"Given an input image of a person, the goal to generate a new image where the p

"Given an input image of a person, the goal to generate a new image where the person's body or clothing changed, while ensuring that the original face remains intact. The model should utilize the Stable Diffusion img2img technique, combining time-based diffusion with an image generator powered by deep learning.

The model should be trained on a dataset comprising various images of people with different body poses and clothing styles. By separating the image into layers and isolating the face, the model can focus on modifying the body or clothing layers while preserving the original face.

To achieve this, the model should leverage a generative neural network, such as a convolutional neural network (), trained through supervised or unsupervised learning methods. It should use a loss function, such as content loss or perceptual loss, to guide the generation process and ensure the generated images are faithful to the target image.

Optimization algorithms like stochastic gradient descent can be employed to fine-tune the generator model's parameters and minimize the loss function during the image generation process.

The ultimate objective to generate realistic and visually appealing images where the person's body or clothing has changed, but the original face remains intact."

I hope this prompt helps you in describing your requirements for generating an image with the specified attributes.

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프롬프트

"Given an input image of a person , the goal to generate a new image where the person's body or clothing changed , while ensuring that the original face remains intact . The model should utilize the Stable Diffusion img2img technique , combining time-based diffusion with an image generator powered by deep learning . The model should be trained on a dataset comprising various images of people with different body poses and clothing styles . By separating the image into layers and isolating the face , the model can focus on modifying the body or clothing layers while preserving the original face . To achieve this , the model should leverage a generative neural network , such as a convolutional neural network () , trained through supervised or unsupervised learning methods . It should use a loss function , such as content loss or perceptual loss , to guide the generation process and ensure the generated images are faithful to the target image . Optimization algorithms like stochastic gradient descent can be employed to fine-tune the generator model's parameters and minimize the loss function during the image generation process . The ultimate objective to generate realistic and visually appealing images where the person's body or clothing has changed , but the original face remains intact . " I hope this prompt helps you in describing your requirements for generating an image with the specified attributes .

사이즈

768X768

날짜

Dec 10, 2023

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기본

유형

upscale

Checkpoint & LoRA

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