OpenArt Tutorial: Train Your Own Model (AI Image Generation 2024)

OpenArt AI
10 Apr 202405:07

TLDRIn this tutorial, viewers are guided through the process of training a custom fine-tuned model with OpenAI for AI image generation. The video covers four types of models: style, character, face, and object. For beginners, a recommended model training book is mentioned, authored by the co-founder of OpenArt. The focus is on creating an illustration style model, which requires a balance of quantity, consistency, and variety in the uploaded images. The training process is demonstrated, and common issues such as capturing the intended theme are discussed. Tips for refining the model's output are provided, including adjusting the prompt to better reflect the desired style. Additionally, the video touches on character model generation, emphasizing the importance of diverse poses and angles to build a comprehensive 3D understanding of the character. The presenter shares their experience creating an anime character named Aane, showcasing how to apply the model to various clothing and settings. The video concludes with resources for generating consistent characters and offers further guidance for those starting from scratch.

Takeaways

  • 🎨 **Style Model Introduction**: The video begins with an introduction to the style model, which is used to create a custom illustration style for generating images.
  • 📈 **Image Quantity**: It's recommended to upload between 4 to 128 images to train the model, maximizing the number for better results.
  • 🔍 **Consistency is Key**: The uploaded images should have a common theme to avoid confusing the model.
  • 🌟 **Variety Matters**: Including a variety of subjects like people, animals, and objects helps the model learn the style across different subjects.
  • ⏱️ **Training Time**: Training the model takes a few minutes, during which you can do other tasks.
  • 🖌️ **Style Capture Issue**: If the model doesn't capture the desired theme, upload more images or adjust the prompt during generation.
  • 👥 **Character Model Tips**: For character models, having a variety of poses and angles is crucial for the model to understand the character from all sides.
  • 🧐 **Three-Dimensional Knowledge**: The character model should build a 3D understanding of the character to enable consistent generation across different settings.
  • 🖼️ **Consistent Character Generation**: Ensure the character looks consistent across the images; if struggling, use OpenArt for assistance.
  • 📚 **Additional Resources**: The video suggests a book for further learning and other videos for tips on generating consistent characters from scratch.
  • 🌈 **Color Palette Inclusion**: When generating, you can also include a specific color palette to achieve a desired tone or theme.

Q & A

  • What are the four types of models that can be fine-tuned with OpenAI?

    -The four types of models that can be fine-tuned are style, character, face, and object.

  • What is the recommended approach when training a style model for the first time?

    -For beginners, it is recommended to follow a model training book, which is authored by brilliant authors, including the co-founder of OpenArt.

  • What are the three key tips to keep in mind when uploading images for training a style model?

    -The three key tips are: 1) Quantity - upload between four to 128 images; 2) Consistency - maintain a common theme across the images; and 3) Variety - include different subjects such as people, animals, and objects to teach the model about the style.

  • How can one improve the model's understanding of the desired style if it doesn't capture the theme correctly?

    -To improve the model's understanding, one can upload more images that better represent the desired theme or include additional details about the theme in the prompt when generating images.

  • What is the importance of having a variety of poses and angles when training a character model?

    -A variety of poses and angles is crucial as it helps the model to build a three-dimensional knowledge of the character, capturing features from all perspectives.

  • How can one ensure consistency in the character's appearance when training a character model?

    -Ensuring consistency involves uploading images where the character looks the same across different poses and angles. If struggling with generating consistent characters, one can refer to specific tutorials on how to achieve this.

  • What is the process of creating a character model from scratch?

    -To create a character model from scratch, one can either upload existing images of a character if created elsewhere or follow specific tutorials that provide tips on generating a consistent character using OpenArt.

  • What is the common issue encountered with the style model, especially regarding the images uploaded?

    -A common issue is that the model may not completely capture the common theme intended by the user, such as a specific color scheme or style element.

  • How many images are typically needed to start training a style model?

    -A minimum of four images is required, and one can upload up to 128 images for training a style model.

  • What are some examples of generated illustrations that the video creator liked?

    -Some examples include a man tapping on a laptop, two people arguing, two people co-working, a girl holding a coffee, and a man walking with a folder.

  • What is the name of the anime character created by the video creator?

    -The anime character created by the video creator is named Aane.

  • What is the recommended action when the model has started training?

    -It is recommended to do something else while the model is training, as it can take a few minutes. Once back, the model should be trained and ready to use.

Outlines

00:00

🎨 Custom Illustration Style Model Training with OpenAI

This paragraph introduces the concept of training a custom fine-tuned model with OpenAI, focusing on the style model. The video demonstrates how to create a personalized illustration style that can be used to generate images for various purposes such as articles or presentations. Key points include the importance of quantity (uploading 4 to 128 images), consistency (maintaining a common theme across images), and variety (including different subjects like people, animals, and objects). The process involves uploading images, selecting the style model, and training it. The speaker also discusses common issues like capturing the intended theme and suggests solutions like uploading more images or adjusting the prompt for better results. The outcome is a model that can generate illustrations in a specific style, as demonstrated with various examples.

05:02

👥 Generating a Consistent Character Model

The second paragraph emphasizes the importance of creating a character model with a diverse range of poses and angles to enable the model to understand the character from all perspectives, thus building a three-dimensional knowledge of the character. The speaker introduces an anime character named 'Aane' and explains how the model can be used to place her in different clothing or settings. The process involves selecting the character model type and uploading multiple images of the character to ensure consistency. The paragraph also suggests looking at additional resources for generating consistent characters, whether by using existing images or creating them from scratch.

Mindmap

Keywords

💡Fine-tuned model

A fine-tuned model refers to a machine learning model that has been trained on a specific task after being pre-trained on a larger, more general dataset. In the context of the video, the term is used to describe the process of customizing a model for AI image generation, such as style, character, face, or object models, to generate images that fit a particular style or represent specific subjects.

💡Illustration style

An illustration style is a distinctive visual art technique or approach that characterizes an artist's work. In the video, the speaker discusses creating a custom illustration style by training a model to generate images that match a preferred visual aesthetic. This is exemplified by the speaker's attempt to train a model to produce black and white illustrations.

💡Quantity of images

The term 'quantity of images' refers to the number of images used to train a machine learning model. The video emphasizes the importance of uploading a sufficient number of images, ranging from four to 128, to ensure the model learns effectively. The speaker mentions uploading 70 images to train their model, highlighting the significance of this step.

💡Consistency

Consistency in the context of training a model means that the uploaded images should share a common theme or style. This helps the model to understand and replicate the desired style without confusion. The video script mentions the need for consistency to prevent the model from being misled by a diverse range of unrelated images.

💡Variety

Variety, in the context of the video, refers to the range of different subjects, poses, and angles included in the training images. The speaker stresses the importance of having a variety of images to teach the model how the desired style should look across different subjects, such as people, animals, and objects. This contributes to a more versatile and adaptable model.

💡Model training

Model training is the process of teaching a machine learning model to perform a specific task by feeding it data (in this case, images) and adjusting its parameters based on the results. The video provides an overview of how to train a custom model using OpenArt, emphasizing the steps and considerations involved in the process.

💡Character model

A character model is a type of AI image generation model that is specifically trained to generate images of characters, such as people or animated figures. The video discusses the importance of capturing a character from various poses and angles to build a three-dimensional understanding of the character's features. This is demonstrated by the creation of an anime character named 'Aane'.

💡Three-dimensional knowledge

Three-dimensional knowledge, as used in the video, refers to the model's ability to understand and generate images that take into account the depth and spatial relationships of subjects within the images. This is particularly important for character models, as it allows the model to generate characters that look coherent from multiple viewpoints.

💡Anime character

An anime character is a character from Japanese animation, typically characterized by distinct visual features such as large eyes and expressive emotions. In the video, the speaker creates an anime character named 'Aane' and discusses how the model can be used to place this character in various clothing or settings, showcasing the flexibility of the model.

💡OpenArt

OpenArt is mentioned in the video as a platform or tool used for generating and training AI models for image creation. The speaker uses OpenArt to generate consistent characters and to train their model to replicate a specific illustration style. It is implied that OpenArt provides the functionality needed for custom AI image generation tasks.

💡Prompting

Prompting, in the context of AI image generation, involves providing the model with a description or set of instructions to guide the generation process. The video script discusses how the speaker adjusts the prompt to better capture the desired theme, such as specifying 'black and white' to achieve the look they want from the model.

Highlights

The video provides a tutorial on training a custom fine-tuned model with OpenAI for AI image generation.

Four types of models can be fine-tuned: style, character, face, and object.

For beginners, a recommended model training book is available, co-authored by the co-founder of OpenArt.

The style model is introduced first, focusing on creating a unique illustration style.

To train the style model, one needs to upload 4 to 128 images with a common theme for consistency.

Variety is essential, including different subjects like people, animals, and objects in the training images.

After training, the model can generate illustrations in the learned style to be used in articles or presentations.

The presenter encountered an issue with the model not capturing the intended black and white theme.

To address this, more images can be uploaded or the desired theme can be included in the prompt during generation.

The character model requires a variety of poses and angles to capture features from all sides.

The model builds a three-dimensional knowledge of the character for more realistic and versatile outputs.

An anime character named Aane is created and demonstrated, showing how she can be placed in various clothing or settings.

Uploading only eight pictures of the character Aane resulted in good training outcomes.

Consistency in the character's appearance across the uploaded images is crucial for effective model training.

If struggling with generating consistent characters, there is a video on how to do it with OpenArt.

The video also covers how to create a functional model from characters drawn or rendered elsewhere.

Another video provides tips on generating a consistent character from scratch.

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