I’m currently involved in a project focused on producing consistent character appearances from various angles. I am using Flux in conjunction with Pulid for this, but I’m facing some challenges.
The key issue is ensuring that the character’s facial features, clothing, and overall look remain consistent when transitioning between views like the front, side profile, three-quarter, and back. At times, the resulting images appear to depict entirely different characters despite using a single reference.
Has anyone managed to establish a dependable workflow for this? I would like to know about:
Effective methods for preparing character references
The best settings to ensure consistency
Any preprocessing that aids in transitioning angles
Mistakes to avoid during the generation
I would greatly value any insights or advice on what could be improved in my process. Thank you for your help!
the main mistake i see people make? rushing reference prep. get that initial character shot nailed down before you even touch different angles. pro tip: use inpainting masks on eyes or mouth when they drift between views - saves you from regenerating the whole thing.
Batch processing saved me so many headaches. Don’t try perfecting each angle one by one - I generate 4-5 variations per view and pick the best matches.
Make a character style guide first. I spend 15 minutes noting eye shape, nose width, jaw structure before doing angles. Sounds boring but catches drift early.
Temperature matters more than you’d think. I keep it low (0.7-0.8) for face shots, bump it slightly for full body. The model goes crazy with proportions when temperature’s too hot.
Learned this the hard way: save your winning parameter combos. I’ve got a simple text file with settings for different character types. Athletic characters need different Pulid weights than older faces or stylized looks.
Seed consistency across angles helps too. Start with a good seed for your front view, then use variations of that same seed for other angles instead of random generation.
This video covers solid techniques for character consistency that work great with Flux workflows.
The preprocessing step everyone talks about is legit. Clean backgrounds, consistent lighting, and neutral expressions in your reference make everything downstream way easier.
Been wrestling with this too and render order matters way more than I thought. Don’t jump around randomly between angles - start with front view, then go three-quarter, profile, back. Each one builds on the last. Game changer: feed your good results back as references. Got a perfect front view? Use that generated image plus your original reference when you do the profile shot. Creates this reinforcement loop that locks in facial structure. Prompt weighting is huge for specific features. Character’s got weird eyebrows or a distinctive nose? Weight those higher (eyebrows:1.2). Simple trick but it works. Technical note: export your reference at exactly 1024x1024 and keep all generations the same size. Different aspect ratios mess with the model’s understanding of face proportions.
Those manual tweaks and constant parameter adjustments are exactly why I automated this whole thing. Wasted way too many hours fine-tuning Pulid weights and CFG scales by hand before realizing automation was the obvious answer.
Built a workflow that handles the entire character rotation pipeline automatically. Processes your reference image, generates consistent prompts for each angle, manages Pulid settings, and does quality checks between outputs. When it spots inconsistencies, it adjusts parameters and reruns problem angles.
The real game changer? Running multiple variations at once and picking the best matches based on facial feature consistency. No more babysitting each generation or comparing outputs manually.
For preprocessing, my pipeline handles image cropping, lighting normalization, and background removal before feeding into Flux. It maintains a database of successful parameter combos for different character types, so it learns over time.
The workflow runs in the background and spits out a complete character sheet with all angles. Saves me 3-4 hours per character vs doing it manually.
I’ve been working with Flux and Pulid for some time, and a few strategies have significantly improved my workflow. Utilizing multiple reference images is essential; it allows me to capture consistent details across various angles. I typically generate a batch of images for the character from various perspectives initially, which helps me identify the most reliable references. Adjusting the CFG scale to a lower range, around 6 to 7, has also made a positive difference, preserving the facial structure better during transition. Moreover, I find that describing distinctive facial features in the prompts ensures that those elements remain uniform across the different angles. One crucial aspect often overlooked is the lighting in your reference images; keeping it consistent avoids confusion for the model regarding how shadows fall on the character’s face.
Pulid weight settings completely changed my character consistency game. I’ve found that cranking the weight too high actually makes things worse, not better; the sweet spot is around 0.8-1.0 for the main reference. Another significant breakthrough was preprocessing my reference images first. I noticed that neutral expressions and straight head positioning yield much better results, while the model tends to struggle with extreme expressions or unusual tilts. It’s crucial to keep your prompts identical between angle shots; only change the angle description. Background elements can interfere with character recognition, so I prefer simple backgrounds. Additionally, tight cropping around the face and shoulders has been a game-changer for maintaining facial structure consistency across different views.
Facial landmark consistency was my game changer here. Instead of just trying to match overall looks, I focus on specific measurement ratios - eye distance, nose width compared to eye spacing, where the mouth sits. This catches subtle drift I used to miss completely. The model’s way better at keeping these proportions right than matching exact visual appearance. Negative prompts made a huge difference too. I don’t just describe what I want - I actively exclude what I don’t want. Stuff like ‘different person, altered facial structure, inconsistent features’ in negatives keeps the model locked in. Temperature ramping works great - start cold for initial angles to nail down the character, then bump it up for creative shots like back views where perfect face matching doesn’t matter as much. One time-saver: generate all angle variations in one session without closing Flux. The model seems to remember the character better when you stay in the same session.
