Welcome to the fascinating world of text-to-image generation! In today’s blog, we’re going to explore how to use the CosmicMan model, a state-of-the-art text-to-image foundation model specifically designed to create stunning human images. Let’s dive into the steps required for setup and execution.

What is CosmicMan?

CosmicMan is a cutting-edge model that allows you to generate high-fidelity images of humans based on textual descriptions. Developed with the principles of stability and detail, it leverages the power of other models like stabilityai/stable-diffusion-xl-base-1.0 to achieve remarkable results.

Setting Up CosmicMan

To start your journey with CosmicMan, you’ll first need to set up your environment. Below are the requirements and installation steps:

Requirements

• Python 3.10
• PyTorch, torchvision, torchaudio
• Several additional libraries for effective operation

Installation Steps

conda create -n cosmicman python=3.10

source activate cosmicman

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

pip install accelerate diffusers datasets transformers botocore invisible-watermark bitsandbytes gradio==3.48.0

Quick Start with Gradio

Once you’ve installed the necessary dependencies, running a demo is simple! Execute the following command:

python demo_sdxl.py

Now, you can access the model via your server’s IP address.

How to Run Inference

Now, let’s look at how to generate images using CosmicMan. Think of this process like a chef preparing a dish using a recipe. Here’s your recipe for generating images:

1. Import Necessary Libraries

import torch
from diffusers import StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline, UNet2DConditionModel, EulerDiscreteScheduler
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file

Just like a chef gathers ingredients, you start by gathering your necessary tools (libraries).

2. Load Your Model

# Specify your model paths
base_path = "stabilityai/stable-diffusion-xl-base-1.0"
refiner_path = "stabilityai/stable-diffusion-xl-refiner-1.0"
unet_path = "cosmicman/CosmicMan-SDXL"

# Load models
unet = UNet2DConditionModel.from_pretrained(unet_path, torch_dtype=torch.float16)
pipe = StableDiffusionXLPipeline.from_pretrained(base_path, unet=unet, torch_dtype=torch.float16, variant(fp16), use_safetensors=True).to(cuda)
pipe.scheduler = EulerDiscreteScheduler.from_pretrained(base_path, subfolder=scheduler, torch_dtype=torch.float16)
refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained(refiner_path,torch_dtype=torch.float16, variant(fp16), use_safetensors=True).to(cuda)

In this step, you’re mixing your ingredients. Loading the model is like measuring out flour and sugar before baking a cake!

3. Generate Your Image

# Define prompts and generate
positive_prompt = "A fit Caucasian elderly woman, her wavy white hair above shoulders, wears a pink floral cotton long-sleeve shirt against a natural landscape."
negative_prompt = ""

# Generate the image
image = pipe(positive_prompt, num_inference_steps=30, guidance_scale=7.5, height=1024, width=1024, negative_prompt=negative_prompt, output_type="latent").images[0]
image = refiner(positive_prompt, negative_prompt=negative_prompt, image=image[None, :]).images[0]
image.save("output.png")

Deciding on your prompts is the thrilling part where you creatively express what you want your image to look like! Finally, saving the image is like pulling your delicious cake out of the oven.

Troubleshooting Tips

Running into issues? Here are some troubleshooting ideas:

• Ensure all dependencies are installed correctly and match the specified versions.
• Double-check your CUDA installation if you’re using GPU acceleration.
• If the output is not as expected, try tweaking the prompts or the number of inference steps.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.