OpenArt Tutorial: Train Your Own Model (AI Image Generation 2024)
TLDRIn this tutorial, the video demonstrates how to train a custom fine-tuned model with OpenAI, focusing on four types of models: style, character, face, and object. The presenter recommends a training book by brilliant authors, including the co-founder of OpenArt, for beginners. The style model is introduced first, with tips on quantity, consistency, and variety of images for training. The presenter uploads 70 images and starts training, encountering an issue with capturing the black and white theme. They suggest adding more images or adjusting the prompt for better results. The video also covers character model training, emphasizing the importance of variety in poses and angles to build a 3D knowledge of the character. The presenter creates an anime character named Aane and shows how to generate her in different clothing and settings. They provide guidance on creating a consistent character or using existing drawings for a functional model.
Takeaways
- 🎨 **Custom Model Training**: OpenAI allows you to fine-tune four types of models - style, character, face, and object.
- 📚 **Recommended Reading**: For beginners, a model training book by brilliant authors, including the co-founder of OpenArt, is highly recommended.
- 🖌️ **Style Model Introduction**: You can create your own illustration style by training a style model with a consistent theme across multiple images.
- 📈 **Quantity and Quality**: When training a model, upload between 4 to 128 images ensuring consistency and variety to avoid model confusion.
- 🔍 **Model Training Process**: After uploading images, select the 'style' model type for training, which may take a few minutes.
- 🖋️ **Addressing Training Issues**: If the model doesn't capture the desired theme, upload more images or adjust the prompt during generation.
- 👥 **Character Model Tips**: For character models, include a variety of poses and angles to help the model build a 3D knowledge of the character.
- 🧍♀️ **Consistent Character Design**: Ensure the character appears consistent across images; generated images can also be used if drawing is challenging.
- 🤖 **OpenArt Assistance**: If you struggle with generating consistent characters, OpenArt provides resources to help achieve this.
- 🖼️ **Image Generation Examples**: The script provides examples of generated images in the chosen style, including people arguing, co-working, and walking with a folder.
- 🌟 **Creative Prompting**: Experiment with different prompts to refine the model's output, getting closer to the desired style and 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 with OpenAI are style, character, face, and object.
What is the first tip for training a style model?
-The first tip for training a style model is to focus on quantity, uploading between four to 128 images.
Why is consistency important when uploading images for a style model?
-Consistency is important to ensure there's a common theme across the images, preventing the model from being confused.
What does 'variety wins' mean in the context of training a style model?
-'Variety wins' means that the training images should include different subjects such as people, animals, and objects to teach the model how the style should look with various subjects.
What happens if the model doesn't capture the intended theme during training?
-If the model doesn't capture the intended theme, you can either upload more images that better represent the theme or adjust the prompt to include more details about the desired theme during generation.
How long does it typically take for a model to finish training?
-The training time can vary, but it usually takes a few minutes. It's recommended to do something else while the model trains and then return to check the results.
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 build a three-dimensional knowledge around the character, capturing features from all perspectives.
How many pictures are needed to start training a character model?
-While there's no specific number, the script suggests starting with eight pictures of the character for training.
What should be done if you struggle to generate consistent characters?
-If you struggle with generating consistent characters, you can refer to other resources or tutorials that provide tips on achieving consistency, such as a video on how to do it with OpenArt.
Can you use images of a character created outside of OpenArt for training a model?
-Yes, you can upload images of a character that you've created or rendered elsewhere to make it a functional model.
What are some common issues encountered when training a style model with images?
-A common issue is the model not fully capturing the common theme intended by the user, such as a specific color scheme or style element.
How can you enhance the results of a style model that didn't capture the intended theme?
-You can enhance the results by uploading more images that closely match the desired theme or by providing additional descriptive prompts during the generation process.
Outlines
🎨 Training a Custom Style Model with OpenAI
This paragraph introduces the process of training a custom style model using OpenAI. It discusses the four types of models available for fine-tuning: style, character, face, and object. The speaker recommends a training book authored by brilliant authors, including the co-founder of OpenAI. The focus then shifts to the style model, emphasizing the creation of a unique illustration style. Tips for training include ensuring a sufficient quantity of images (between 4 to 128), maintaining consistency across images to avoid confusing the model, and providing variety in the subjects (people, animals, objects) to teach the model about the style's appearance across different elements. The speaker demonstrates uploading 70 images to train the model and addresses a common issue with the model not capturing the intended black and white theme, suggesting solutions like uploading more images or adjusting the prompt. The paragraph concludes with examples of generated illustrations in the trained style, showcasing various scenarios like people arguing, co-working, and a lightbulb moment.
👥 Developing a Character Model with Diverse Poses
The second paragraph emphasizes the importance of training a character model with a variety of poses and angles to enable the model to build a three-dimensional understanding of the character. The speaker introduces 'Aane,' an anime character they created, and explains how the model can be used to place the character in different clothing or settings. To train the character model, the speaker chooses the 'character' option and uploads eight pictures of Aane, noting that consistency in the character's appearance is key for effective training. The paragraph also mentions that if one has a character created outside of OpenAI, those images can be uploaded for training. Additionally, there is a reference to another video that provides tips on generating a consistent character from scratch.
Mindmap
Keywords
💡Custom Fine-Tuned Model
💡Style Model
💡Consistency
💡Variety
💡Training Images
💡Model Training Book
💡Character Model
💡Three-Dimensional Knowledge
💡Anime Character
💡OpenArt
💡Prompting
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.
A recommended model training book is mentioned, featuring contributions from the co-founder of OpenArt.
The style model is introduced first, with a focus on creating a unique illustration style.
Three tips for training the model are provided: quantity, consistency, and variety.
The importance of uploading images with a common theme to avoid model confusion is emphasized.
The model should be trained with a variety of subjects to understand different styles.
An example of training a style model with 70 images is demonstrated.
The model may require more images or specific prompts to capture the desired theme accurately.
Generated images may need adjustments based on the results obtained from initial attempts.
The video showcases examples of generated images, including people arguing, co-working, and walking with a folder.
A character model is highlighted, emphasizing the need for a variety of poses and angles.
The character model is demonstrated with an anime character named 'Aane', showing how to change clothing and settings.
Eight pictures of 'Aane' are used to train the character model for consistency.
The video provides tips on generating consistent characters, even if created outside of OpenArt.
An additional video resource is mentioned for generating consistent characters from scratch.
The final generated images showcase a range of scenarios with the character model, including a cozy, work-themed palette.
The video concludes with a light bulb idea image, demonstrating the model's ability to capture luminance and themes.