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

OpenArt AI
10 Apr 202405:07

TLDRThis tutorial video guides viewers on how to train a custom fine-tuned model with OpenAI for AI image generation. The video covers four types of models: style, character, face, and object. It emphasizes the importance of quantity, consistency, and variety in the training images. For the style model, the presenter uploads 70 images and trains the model, encountering an issue with capturing the desired black and white theme. To address this, they suggest either uploading more images or adjusting the prompt during generation. The video also demonstrates generating illustrations with the trained model, showing various scenarios like people arguing, co-working, and walking with a folder. Additionally, it discusses creating a character model, highlighting the need for a variety of poses and angles to build a three-dimensional understanding of the character. The presenter shares their process of creating an anime character named Aane, showcasing how to dress her in different settings. The video concludes with tips on generating consistent characters from scratch or using existing images to create a functional model.

Takeaways

  • 🎨 **Custom Model Training**: OpenAI offers the ability to fine-tune four types of models: style, character, face, and object.
  • 📚 **Learning Resources**: For beginners, a model training book by brilliant authors, including the co-founder of OpenArt, is highly recommended.
  • 🖌️ **Style Model Introduction**: The process starts with creating an illustration style that can be used to generate images for various purposes.
  • 📈 **Quantity Matters**: When training a style model, uploading as many as 128 images is advised to ensure the model learns effectively.
  • 🔍 **Consistency is Key**: Uploaded images should have a common theme to avoid confusing the model.
  • 🌟 **Variety Wins**: Including a variety of subjects (people, animals, objects) in training images helps the model understand the style across different contexts.
  • ⏱️ **Training Time**: Training a model takes a few minutes, during which you can do other tasks.
  • 🖇️ **Theme Adjustment**: If the model doesn't capture the desired theme, more images or specific prompts can be used during generation.
  • 🧍‍♀️ **Character Model Tips**: For character models, having a variety of poses and angles is crucial for capturing features from all sides.
  • 🌐 **Consistency in Characters**: Ensure the character looks consistent across different images for better model training results.
  • 📝 **Content Creation**: Once the model is trained, you can generate images in the learned style or with the created character for various uses like articles, presentations, or schoolwork.

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 with OpenAI are style, character, face, and object.

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

    -When training a style model for the first time, it is recommended to follow a model training book by brilliant authors, including the co-founder of OpenArt, to get a better understanding of the process.

  • 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 4 to 128 images, 2) Consistency - ensure a common theme in the images, and 3) Variety - include different subjects like people, animals, and objects to teach the model the style across various subjects.

  • How does the model training process work once you have uploaded the images?

    -After uploading the images and selecting the style model type, the model begins training. This process usually takes a few minutes, during which you can do other tasks. Once completed, the model is ready for use.

  • What is a common issue encountered with the style model and how can it be resolved?

    -A common issue is the model not capturing the intended common theme of the images. This can be resolved by uploading more images that represent the theme or by adding details about the desired theme in the prompt during generation.

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

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

  • How can you ensure that the character model looks consistent during the training process?

    -To ensure consistency, upload images where the character appears the same across different poses and angles. If generating characters, use tools or techniques that help in creating consistent character representations.

  • What are some examples of scenarios where the generated style model can be used?

    -The generated style model can be used to create illustrations for embedding in articles, presentations, or to make work or school materials more engaging and fun.

  • How can you prompt the model to generate specific themes or styles during the image generation process?

    -You can prompt the model by adding descriptive text about the theme or style you want during the image generation process, guiding the model towards the desired outcome.

  • What is the name of the anime character created in the tutorial?

    -The name of the anime character created in the tutorial is Aane.

  • What are the steps to create a character model from scratch using OpenArt?

    -To create a character model from scratch, you can either upload images of a character you've drawn or rendered elsewhere to make it a functional model, or follow a specific tutorial that provides tips on generating a consistent character from the ground up using OpenArt.

  • What is the recommended number of images to upload when training a character model?

    -It is recommended to upload at least eight pictures of the character to train the model effectively, ensuring the character is depicted in various poses and angles.

Outlines

00:00

🎨 Custom Illustration Style Model Training with OpenAI

This paragraph introduces the process of training a custom style model with OpenAI. It covers the four types of models available for fine-tuning: style, character, face, and object. The focus is on the style model, which allows users to create their own illustration style. The paragraph provides three key tips for successful training: ensuring a sufficient quantity of images (between 4 to 128), maintaining consistency across images to avoid model confusion, and providing variety in the subjects (people, animals, objects) to inform the model about the style's appearance across different elements. The speaker shares their personal experience with training a model to capture a specific black and white style, and discusses strategies for addressing common issues like the model not fully capturing the intended theme. The paragraph concludes with examples of generated illustrations in the desired style, showcasing the model's capabilities.

05:02

👥 Generating a Consistent Character Model

The second paragraph emphasizes the importance of training a character model with a variety of poses and angles to capture the character's features from all perspectives, thus enabling the model to build a three-dimensional understanding of the character. The speaker introduces an anime character named Aane, which can be placed in various clothing or settings. The process involves selecting the character model type and uploading multiple images of the character to ensure consistency. The paragraph also mentions the option to upload images of a character created outside of OpenAI to train the model or to generate a character from scratch using OpenAI, with a reference to another video providing tips for the latter approach.

Mindmap

Keywords

💡Fine-tuned model

A fine-tuned model refers to a machine learning model that has been trained on a specific task or dataset after being pre-trained on a larger, more general dataset. In the context of the video, it means customizing a pre-existing AI model to generate images in a particular style or theme. The video emphasizes training a model with a specific illustration style to generate images for articles or presentations.

💡Style model

A style model is a type of AI model that is trained to recognize and replicate a specific artistic style. It is one of the four types of models mentioned in the video that can be fine-tuned. The video demonstrates how to create a custom illustration style by training a style model, which can then be used to generate images in that style.

💡Quantity

In the context of training an AI model, quantity refers to the number of images used to train the model. The video advises uploading a maximum number of images (up to 128) to ensure the model has enough data to learn from. This is crucial for the model to understand the desired style or theme accurately.

💡Consistency

Consistency in the context of AI model training means that the images uploaded should have a common theme or style. This helps the model to learn a specific style without getting confused by varied or unrelated content. The video stresses the importance of maintaining a consistent theme across the training images.

💡Variety

Variety, when training an AI model, is about including different subjects in the training images to show the model how the desired style should look across various elements. The video mentions including people, animals, and objects to teach the model about the style's appearance with different subjects.

💡Training images

Training images are the specific set of images used to train an AI model. They are crucial for the model to learn the desired style or characteristics. The video provides an example of uploading 70 images to train a style model and emphasizes the importance of these images in capturing the intended style.

💡Character model

A character model is an AI model that is trained to generate images of a specific character from different angles and poses. This type of model is important for creating characters that are recognizable and consistent. The video discusses creating a character named Aane and training a character model to generate images of her in various settings.

💡Poses and angles

Poses and angles are critical for character models as they allow the AI to learn the character's features from all perspectives, building a three-dimensional understanding of the character. The video highlights the importance of having a variety of poses and angles in the training images for character models.

💡Three-dimensional knowledge

Three-dimensional knowledge in the context of AI refers to the model's ability to understand and generate images that take into account the depth and spatial relationships of objects or characters. This is particularly important for character models, as it allows the model to generate more realistic and varied depictions of the character.

💡Prompting

Prompting in the context of AI image generation is the process of providing the model with specific instructions or descriptions to guide the generation of an image. The video discusses how to prompt the model to generate images that are closer to the desired style or theme, especially when the initial training results are not fully capturing the intended style.

💡Illustration style

An illustration style refers to a distinctive visual art style used in creating images, often for storytelling or decorative purposes. In the video, the focus is on training a model to replicate a specific illustration style, which can then be used to generate images that match this style for various applications.

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 must consider quantity, consistency, and variety in the training images.

A common theme should be present in the uploaded images to avoid model confusion.

Different subjects like people, animals, and objects should be included in the training images for a diverse style representation.

The presenter demonstrates training a style model by uploading 70 images and selecting the 'style' model type.

A common issue with the style model is not capturing the intended theme; more images or adjusted prompts can resolve this.

The model training process takes a few minutes, during which the user can multitask.

Generated examples include a man typing on a laptop, two people arguing, and a man walking with a folder.

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

The presenter creates an anime character named 'Aane' and demonstrates how to apply her in different settings.

For generating consistent characters, OpenArt can be used, and additional tips are provided in another video.

The importance of having a consistent look for the character in the uploaded images is emphasized.

If struggling with generating consistent characters, there are resources available to assist with this process.

The video concludes with a demonstration of 'Aane' powered by OpenArt, showcasing the character's versatility.

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