์ฝ˜ํ…์ธ ๋กœ ๊ฑด๋„ˆ๋›ฐ๊ธฐ

YOLO11 Model Training Made Simple with Paperspace Gradient

Training computer vision models like YOLO11 can be complicated. It involves managing large datasets, using different types of computer hardware like GPUs, TPUs, and CPUs, and making sure data flows smoothly during the training process. Typically, developers end up spending a lot of time managing their computer systems and environments. It can be frustrating when you just want to focus on building the best model.

This is where a platform like Paperspace Gradient can make things simpler. Paperspace Gradient is a MLOps platform that lets you build, train, and deploy machine learning models all in one place. With Gradient, developers can focus on training their YOLO11 models without the hassle of managing infrastructure and environments.

Paperspace

Paperspace ๊ฐœ์š”

Paperspace2014๋…„ ๋ฏธ์‹œ๊ฐ„ ๋Œ€ํ•™๊ต ์กธ์—…์ƒ๋“ค์ด ์‹œ์ž‘ํ•˜์—ฌ 2023๋…„ DigitalOcean์— ์ธ์ˆ˜๋œ ๋จธ์‹  ๋Ÿฌ๋‹์„ ์œ„ํ•ด ํŠน๋ณ„ํžˆ ์„ค๊ณ„๋œ ํด๋ผ์šฐ๋“œ ํ”Œ๋žซํผ์ž…๋‹ˆ๋‹ค. ์‚ฌ์šฉ์ž์—๊ฒŒ ๊ฐ•๋ ฅํ•œ GPU, ํ˜‘์—…์šฉ Jupyter ๋…ธํŠธ๋ถ, ๋ฐฐํฌ๋ฅผ ์œ„ํ•œ ์ปจํ…Œ์ด๋„ˆ ์„œ๋น„์Šค, ๋จธ์‹  ๋Ÿฌ๋‹ ์ž‘์—…์„ ์œ„ํ•œ ์ž๋™ํ™”๋œ ์›Œํฌํ”Œ๋กœ์šฐ, ๊ณ ์„ฑ๋Šฅ ๊ฐ€์ƒ ๋จธ์‹ ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ธฐ๋Šฅ์€ ์ฝ”๋”ฉ๋ถ€ํ„ฐ ๋ฐฐํฌ๊นŒ์ง€ ์ „์ฒด ๋จธ์‹  ๋Ÿฌ๋‹ ๊ฐœ๋ฐœ ํ”„๋กœ์„ธ์Šค๋ฅผ ๊ฐ„์†Œํ™”ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•ฉ๋‹ˆ๋‹ค.

Paperspace ๊ทธ๋ผ๋ฐ์ด์…˜

PaperSpace ๊ทธ๋ผ๋ฐ์ด์…˜ ๊ฐœ์š”

Paperspace Gradient๋Š” ํด๋ผ์šฐ๋“œ์—์„œ AI ๋ฐ ๋จธ์‹  ๋Ÿฌ๋‹ ์ž‘์—…์„ ํ›จ์”ฌ ๋น ๋ฅด๊ณ  ์‰ฝ๊ฒŒ ํ•  ์ˆ˜ ์žˆ๋„๋ก ์„ค๊ณ„๋œ ๋„๊ตฌ ๋ชจ์Œ์ž…๋‹ˆ๋‹ค. Gradient๋Š” ๋ชจ๋ธ ๊ตฌ์ถ• ๋ฐ ํ•™์Šต๋ถ€ํ„ฐ ๋ฐฐํฌ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ์ „์ฒด ๋จธ์‹  ๋Ÿฌ๋‹ ๊ฐœ๋ฐœ ํ”„๋กœ์„ธ์Šค๋ฅผ ๋‹ค๋ฃน๋‹ˆ๋‹ค.

์ด ํˆดํ‚ท์—๋Š” ์žก ๋Ÿฌ๋„ˆ๋ฅผ ํ†ตํ•œ Google ์˜ TPU ์ง€์›, Jupyter ๋…ธํŠธ๋ถ ๋ฐ ์ปจํ…Œ์ด๋„ˆ์— ๋Œ€ํ•œ ํฌ๊ด„์ ์ธ ์ง€์›, ์ƒˆ๋กœ์šด ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด ํ†ตํ•ฉ์ด ํฌํ•จ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ ์–ธ์–ด ํ†ตํ•ฉ์— ์ค‘์ ์„ ๋‘์–ด ์‚ฌ์šฉ์ž๊ฐ€ ๊ธฐ์กด Python ํ”„๋กœ์ ํŠธ๋ฅผ ๊ฐ€์žฅ ์ตœ์‹ ์˜ GPU ์ธํ”„๋ผ๋ฅผ ์‚ฌ์šฉํ•˜๋„๋ก ์‰ฝ๊ฒŒ ์กฐ์ •ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Training YOLO11 Using Paperspace Gradient

Paperspace Gradient makes training a YOLO11 model possible with a few clicks. Thanks to the integration, you can access the Paperspace console and start training your model immediately. For a detailed understanding of the model training process and best practices, refer to our YOLO11 Model Training guide.

๋กœ๊ทธ์ธํ•œ ๋‹ค์Œ ์•„๋ž˜ ์ด๋ฏธ์ง€์— ํ‘œ์‹œ๋œ '์ปดํ“จํ„ฐ ์‹œ์ž‘' ๋ฒ„ํŠผ์„ ํด๋ฆญํ•ฉ๋‹ˆ๋‹ค. ๋ช‡ ์ดˆ ํ›„ ๊ด€๋ฆฌ๋˜๋Š” GPU ํ™˜๊ฒฝ์ด ์‹œ์ž‘๋˜๊ณ  ๋…ธํŠธ๋ถ์˜ ์…€์„ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Training YOLO11 Using Paperspace Gradient

Explore more capabilities of YOLO11 and Paperspace Gradient in a discussion with Glenn Jocher, Ultralytics founder, and James Skelton from Paperspace. Watch the discussion below.



Watch: Ultralytics Live Session 7: It's All About the Environment: Optimizing YOLO11 Training With Gradient

Paperspace ๊ทธ๋ผ๋ฐ์ด์…˜์˜ ์ฃผ์š” ๊ธฐ๋Šฅ

Paperspace ์ฝ˜์†”์„ ์‚ดํŽด๋ณด๋ฉด ๋จธ์‹  ๋Ÿฌ๋‹ ์›Œํฌํ”Œ๋กœ์šฐ์˜ ๊ฐ ๋‹จ๊ณ„๊ฐ€ ์–ด๋–ป๊ฒŒ ์ง€์›๋˜๊ณ  ๊ฐœ์„ ๋˜๋Š”์ง€ ํ™•์ธํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋‹ค์Œ์€ ๋ช‡ ๊ฐ€์ง€ ์ฃผ์˜ํ•ด์•ผ ํ•  ์‚ฌํ•ญ์ž…๋‹ˆ๋‹ค:

  • One-Click Notebooks: Gradient provides pre-configured Jupyter Notebooks specifically tailored for YOLO11, eliminating the need for environment setup and dependency management. Simply choose the desired notebook and start experimenting immediately.

  • ํ•˜๋“œ์›จ์–ด ์œ ์—ฐ์„ฑ: ๋‹ค์–‘ํ•œ CPU, GPU, TPU ๊ตฌ์„ฑ์˜ ๋‹ค์–‘ํ•œ ๋จธ์‹  ์œ ํ˜• ์ค‘์—์„œ ๊ต์œก ์š”๊ตฌ ์‚ฌํ•ญ๊ณผ ์˜ˆ์‚ฐ์— ๋งž๊ฒŒ ์„ ํƒํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋ผ๋””์–ธํŠธ๋Š” ๋ชจ๋“  ๋ฐฑ์—”๋“œ ์„ค์ •์„ ์ฒ˜๋ฆฌํ•˜๋ฏ€๋กœ ์‚ฌ์šฉ์ž๋Š” ๋ชจ๋ธ ๊ฐœ๋ฐœ์— ์ง‘์ค‘ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

  • ์‹คํ—˜ ์ถ”์ : ๊ทธ๋ผ๋””์–ธํŠธ๋Š” ํ•˜์ดํผํŒŒ๋ผ๋ฏธํ„ฐ, ๋ฉ”ํŠธ๋ฆญ, ์ฝ”๋“œ ๋ณ€๊ฒฝ์„ ํฌํ•จํ•œ ์‹คํ—˜์„ ์ž๋™์œผ๋กœ ์ถ”์ ํ•ฉ๋‹ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ํŠธ๋ ˆ์ด๋‹ ์‹คํ–‰์„ ์‰ฝ๊ฒŒ ๋น„๊ตํ•˜๊ณ , ์ตœ์ ์˜ ๊ตฌ์„ฑ์„ ์‹๋ณ„ํ•˜๊ณ , ์„ฑ๊ณต์ ์ธ ๊ฒฐ๊ณผ๋ฅผ ์žฌํ˜„ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

  • ๋ฐ์ดํ„ฐ ์„ธํŠธ ๊ด€๋ฆฌ: Gradient ๋‚ด์—์„œ ์ง์ ‘ ๋ฐ์ดํ„ฐ์„ธํŠธ๋ฅผ ํšจ์œจ์ ์œผ๋กœ ๊ด€๋ฆฌํ•˜์„ธ์š”. ๋ฐ์ดํ„ฐ๋ฅผ ์‰ฝ๊ฒŒ ์—…๋กœ๋“œ, ๋ฒ„์ „ ๊ด€๋ฆฌ ๋ฐ ์‚ฌ์ „ ์ฒ˜๋ฆฌํ•˜์—ฌ ํ”„๋กœ์ ํŠธ์˜ ๋ฐ์ดํ„ฐ ์ค€๋น„ ๋‹จ๊ณ„๋ฅผ ๊ฐ„์†Œํ™”ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

  • Model Serving: Deploy your trained YOLO11 models as REST APIs with just a few clicks. Gradient handles the infrastructure, allowing you to easily integrate your object detection models into your applications.

  • ์‹ค์‹œ๊ฐ„ ๋ชจ๋‹ˆํ„ฐ๋ง: Gradient์˜ ์ง๊ด€์ ์ธ ๋Œ€์‹œ๋ณด๋“œ๋ฅผ ํ†ตํ•ด ๋ฐฐํฌ๋œ ๋ชจ๋ธ์˜ ์„ฑ๋Šฅ๊ณผ ์ƒํƒœ๋ฅผ ๋ชจ๋‹ˆํ„ฐ๋งํ•˜์„ธ์š”. ์ถ”๋ก  ์†๋„, ๋ฆฌ์†Œ์Šค ์‚ฌ์šฉ๋ฅ , ์ž ์žฌ์  ์˜ค๋ฅ˜์— ๋Œ€ํ•œ ์ธ์‚ฌ์ดํŠธ๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Why Should You Use Gradient for Your YOLO11 Projects?

While many options are available for training, deploying, and evaluating YOLO11 models, the integration with Paperspace Gradient offers a unique set of advantages that separates it from other solutions. Let's explore what makes this integration unique:

  • ํ–ฅ์ƒ๋œ ํ˜‘์—…: ๊ณต์œ  ์ž‘์—… ๊ณต๊ฐ„๊ณผ ๋ฒ„์ „ ์ œ์–ด๋Š” ์›ํ™œํ•œ ํŒ€์›Œํฌ๋ฅผ ์ด‰์ง„ํ•˜๊ณ  ์žฌํ˜„์„ฑ์„ ๋ณด์žฅํ•˜์—ฌ ํŒ€์ด ํšจ๊ณผ์ ์œผ๋กœ ํ˜‘์—…ํ•˜๊ณ  ํ”„๋กœ์ ํŠธ์˜ ๋ช…ํ™•ํ•œ ๊ธฐ๋ก์„ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•ฉ๋‹ˆ๋‹ค.

  • ์ €๋น„์šฉ GPU: Gradient๋Š” ์ฃผ์š” ํด๋ผ์šฐ๋“œ ์ œ๊ณต์—…์ฒด๋‚˜ ์˜จํ”„๋ ˆ๋ฏธ์Šค ์†”๋ฃจ์…˜๋ณด๋‹ค ํ›จ์”ฌ ์ €๋ ดํ•œ ๋น„์šฉ์œผ๋กœ ๊ณ ์„ฑ๋Šฅ GPU์— ์•ก์„ธ์Šคํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ดˆ๋‹น ๊ณผ๊ธˆ ๋ฐฉ์‹์„ ์‚ฌ์šฉํ•˜๋ฉด ์‹ค์ œ๋กœ ์‚ฌ์šฉํ•œ ๋ฆฌ์†Œ์Šค์— ๋Œ€ํ•ด์„œ๋งŒ ๋น„์šฉ์„ ์ง€๋ถˆํ•˜๋ฏ€๋กœ ์˜ˆ์‚ฐ์„ ์ตœ์ ํ™”ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

  • ์˜ˆ์ธก ๊ฐ€๋Šฅํ•œ ๋น„์šฉ: Gradient์˜ ์˜จ๋””๋งจ๋“œ ์š”๊ธˆ์ œ๋Š” ๋น„์šฉ ํˆฌ๋ช…์„ฑ๊ณผ ์˜ˆ์ธก ๊ฐ€๋Šฅ์„ฑ์„ ๋ณด์žฅํ•ฉ๋‹ˆ๋‹ค. ํ•„์š”์— ๋”ฐ๋ผ ๋ฆฌ์†Œ์Šค๋ฅผ ํ™•์žฅํ•˜๊ฑฐ๋‚˜ ์ถ•์†Œํ•˜๊ณ  ์‚ฌ์šฉํ•œ ์‹œ๊ฐ„๋งŒํผ๋งŒ ๋น„์šฉ์„ ์ง€๋ถˆํ•˜์—ฌ ๋ถˆํ•„์š”ํ•œ ๋น„์šฉ์„ ํ”ผํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

  • ์•ฝ์ • ์—†์Œ: ์ธ์Šคํ„ด์Šค ์œ ํ˜•์„ ์–ธ์ œ๋“ ์ง€ ์กฐ์ •ํ•˜์—ฌ ๋ณ€ํ™”ํ•˜๋Š” ํ”„๋กœ์ ํŠธ ์š”๊ตฌ์‚ฌํ•ญ์— ์ ์‘ํ•˜๊ณ  ๋น„์šฉ ๋Œ€๋น„ ์„ฑ๋Šฅ ๊ท ํ˜•์„ ์ตœ์ ํ™”ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฝ์ธ ๊ธฐ๊ฐ„์ด๋‚˜ ์•ฝ์ •์ด ์—†์œผ๋ฏ€๋กœ ์œ ์—ฐ์„ฑ์ด ๊ทน๋Œ€ํ™”๋ฉ๋‹ˆ๋‹ค.

์š”์•ฝ

This guide explored the Paperspace Gradient integration for training YOLO11 models. Gradient provides the tools and infrastructure to accelerate your AI development journey from effortless model training and evaluation to streamlined deployment options.

์ž์„ธํ•œ ๋‚ด์šฉ์€ PaperSpace ์˜ ๊ณต์‹ ๋ฌธ์„œ๋ฅผ ์ฐธ์กฐํ•˜์„ธ์š”.

Also, visit the Ultralytics integration guide page to learn more about different YOLO11 integrations. It's full of insights and tips to take your computer vision projects to the next level.

์ž์ฃผ ๋ฌป๋Š” ์งˆ๋ฌธ

How do I train a YOLO11 model using Paperspace Gradient?

Training a YOLO11 model with Paperspace Gradient is straightforward and efficient. First, sign in to the Paperspace console. Next, click the โ€œStart Machineโ€ button to initiate a managed GPU environment. Once the environment is ready, you can run the notebook's cells to start training your YOLO11 model. For detailed instructions, refer to our YOLO11 Model Training guide.

What are the advantages of using Paperspace Gradient for YOLO11 projects?

Paperspace Gradient offers several unique advantages for training and deploying YOLO11 models:

  • ํ•˜๋“œ์›จ์–ด ์œ ์—ฐ์„ฑ: ๋‹ค์–‘ํ•œ CPU, GPU, TPU ๊ตฌ์„ฑ ์ค‘์—์„œ ์„ ํƒํ•˜์„ธ์š”.
  • One-Click Notebooks: Use pre-configured Jupyter Notebooks for YOLO11 without worrying about environment setup.
  • ์‹คํ—˜ ์ถ”์ : ํ•˜์ดํผํŒŒ๋ผ๋ฏธํ„ฐ, ๋ฉ”ํŠธ๋ฆญ ๋ฐ ์ฝ”๋“œ ๋ณ€๊ฒฝ ์‚ฌํ•ญ์„ ์ž๋™์œผ๋กœ ์ถ”์ ํ•ฉ๋‹ˆ๋‹ค.
  • ๋ฐ์ดํ„ฐ ์„ธํŠธ ๊ด€๋ฆฌ: Gradient ๋‚ด์—์„œ ๋ฐ์ดํ„ฐ์„ธํŠธ๋ฅผ ํšจ์œจ์ ์œผ๋กœ ๊ด€๋ฆฌํ•˜์„ธ์š”.
  • ๋ชจ๋ธ ์ œ๊ณต: ๋ชจ๋ธ์„ REST API๋กœ ์‰ฝ๊ฒŒ ๋ฐฐํฌํ•˜์„ธ์š”.
  • ์‹ค์‹œ๊ฐ„ ๋ชจ๋‹ˆํ„ฐ๋ง: ๋Œ€์‹œ๋ณด๋“œ๋ฅผ ํ†ตํ•ด ๋ชจ๋ธ ์„ฑ๋Šฅ ๋ฐ ๋ฆฌ์†Œ์Šค ์‚ฌ์šฉ๋ฅ ์„ ๋ชจ๋‹ˆํ„ฐ๋งํ•˜์„ธ์š”.

Why should I choose Ultralytics YOLO11 over other object detection models?

Ultralytics YOLO11 stands out for its real-time object detection capabilities and high accuracy. Its seamless integration with platforms like Paperspace Gradient enhances productivity by simplifying the training and deployment process. YOLO11 supports various use cases, from security systems to retail inventory management. Explore more about YOLO11's advantages here.

Can I deploy my YOLO11 model on edge devices using Paperspace Gradient?

Yes, you can deploy YOLO11 models on edge devices using Paperspace Gradient. The platform supports various deployment formats like TFLite and Edge TPU, which are optimized for edge devices. After training your model on Gradient, refer to our export guide for instructions on converting your model to the desired format.

How does experiment tracking in Paperspace Gradient help improve YOLO11 training?

Paperspace ์—์„œ ์‹คํ—˜ ์ถ”์  ํ•˜์ดํผํŒŒ๋ผ๋ฏธํ„ฐ, ๋ฉ”ํŠธ๋ฆญ ๋ฐ ์ฝ”๋“œ ๋ณ€๊ฒฝ ์‚ฌํ•ญ์„ ์ž๋™์œผ๋กœ ๊ธฐ๋กํ•˜์—ฌ ๋ชจ๋ธ ๊ฐœ๋ฐœ ํ”„๋กœ์„ธ์Šค๋ฅผ ๊ฐ„์†Œํ™”ํ•ฉ๋‹ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ํ›ˆ๋ จ ์‹คํ–‰์„ ์‰ฝ๊ฒŒ ๋น„๊ตํ•˜๊ณ , ์ตœ์ ์˜ ๊ตฌ์„ฑ์„ ํŒŒ์•…ํ•˜๊ณ , ์„ฑ๊ณต์ ์ธ ์‹คํ—˜์„ ์žฌํ˜„ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.


๐Ÿ“… Created 5 months ago โœ๏ธ Updated 7 days ago

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