์ž๋™ ๋ฐฐ์น˜ ๊ธฐ๋Šฅ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ตœ์ ์˜ ๋ฐฐ์น˜ ํฌ๊ธฐ๋ฅผ ๊ฒฐ์ •ํ•˜์„ธ์š”:

    from ultralytics.utils.autobatch import autobatch
    
    optimal_batch_size = autobatch(model)
    
  2. ๋ ˆ์ด ํŠ ๊ณผ ๊ฐ™์€ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํ•˜์ดํผํŒŒ๋ผ๋ฏธํ„ฐ ํŠœ๋‹์„ ๊ตฌํ˜„ํ•˜์„ธ์š”:

    from ultralytics.utils.tuner import run_ray_tune
    
    best_results = run_ray_tune(model, data="path/to/data.yaml")
    
  3. ์ฃผํ”ผํ„ฐ๋žฉ์˜ ํ”Œ๋กœํŒ… ๊ธฐ๋Šฅ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ชจ๋ธ ๋ฉ”ํŠธ๋ฆญ์„ ์‹œ๊ฐํ™”ํ•˜๊ณ  ๋ถ„์„ํ•˜์„ธ์š”:

    from ultralytics.utils.plotting import plot_results
    
    plot_results(results.results_dict)
    
  4. Experiment with different model architectures and export formats to find the best balance of speed and accuracy for your specific use case.

JupyterLab's interactive environment allows for quick iterations and real-time feedback, making it easier to optimize your YOLO11 models efficiently.

How do I handle common issues when working with JupyterLab and YOLO11?

When working with JupyterLab and YOLO11, you might encounter some common issues. Here's how to handle them:

  1. GPU ๋ฉ”๋ชจ๋ฆฌ ๋ฌธ์ œ:

    • ์‚ฌ์šฉ torch.cuda.empty_cache() ๋ฅผ ํด๋ฆญํ•˜์—ฌ ์‹คํ–‰ ์‚ฌ์ด์— GPU ๋ฉ”๋ชจ๋ฆฌ๋ฅผ ์ง€์›๋‹ˆ๋‹ค.
    • Adjust batch size or image size to fit your GPU memory.
  2. ํŒจํ‚ค์ง€ ์ถฉ๋Œ:

    • Create a separate conda environment for your YOLO11 projects to avoid conflicts.
    • ์‚ฌ์šฉ !pip install package_name ๋ฅผ ๋…ธํŠธ๋ถ ์…€์— ์ถ”๊ฐ€ํ•˜์—ฌ ๋ˆ„๋ฝ๋œ ํŒจํ‚ค์ง€๋ฅผ ์„ค์น˜ํ•˜์„ธ์š”.
  3. ์ปค๋„์ด ์ถฉ๋Œํ•ฉ๋‹ˆ๋‹ค:

    • ์ปค๋„์„ ์žฌ์‹œ์ž‘ํ•˜๊ณ  ์…€์„ ํ•˜๋‚˜์”ฉ ์‹คํ–‰ํ•˜์—ฌ ๋ฌธ์ œ๊ฐ€ ์žˆ๋Š” ์ฝ”๋“œ๋ฅผ ์‹๋ณ„ํ•˜์„ธ์š”.

๐Ÿ“… Created 2 months ago โœ๏ธ Updated 8 days ago

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