Learn how to deploy the state-of-the-art YOLO11 object detection model to Amazon SageMaker AI for production-ready, real-time inference with GPU acceleration.
Object detection is a critical component in many modern AI applications, from autonomous vehicles to security systems. In this comprehensive guide, I'll walk you through deploying the YOLO11 (You Only Look Once) model to Amazon SageMaker AI, enabling scalable, production-ready object detection in the cloud.
What you'll learn:
| #!/usr/bin/env python3 | |
| """ | |
| Strands Agent using Ollama and IBM Granite model for math calculations and LaTeX formatting. | |
| This script sets up a Gradio interface to interact with a Strands Agent powered by | |
| an Ollama-served IBM Granite model. The agent can perform mathematical calculations | |
| and format responses using LaTeX. | |
| """ | |
| import logging |
| # Author: Gary A. Stafford | |
| # Purpose: Delete all SageMaker Models | |
| # Date: 2024-05-08 | |
| # License: MIT License | |
| # Based on https://gist.github.com/Nxtra/49cde5999de20023e2607433046ca6cf | |
| import boto3 | |
| client = boto3.client("sagemaker") |
| # Author: Gary A. Stafford | |
| # Purpose: Delete all SageMaker Endpoint Configs | |
| # Date: 2024-05-08 | |
| # License: MIT License | |
| # Based on https://gist.github.com/Nxtra/49cde5999de20023e2607433046ca6cf | |
| import boto3 | |
| client = boto3.client("sagemaker") |
| # Install ComfyUI on Ubuntu | |
| apt install python3-pip | |
| sudo apt install python3-pip | |
| git clone https://github.com/comfyanonymous/ComfyUI.git | |
| cd ComfyUI/ | |
| pip install -r requirements.txt | |
| pip install torchvision # error message in terminal |
| # For use with AUTOMATIC1111 on Ubuntu | |
| # current install 2024-06-10: | |
| # version: v1.8.0 | |
| # python: 3.10.12 | |
| # torch: 2.3.0+cu121 | |
| # xformers: 0.0.26.post1 | |
| # gradio: 3.41.2 | |
| # checkpoint: e6bb9ea85b |
| import torch | |
| print(torch.__version__) # e.g., 2.0.0 (at the time of the post) | |
| print(torch.cuda.get_device_name(0)) # e.g., NVIDIA A10G |
| pipeline = DiffusionPipeline.from_pretrained( | |
| model_name_base, | |
| torch_dtype=torch.float16, | |
| ).to(device) | |
| # new LoRA weights from fine-tuning process | |
| pipeline.load_lora_weights( | |
| project_name, | |
| weight_name="pytorch_lora_weights.safetensors" | |
| ) |
| subject_prompt = """oue, photo of a oue electric scooter in a brightly colored | |
| neon-lite city at night, sleek design, smooth curves, colorful, nighttime, | |
| urban environment, futuristic cityscape""" | |
| subject_negative_prompt = """person, people, human, rider, floating objects, daytime, | |
| sunlight, text, words, writing, letters, phrases, trademark, watermark, icon, logo, | |
| banner, signature, username, monochrome, cropped, cut-off, patterned background""" | |
| refiner_prompt = """ultra-high-definition, photorealistic, 8k uhd, high-quality, | |
| ultra sharp detail""" |
| subject_prompt = """oue, photo of a oue electric scooter, sleek, smooth curves, colorful, | |
| daytime, urban, futuristic cityscape""" | |
| subject_negative_prompt = """person, people, human, rider, floating objects, text, | |
| words, writing, letters, phrases, trademark, watermark, icon, logo, banner, signature, | |
| username, monochrome, cropped, cut-off, patterned background""" | |
| refiner_prompt = """ultra-high-definition, photorealistic, 8k uhd, high-quality, | |
| ultra sharp detail""" |