ever wonder how top AI content creators flood their social media with stunning images? The secret is batch generation, and today I'm pulling back the curtain. What if I told you there's a way to create dozens of high-quality, diverse images of your AI digital model in just minutes? In this tutorial, I'll show you how to supercharge your workflow using batch generation techniques in Comfy UI. Plus, I'll reveal my secret weapon, a custom node I've personally developed that will take your AI model production to the next level. Get ready to leave your competitors in the dust and flood your social media with stunning, professional-grade content. Let's dive in and revolutionize your AI image creation process. Let's explore how to install the Save Florence two bulk prompt, a simple yet powerful custom node that will save you considerable time and keep you ahead of the competition. Before we begin the installation process, you can find detailed information about this custom node in the README section. For those concerned about safety, the code is open for inspection. To get started, navigate to the GitHub link.

provided below and clone the repository. Once you've done that, locate your comfy UI folder and then open the custom nodes folder within it. In this folder, open the command prompt by typing CMD in the address bar. In the command prompt, type git clone followed by pasting the repository link, then press enter. It's important to note that you need to be signed into your GitHub account for this step. After the cloning process is complete, you'll see that our custom node is now installed and ready to use. One of the great advantages of this node is that there are no additional requirements. Simply launch comfy UI, and you can start using the save Florence 2 bulk prompt right away, enhancing your workflow and productivity. This workflow is designed to generate batch prompts using the power of Florence 2. Let's break down the process step by step. On the left side of our workflow, we begin with the load image list from the directory node from the Inspire pack. This node's function is to feed a group of images from a specified folder on your hard drive into Florence.

2 for processing. Florence 2, developed by Microsoft, is an advanced AI model that excels at describing images with detailed captions. It's known for its accuracy and ability to generate natural language prompts that work exceptionally well with flux and the latest sdxl models, which have good prompt adherence. For this method to function correctly, it's crucial to ensure that the keep model loaded option is disabled in Florence 2's settings. At the end of our workflow, we have a custom node called save text from Florence 2. This node, which I specifically created for this purpose, can be easily loaded in future projects by simply typing a economist. Its primary function is to capture all the captions generated by Florence 2, organize them into a text file, and prepare them for batch prompt generation. In the first field of this custom node, you can specify the name of your output text file. Remember to include the txt extension at the end of the file name. The resulting file will be saved in your comfy UI output folder for easy access. The node also features an enable

replacement button. This toggle allows you to activate or deactivate Replacements in the captions. You might want to use this feature if you prefer raw unmodified Florence 2 captions or if you're looking to generate images of scenes without specific characters present in the original images. Let's begin by testing this workflow without any Replacements to see the raw output when you run the workflow. Keep an eye on your terminal; you'll see Florence working diligently to describe all the images in your specified [Music] directory. Once the process is complete, you'll find a new text file in your comfy UI output folder. We've named this file batch image no Replacements, and it contains your prepared prompts for batch image generation [Music]. Now let's explore the workflow with Replacements enabled. We'll start by changing the file name to create a new output file. When we enable Replacements, we're essentially implementing a pattern recognition system in the image style field. You can specify the style of image you want to generate. Some examples include Instagram photo or cinematic photo.

of analog photo of or painting of. Remember to add of at the end of your chosen style. The next field is for gender and age replacement. Here, you can specify the character's gender and age, for example, young woman, young man, or middle-aged woman. You can even add details about body type and physique. This text will replace whatever character description Florence provides in your batch images. For our current example, we're going with young woman to generate a youthful version of Aara Rena, the channel's AI model. This choice raises an interesting question for our viewers: do you prefer a middle-aged Alara or the younger version we're about to create? Leave your thoughts in the comments below. The next component we have is the Laura trigger word field. If you've trained Aura or plan to use one in your batch image generation, you can specify the trigger word here. This will ensure that the Laura is activated in each of your generated prompts. Following that, we have the negative prompt field. This is particularly important if you're using SDXL, as negative prompts play a crucial

role in refining your outputs. However, if you're using flux, which doesn't utilize negative prompts, you can leave this field empty. To summarize, this custom node performs several key functions. It replaces specific keywords and phrases in the Florence captions, organizes your prompts, and prepares a text file ready for bulk image generation. As you can see, a new file has been created containing all the modifications we requested. Before we continue, I want to thank everyone who supported this channel by purchasing The Ultimate Guide to AI digital models in comfy UI. Your feedback has been incredible. Your support keeps this channel ad-free and focused on free local solutions, not the subscription services companies often pitch to me. If you want to dive deeper, use code AI Economist 40 for 40% off lifetime course access. Now, back to batch generation. Moving on to the batch image generation workflow for flux, we'll also provide a workflow for sdxl in the description, but our focus will be on flux for now. On the left side of the workflow, we have black nodes that load the flux model. If you've trained Aur for

your AI Digital model. You can load it here for those who haven't yet trained. Allur, there's a dedicated 27-minute video explaining the process. We also have nodes for clip and vae, which are essential components of the image generation pipeline. The purple nodes in our workflow are crucial components from the Inspire pack. These nodes are responsible for loading and unzipping the text file we prepared earlier using the custom node. Their primary function is to feed our prepared prompts one by one into the K sampler with flux guidance, ensuring each prompt is processed [Music] individually. To use these nodes effectively, we need to place our prepared text file in the correct directory. Copy the text file we generated from the output folder, navigate to the custom nodes folder, then to the Inspire pack folder, and finally to the prompts folder. Within the prompts folder, you'll find an example folder. This is where you should place your text [Music] file. Once you've placed the file, return to comfy UI and refresh your browser. You should now see your text file available.

to select in the load prompts from file node with this setup. You're almost ready to begin the generation process. Just a few final adjustments. One, if you're using Aura, you may want to tweak its strength to suit your needs. Two, set your desired image size. Three, ensure that the batch size is set to one, as we want to process each prompt individually. Now we're ready to start the generation process. Click Q prompt to begin. Keep in mind that this process will take some time, as we're generating an image for each of the 33 prompts in our file. The duration will depend on your graphics card's VRAM and processing speed. For reference, I'm using an RTX 390 with 24 GB of VRAM, and it took around 12 minutes to generate all 33 images. While we wait, you can monitor the progress by checking the top left corner of the interface, which displays how many images have been processed. This method of batch generation allows us to create a diverse set of images based on our carefully crafted prompts, all in one automated process. It's an

efficient way to produce a large number of variations or explore different aspects of our AI model's capabilities. Once the process is complete, we'll have a collection of images to review and potentially use in our projects. Our batch of images featuring Young Alara has been successfully generated, and it seems like the results are quite impressive. This method has efficiently produced a variety of images that are ready for social media posting, saving you considerable time and effort. The beauty of this batch generation process is its flexibility. If you're not entirely satisfied with this set or simply want more options, you can easily rerun the batch with a different seed number. This will give you even more variations to choose from, increasing the likelihood of finding that perfect image for your needs. It's worth noting that this same process can be applied to the SDXL model as well. For those interested in trying this with SDXL, you can find the corresponding workflow in the description below the video. If you have any suggestions or improvements for my first custom note.

I'd love to hear them. Please share your thoughts in the comments below. For those interested in learning more about AI modeling techniques, from basics to advanced, don't forget to check out the course available on pixel aabs docomo. [Music] to

Batch Generate AI Model Images Like a PRO in Flux! (ComfyUI Tutorial)

Batch Generate AI Model Images Like a PRO in Flux! (ComfyUI Tutorial)

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