【Stable Diffusion】画像から画像を作成するimg2imgの使い方について解説

AIジェネ【AIイラスト生成の情報発信】
15 Jul 202307:21

TLDRExplore the 'img2img' feature of Stable Diffusion to create images with desired poses and features by using a reference image. This method allows for quick generation of anime-style illustrations from real-life images. Adjust the 'denoising strength' for similarity to the reference, and 'resize and fill' for different image sizes. The tutorial provides insights on generating high-quality images while maintaining the essence of the original, offering a powerful tool for artists and creators.

Takeaways

  • 🎨 Use 'img2img' to generate images with desired poses and features from an existing image.
  • 🌟 Switch from 'txt2img' to 'img2img' in Stable Diffusion Web UI for image-to-image generation.
  • 📸 Upload a reference image to capture specific features such as poses and background.
  • 🖼️ Set the image size to match the uploaded reference for better results.
  • 🌈 Include a detailed prompt with desired features and a negative prompt to avoid unwanted image qualities.
  • 🔄 Adjust 'denoising strength' to strengthen or weaken the reference image's characteristics.
  • 📏 Use 'resize and fill' in 'resize mode' for generating images with different sizes from the reference image.
  • 🔎 Compare different 'resize mode' options for optimal image generation outcomes.
  • 🏞️ 'img2img' is suitable for inheriting background and other features along with poses.
  • 🎭 For imitating poses only, consider using 'openpose' instead of 'img2img'.

Q & A

  • What is the main purpose of using 'img2img' in Stable Diffusion?

    -The main purpose of using 'img2img' in Stable Diffusion is to generate images from an existing image, preserving desired features such as poses and background characteristics.

  • How does the 'txt2img' method differ from 'img2img'?

    -'txt2img' generates images based on textual descriptions, while 'img2img' generates images from an uploaded reference image, maintaining specific features of the original image.

  • What should you do first when using 'img2img' in Stable Diffusion?

    -When using 'img2img', the first step is to switch from the default 'txt2img' mode by clicking 'img2img' in the upper left corner of the Stable Diffusion web UI.

  • How do you upload the reference image for 'img2img'?

    -After switching to 'img2img' mode, scroll down and click the 'img2img' tab to upload the reference image you want to use.

  • What is the significance of the 'resize to' option in 'img2img'?

    -The 'resize to' option allows you to set the image size for the generated image. It is recommended to match the size of the uploaded reference image for better results.

  • Why is it important to include a prompt when using 'img2img'?

    -Including a prompt is crucial because it guides the generation process. Without a prompt, the generated image may be of poor quality.

  • How does the 'denoising strength' setting affect the generated image?

    -The 'denoising strength' setting determines the influence of the reference image on the generated image. A lower number strengthens the reference image's features, while a higher number weakens it.

  • What is the recommended 'denoising strength' setting for generating a completely different image?

    -For generating a completely different image, a 'denoising strength' setting of about 0.6 is recommended.

  • How can you adjust the size of the generated image with 'resize mode'?

    -You can adjust the size of the generated image by selecting 'resize and fill' in 'resize mode'. This allows for generating an image with a different size while maintaining the reference image's features.

  • What are the four different 'resize mode' options in 'img2img'?

    -The four 'resize mode' options are 'just resize', 'crop and resize', 'resize and fill', and 'latent upscale'.

  • What is the difference between 'openpose' and 'img2img'?

    -'openpose' is used to imitate only poses, while 'img2img' generates images with similar poses and other features like the background.

Outlines

00:00

🎨 Understanding 'img2img' for Enhanced Image Generation

This paragraph introduces the concept of 'img2img' for image generation, emphasizing its utility over 'txt2img' when specific poses and features are desired. It explains that 'img2img' allows users to generate images based on an existing image, which can be particularly useful for maintaining desired attributes such as pose and background. The process of using 'img2img' is detailed, starting from uploading the reference image on the 'stable diffusion web ui' platform to adjusting the image size and entering the appropriate prompts for quality and desired features. The importance of the 'denoising strength' parameter is highlighted, illustrating its role in influencing how closely the generated image resembles the reference image. Additionally, the paragraph discusses the option to generate images with different sizes using the 'resize and fill' mode, and the impact of the 'scale' parameter on the clarity of details such as eyes.

05:04

🔄 Exploring Different Resizing Techniques for Image Generation

The second paragraph delves into the various resizing techniques available for image generation, comparing 'just resize', 'crop and resize', 'resize and fill', and 'latent upscale'. It explains that 'just resize' may not always yield the correct image size, while 'crop and resize' maintains the aspect ratio of the reference image. 'Resize and fill' is recommended for generating images with additional content outside the reference image's range. 'Latent upscale' is noted to have similar results to 'just resize' but with horizontal stretching. The paragraph concludes with a summary of how 'img2img' can be used to generate images with similar character and background features by adjusting the 'denoising strength'. It also mentions 'openpose' for those looking to imitate poses specifically and encourages viewers to explore AI generation further through provided resources. The paragraph ends with a call to action for viewers to subscribe to the channel for more content.

Mindmap

Keywords

💡Stable Diffusion

Stable Diffusion is an AI model used for generating images based on textual descriptions or other images. In the context of the video, it is the primary tool introduced to demonstrate the process of creating images with similar features from an existing image, particularly focusing on the 'img2img' function. It allows users to maintain certain aspects of a reference image while generating a new, unique image.

💡img2img

The 'img2img' function refers to the method of generating new images from existing ones. This feature is highlighted in the video as a way to quickly generate images that retain specific poses, features, or backgrounds of the uploaded reference image. It is an essential part of the Stable Diffusion model that enables users to create images with desired characteristics by using an example image as a guide.

💡Pose

In the context of the video, 'pose' refers to the specific arrangement of a figure or object within an image. It is a crucial element when using the 'img2img' function because it allows the user to preserve the original posture or stance of the subject in the generated image. The video emphasizes the importance of maintaining the desired pose from the reference image when creating a new image.

💡Features

Features in the video refer to the distinct characteristics or attributes of the subjects and objects within an image. These can include facial expressions, clothing, colors, and other visual elements that define the look and style of the image. The 'img2img' function is used to ensure that these features are replicated or emphasized in the new image generated by the Stable Diffusion model.

💡Resize to

'Resize to' is an option within the Stable Diffusion web UI that allows users to adjust the size of the generated image in relation to the uploaded reference image. This feature is important for maintaining the proportions and dimensions of the original image, ensuring that the generated image matches the desired size without distortion.

💡Prompt

In the context of the video, a 'prompt' is a textual description that guides the Stable Diffusion model in generating an image. It includes specific instructions or keywords that the AI uses to create an image with the desired qualities, such as 'masterpiece', 'best quality', or 'detailed eyes'. The prompt is essential for directing the AI to produce high-quality images that align with the user's vision.

💡Negative prompt

A 'negative prompt' is a set of instructions used in conjunction with the primary prompt to specify what aspects of the generated image should be avoided or minimized. It helps refine the output by telling the AI what not to include, such as 'low quality' or 'lowres'. This tool is crucial for achieving a more precise and desired outcome in the generated image.

💡Denoising strength

The 'denoising strength' is a parameter that influences the degree to which the Stable Diffusion model adheres to the features of the reference image. A lower value strengthens the influence of the reference image, resulting in a closer match, while a higher value allows for more deviation, creating a more distinct image. This setting is important for balancing the similarity between the generated image and the reference image.

💡Scale

The 'scale' parameter in the video relates to the enlargement of specific elements within the generated image, such as the eyes or other details. By setting the scale to a value higher than 1, users can ensure that these features are clearer and more defined in the final image. This is particularly useful when the generated image has blurred or distorted details that need to be corrected for better visual quality.

💡Resize mode

The 'resize mode' offers different options for adjusting the size of the generated image in relation to the reference image. These options include 'just resize', 'crop and resize', 'resize and fill', and 'latent upscale'. Each mode has a unique way of altering the image size while maintaining certain aspects of the original image, allowing users to choose the best fit for their desired outcome.

💡Openpose

In the video, 'openpose' is mentioned as an alternative tool for generating images that focus solely on imitating the pose of a reference image. Unlike 'img2img', which retains other features such as the background, 'openpose' is used when the user wants to generate an image with a similar pose but may not necessarily want to carry over other aspects of the original image.

Highlights

画像から画像を生成する「img2img」の概念を紹介。

Stable Diffusion Web UIで「txt2img」から「img2img」に切り替える方法を説明。

ポーズや背景などの特徴を維持するために参照画像をアップロードする重要性。

実写画像からアニメスタイルのイラストを生成するデモンストレーション。

エラーを避けるために正しく画像サイズを設定する方法。

画像の結果を向上させるためにプロンプトに品質呪文を使用する重要性。

より良い画像生成のための入力プロンプトとネガティブプロンプトの例。

参照画像と生成画像を比較する生成結果。

「デノイジング強度」設定が画像の特性に与える影響について説明。

「リサイズモード」を調整することで異なるサイズの画像を生成するヒント。

画像生成におけるさまざまな「リサイズモード」オプションとその影響についての議論。

サイズ調整が必要な画像に「リサイズして埋める」を使用する利点。

「潜在アップスケール」とその他のリサイズオプションとの比較についての紹介。

特定のキャラクターの特徴を再現するために「img2img」を使用する方法の要約。

AI生成に関するさらなる洞察を得るためにチャンネル登録を促す。

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