LocalGhost

Hi everyone,In text-to-image generation, the camera acts as an invisible storyteller. It determines what the viewer notices, how the subject feels, and why an image carries emotion. By choosing the right camera position and point of view, even a simple prompt can evolve into a cinematic, powerful, or iconic visual.In this article, I will walk you through the most commonly used camera angles and perspectives in text-to-image prompting, explained in a simple, practical, and easy-to-apply way, complete with prompt examples.🧭 Overview: Common Camera Angles & Points of ViewBefore diving into detailed explanations, here is a quick overview of the camera angles discussed in this guide:👁️ Eye-Level Shot – neutral, natural perspective⬆️ High-Angle Shot – looking down on the subject⬇️ Low-Angle Shot – looking up at the subject🦅 Bird’s-Eye View – straight top-down perspective🐜 Worm’s-Eye View – extreme low-angle from the ground🎭 Over-the-Shoulder Shot (OTS) – narrative, viewpoint-based framing🔍 Close-Up / Extreme Close-Up – focus on details or emotionEach angle carries a distinct visual meaning. The sections below explain how and when to use them effectively in text-to-image prompts.👁️ 1. Eye-Level Shot📌 DescriptionThe camera is positioned at the same height as the subject’s eyes.🎯 Visual ImpressionNatural and realisticNeutral and balancedCreates a sense of equality🧩 Best Used ForPortraits, lifestyle scenes, fashion catalogs, everyday moments.📝 Prompt ExampleA young woman standing on a city sidewalk, eye-level camera angle, natural proportions, realistic lighting, casual urban atmosphere⬆️ 2. High-Angle Shot📌 DescriptionThe camera is placed above the subject and tilted downward.🎯 Visual ImpressionSubject appears smallerVulnerable, gentle, or isolated mood🧩 Best Used ForEmotional scenes, loneliness, observational perspectives.📝 Prompt ExampleA lone girl sitting on a bench, high-angle shot, camera looking down, quiet mood, soft shadows, cinematic composition⬇️ 3. Low-Angle Shot📌 DescriptionThe camera is positioned below the subject and tilted upward.🎯 Visual ImpressionPowerful and dominantHeroic or authoritative presence🧩 Best Used ForMain characters, fashion editorials, strong or confident figures.📝 Prompt ExampleA confident female model wearing a red blazer, low-angle camera view, dramatic lighting, powerful presence🦅 4. Bird’s-Eye View (Top-Down View)📌 DescriptionThe camera is placed directly above the subject, facing straight down.🎯 Visual ImpressionGraphic and structuredEmphasizes patterns, shapes, and layoutFeels abstract or conceptual🧩 Best Used ForStreet scenes, conceptual design, spatial exploration.📝 Prompt ExampleBird’s-eye view of a woman crossing a red street, top-down perspective, strong geometric composition, minimal shadows🐜 5. Worm’s-Eye View📌 DescriptionThe camera is placed extremely low, almost touching the ground, looking upward.🎯 Visual ImpressionDramatic and monumentalExaggerated scale and depth🧩 Best Used ForArchitecture, avant-garde fashion, extreme cinematic shots.📝 Prompt ExampleWorm’s-eye view of a fashion model walking between tall buildings, exaggerated perspective, cinematic scale🎭 6. Over-the-Shoulder Shot (OTS)📌 DescriptionThe camera is positioned behind one subject’s shoulder, framing another subject in front.🎯 Visual ImpressionNarrative and immersiveViewer feels present in the scene🧩 Best Used ForDialogue scenes, storytelling, cinematic compositions.📝 Prompt ExampleOver-the-shoulder shot from behind a man, focusing on a woman’s face, shallow depth of field, intimate cinematic mood🔍 7. Close-Up & Extreme Close-Up📌 DescriptionThe camera tightly frames the subject’s face or a specific detail.🎯 Visual ImpressionIntimate and emotionalStrong psychological focus🧩 Best Used ForFacial expressions, beauty shots, intense emotional moments.📝 Prompt ExampleExtreme close-up portrait of a woman’s eyes, eye-level camera, soft lighting, ultra-high detail, emotional expression🛠️ Practical Tips for Writing Camera Prompts✅ Mention the camera angle early in the prompt✅ Combine angle with shot distance (wide shot, medium shot, close-up)✅ Match the angle with the intended emotion or story✅ Avoid stacking too many camera angles in one prompt📝 Simple Combined ExampleLow-angle medium shot of a stylish woman in a red-and-black outfit, cinematic lighting, confident mood🌐 Model Compatibility: Is This Universal?Yes, the use of camera position and point of view is universal across text-to-image models. However, how accurately each model interprets and applies camera angles can vary.Think of camera angles as a shared visual language. Every model understands the vocabulary, but each has its own accent.🧠 How Different Models Interpret Camera Angles🔹 FLUX🟢 Highly accurate and literalStrong adherence to camera position and perspectivePrompt order matters significantlyExcellent for cinematic, editorial, and realistic compositions📌 Best practice: Place the camera angle early in the prompt.🔹 SDXL🟢 Stable and reliableUnderstands standard camera terminology wellExtreme angles may be softenedPerforms best when angle and framing are combined📌 Best practice: Combine camera angle with shot distance.🔹 Stable Diffusion (SD 1.5 & derivatives)🟡 Conceptually correct, but more interpretiveCamera angles influence composition more than literal positioningExtreme perspectives can be inconsistent📌 Best practice: Reinforce angles with descriptive cues.🔹 z-Image🟡🟢 Aesthetic-driven interpretationCamera angles are recognized but may be stylizedVisual mood sometimes takes priority over technical accuracy📌 Best practice: Pair angles with mood or artistic descriptors.🔹 Pony & Anime-Based Models🟡 Stylistic rather than technicalCamera angles are interpreted as visual feelingPerspective is often exaggerated or illustrated📌 Best practice: Combine camera terms with illustration context.📌 Universal Prompt Formula (Safe for All Models)[Camera Angle] + [Shot Distance] + [Subject] + [Environment] + [Mood / Style]📝 Example:Low-angle medium shot of a woman in a red blazer, urban background, dramatic lighting, confident mood⚠️ Important Note: About Prompt Accuracy & Model InterpretationWhile camera angles and prompt structures provide strong guidance, no text-to-image model can guarantee 100% literal compliance with every instruction.This is not a flaw in the prompt, nor an error in understanding camera concepts. It is a natural characteristic of how generative models work.Why Prompts Are Not Followed 100%?🔹 Probabilistic GenerationText-to-image models generate images based on probability, patterns, and learned visual associations, not strict rules. Even clear instructions may be interpreted creatively.🔹 Concept PrioritizationModels often prioritize dominant elements such as subject, style, or mood over technical details like precise camera placement.🔹 Training Bias & Dataset InfluenceSome camera angles are more common in training data than others. Rare or extreme perspectives may be softened or approximated.🔹 Model-Specific InterpretationEach model translates camera terminology differently, ranging from literal (FLUX, SDXL) to stylistic (anime-based models).What This Means for Creators✅ Camera prompts should be treated as directional guidance, not rigid commands✅ Iteration, refinement, and rerolling are normal parts of the creative process✅ Small adjustments in wording can significantly affect results📌 In practice, a well-written camera prompt dramatically increases the likelihood of achieving the intended perspective, even if it is not perfectly replicated every time.🎬 Final ThoughtsCamera position and point of view form a shared visual language across all major text-to-image models. While results may vary, understanding and applying these concepts gives creators far more control than relying on vague descriptions alone.Think of prompts not as strict instructions, but as directorial cues. The clearer the direction, the closer the model gets to your vision.Thank you for reading. I hope this article proves useful and helps you gain better control over camera angles and perspective, so you can create images that not only look good, but truly match the vision you have in mind. Happy experimenting, and may your prompts always lead to satisfying results. 🤩✨

Hello everyone, in this guide I will give a brief explanation of how to use LoRA, especially in terms of the sequence/order of placement.Question: I want to generate a text2image image. In addition to using the Base Model, I will also use several LoRAs. The question is, will the order of the LoRAs affect the image? For example: the first LoRA is Extra Detailer, the second LoRA is Enhanced Lightning, and the third LoRA is Realistic Skin.The short answer: yes, the order of LoRA can have an effect, but it's not always dramatic. Think of LoRA as a transparent layer layered on top of a base painting. The order determines who gets the last word in the overlapping areas. 🎨Let's analyze it carefully.1️⃣ How LoRA works (brief but precise)Most LoRA models work by adding biases or weight modifications to the base model on the same layer.If two LoRA models touch the same area (e.g., facial details, lighting, or skin texture), then:LoRAs loaded later tend to be more dominantEspecially if the weight is similar or quite highIf LoRA touches different areas, the sequence is barely noticeable.2️⃣ Analyze the LoRA example you are asking aboutOrder:Extra DetailerEnhanced LightningRealistic SkinWhat happened?Extra DetailerAdding micro-details, textures, and sharpness. This is global in nature.Enhanced LightningChange contrast, highlights, shadows, sometimes color tones.Realistic Skin (last)Usually focuses on the face and skin: pores, softness, color blending.📌 Since Realistic Skin was loaded last:He can override the rough detail effects of Extra Detailer.The skin becomes more natural, not too "crispy"Lighting is still felt, but adjusted to the skin➡️ This is a pretty reasonable order for realistic results.3️⃣ Example if the order is reversedFor example:Realistic SkinExtra DetailerEnhanced LightningThe results can be:The skin is initially realisticThen “sharpened again” by Extra Detailer → pores can be too strongThe final lighting can make the skin look plastic or over-contrast.It's not wrong, but the characters are different.4️⃣ Rules of thumb (that practitioners actually use)Use this principle:Global LoRA first → specific LoRA laterIdeal order:🔹 Style / Detail / Texture LoRA🔹 Lighting / Mood / Color LoRA🔹 Anatomy / Face / Skin / Character LoRAIn other words:The ones you most want to “maintain” the effect of, put last.5️⃣ Important notes that are often forgottenWeight is more influential than orderLoRA weight 1.2 at the beginning can still override LoRA weight 0.6 at the endClip vs UNetIf LoRA targets are different (e.g. one is dominant in CLIP, one in UNet), the order becomes less significant.Sampler & CFGHigh CFG can make LoRA conflicts more visibleConclusion 🎯✔️ The LoRA order does matter, especially if:The effects overlap each otherSimilar weightTouching the face / lighting / details togetherQuestion: If I use the following LoRA settings globally: Face, Detailer, Lighting, Realistic, Correction (hand/finger), Background Detail. And all the weights are the same, say they all use 0.8 (the default weight). What would be a good LoRA order?Answer: Imagine you're putting together a movie scene on a mini-stage. There's a set crew, a lighting designer, a makeup artist, and a final editor. They all have the same volume (weight 0.8), so whoever comes in last will have the most say in the final touches. 🎬Assuming all weights are the same (0.8) and that LoRAs potentially touch overlapping areas, this is the most stable and “sane” sequence globally:🔑 Main principles (in summary)General → specific → corrective → finishing touchesThose who shape the world are done first, those who correct mistakes come later.✅ Recommended LoRA order1️⃣ Background detailsReason:Most global and insensitiveDetermine the texture of the environment, architecture, foliage, etc.Hardly any conflict with the face or anatomyIt's like building a stage set first.2️⃣ LightingReason:Lighting affects the perception of all objectsIt is better to be “accepted” by the face and skin, not to be inflicted on it.The lights are installed before the actor is made up.3️⃣ DetailerReason:Increasing global sharpnessIf placed too late, it can damage the skin or hands.This is basic sharpening before the touch of realism.4️⃣ RealisticReason:Adjusting natural texture: skin blending, tone, micro-imperfectionTaming the effects of previous over-detailingMake-up stage so it doesn't look digital.5️⃣ FaceReason:Very sensitiveOften adjust the proportions, eyes, nose, expressionMust come after lighting & realism for consistencyThe main actors are made up after the stage and lights are ready.6️⃣ Correction (hand/finger)Reason:Corrective in natureOften “override” other LoRAsThe safest place is at the end.The editor comes last, correcting anything strange.🧾 Final order (summarized)Background Detail → Lighting → Detailer → Realistic → Face → Hand/Finger Correction ⚠️ Important note (small but valuable gold)With the same weight (0.8), this sequence really feels the effect.If the hands still don't fit:hand correction can be increased to 0.9–1.0 without messing up the faceIf the face becomes too “cartoonish”:lower the face LoRA to 0.7, don't change the order yet🎯 Conclusion✔️ The LoRA order is not about right or wrong, but who has the final say.Question: I use Flux and SDXLAnswer: For Flux and SDXL, the rules are philosophically similar, but the sense of influence of the LoRA order is different. Think of Flux as fast-flowing, adaptive water, while SDXL is like thick oil paint that leaves brush marks. Therefore, the order needs to be adjusted slightly. 🎨Below I give a separate optimal sequence, assuming:All LoRA weight = 0.8LoRA Types: Face, Detailer, Lighting, Realistic, Hand/finger correction, Background detailsTarget: realistic and stable🔷 FLUX (all variants)Flux is more “context-respecting,” so LoRA coming in last is less brutal, but still impactful.✅ Best order for FLUXBackground Detail → Lighting → Detailer → Face → Realistic → Hand/Finger Correction Why is it different?Realistic behind the faceFlux blends more smoothly, so realism can “reset” the face without destroying identity.Detailing should not be too finalIf it's too far back, Flux tends to make the skin too rough.📌 Flux Notes:Hand correction in the last position is almost always the safest.Flux is relatively tolerant, so this sequence is stable even for full body🔷 SDXLSDXL is much more sensitive to the “last word.” The LoRA sequence in SDXL has a more pronounced effect.✅Best order for SDXLBackground Detail → Lighting → Detailer → Realistic → Face → Hand/Finger Correction Why is the face later?LoRA faces in SDXL often:change the structureexpressioneye & nose shapeIf placed before realism, the result can feel “polished” and lose character.📌 SDXL Notes:Realistic functions as a balance of detailThe face should “lock identity” at almost the end🧠 Quick summaryModel Key sequenceFlux: background → lighting → detailer → face → realistic → correctionSDXL: background → lighting → detailer → realistic → face → correction⚠️ Hassle-free tuning tipsBroken hand?👉 increase LoRA correction to 0.9–1.0Skin too sharp?👉 lower Detailer to 0.6–0.7Does face feel “less alive”?👉 increase the face LoRA 0.85 without changing the order🎯 Conclusion✔️ LoRA order still matters in Flux and SDXL, but:Flux = more flexibleSDXL = more sensitive✔️ Weight overrides all sequences/orders 👉 Higher weight beats smaller weight for similar or identical LoRAThat's all, folks. I created this guide based on my experience in generating text into images. Since I mostly use the Flux and SDXL/Pony Base Models, I think it won't be much different for other Base Models, so feel free to try it yourself.Final Note: This is just a guide, so it's not absolute; it all comes down to your creativity and imagination.

Hi everyone, in this guide I will try to explain the correct way to create a full body image using Flux (other models will most likely be able to do this too). You may have experienced the difficulty of creating full-body images, as the results are usually cropped, usually with a 2:3 image ratio (768x1152) and other variations. One effective way is to change the image ratio to be larger in height and smaller in width (e.g., 800x2048). But actually, that's unnecessary because Flux is very "stubborn."Why is Flux so “stubborn” about full body?1️⃣ Data bias: Flux “likes face & torso”The Flux model is heavily biased towards the face, chest and waist because:The training dataset is full of portrait, half-body, fashion cropFace = high detail = high aesthetic value according to the modelWhen you write:full body shot, wide angle shotThe model reads it, but its internal priority remains the face. So the camera “zooms in” on its own.2️⃣ The term “wide angle” ≠ camera distanceThis is a classic trap.Prompt → What the model understandswide angle → lens distortionfull body → intention, not a guaranteecinematic → lighting & mood❌ It doesn't mean: the camera is far away✔️ Models can still use wide lenses but close up3️⃣ Human = main object → auto cropFor human subjects, Flux automatically:Zoom in on the subjectSacrifice leg firstfocus on expression & top clothingThat's why the background is rarely "used".The RIGHT way to force full body in FluxThis isn't one trick. It's a combination of techniques.🧠 Main principlesDon't just say "full body" Force it with physical context and framing.✅ Technique 1: Use a physical anchor (THIS IS IMPORTANT)The model adheres more to object relations than to camera terms.❌ Bad:full body shot, wide angle✅ Good:standing on the ground, feet visible, head to toe visible, shoes touching the floorModels cannot crop the feet if "feet touching the ground".✅ Technique 2: Use “distance language”Replace camera language with physical distance.Effective example:camera placed far away, subject small in frame, full height visibleOr:long distance shot, entire body visible within the frame✅ Technique 3: Use “environment dominance”Make the background more important than the human.large environment, vast background, subject occupying small portion of the frameFlux will “move the camera away”.✅ Technique 4: Add anti-crop instructionFlux is quite responsive to explicit prohibitions.no cropped body, no half body, no close upThis isn't an official negative prompt, but it's still influential.🔥 Examples of prompts that are PROVEN to be more compliantSimple example:a young woman standing on a street, full height visible from head to toe, feet clearly visible touching the ground, camera placed far away, subject small in frame, wide environment background, entire body inside the frame, no cropped body, natural daylightOr a more “Flux-friendly” version:long distance shot of a woman, standing upright, head to toe visible, shoes visible on the ground, wide environment, camera far away, subject centered but small in frame⚠️ Things to AVOID🚫 Don't just rely on:full body shotwide anglecinematicfashion photographyThat's a cosmetic prompt, not a structural instruction.The summary 🎯Flux naturally cuts through the human body“full body” is not enoughObject + camera distance + environment relation is keyForce models with physical logic, not photographic terms.👩 FULL BODY TEMPLATE IMAGE OF A WOMAN (Or Man if you want to change it)Flux is more aggressive in zooming in on women, so this template is tighter on the legs & framing. Example:a young adult woman, standing upright on the ground, full height visible from head to toe, legs fully visible, feet clearly visible touching the ground, entire body fully inside the frame, no cropped body, no half body, no close up, camera placed far away, long distance shot, subject small in frame, wide environment surrounding the subject, wearing a summer dress and flat sandals, full outfit visible including footwear, located in a wide park with trees and open space, background dominates the scene, large scale background, natural body proportions, realistic female anatomy, balanced natural standing pose, soft daylight, high detail, realistic, flux dev style🧠 Why this template works“feet touching the ground” = Flux dare not cut“subject small in frame” = camera moves away slightlyEnvironment dominance = background priority > faceExplicit crop ban = suppress portrait biasThis isn't magic. It's stubborn negotiation with a model. 😄🔧 Additional tips (optional but powerful)If it's still cut off → add:full body framed with extra space above head and below feetFor an establishing backdrop:vast environment, large scale sceneFor safe poses:standing straight, arms relaxed at sidesWill "camera placed far away" make the impression that the human object in the photo is too far away / zoomed-out?Short answer:Maybe yes, maybe not.It depends on the combination, not the phrase alone.Now we dissect it with the Flux version of camera logic.Why does “camera placed far away” feel scary?Because if it stands alone, Flux reads it as:small subjectdominant environmentextreme distanceThe result could be something like:🧍‍♂️ ➝ human dot in the background oceanBut… in the template above, why is it safe?Because the phrase is CLIPPED by another instruction.Safe combination:camera placed far away, subject centered, full height visible, natural body proportionsIt means:camera back away ➝ so that the feet are inbut the subject remains the center of the framenot an extreme wide establishing shotHow to set a “safe distance” (sweet spot)🔧 Opt 1: Safe version (RECOMMENDED)Change far away ➝ moderate distancecamera placed at a moderate distance, full body visible, subject clearly visibleThis is the most stable for Flux.🔧 Opt 2: Stay “far away” but lockedcamera placed far away, subject clearly visible, subject occupying medium portion of the frameThe prompt medium portion holds back excessive zoom-out.🔧 Opt 3: Framing language, not distanceFlux is more compliant to this:full body framed with space above the head and below the feetWithout mentioning the distance at all.Quick table: distance word effects in Fluxcamera placed far away ➝ safe for feet, risky too smallmoderate distance ➝ most balancedlong distance shot ➝ dominant environmentsmall subject in frame ➝ very far awaymedium subject in frame ➝ clear full bodyMy final recommendation 🎯For 90% of human full body cases:camera placed at a moderate distance, full body framed from head to toe, subject centered and clearly visibleIt's far enough for feet, close enough for details.Conclusion:❌ “far away” is not poison⚠️ But it must be clamped✅ “moderate distance + framing language” = most stable🧠 Think of Flux like a stabborn photographer, not a passive camera.Below are 3 camera distances templates.I wrote the core template and then a ready-to-use example so it's easy to copy.🧍‍♀️ CLOSE FULL BODYImpression: dominant subject, clear clothing details, secure feetfull body framed tightly from head to toe, subject occupying large portion of the frame, camera placed at a close but full-body distance, space visible above the head and below the feet, entire body inside the frame, feet clearly visible touching the ground, no cropped body, no close up🧍 MEDIUM FULL BODYImpression: most balanced, safe for 80% of use casesfull body clearly visible from head to toe, subject occupying medium portion of the frame, camera placed at a moderate distance, balanced framing, wide environment visible but not dominant, feet clearly visible touching the ground, no cropped body🌆 WIDE / ESTABLISHING SHOT (BUT FULL BODY IS SAFE)Impression: strong location, small but intact humanestablishing shot, wide environment dominating the scene, subject occupying small portion of the frame, full body visible from head to toe, entire body inside the frame, feet visible touching the ground, subject clearly identifiableImportant for Flux:Don't mix small subjects in frame with close full body shots.Always repeat head to toe + feet touching groundFor women, repeating the leg 2× is normalDoes the prompt fit at the beginning of the prompt before the subject and details or at the end of the prompt after the subject and other details?Answer:Place it at the BEGINNING of the prompt.NOT at the end. NOT in the middle. IN FRONT.Now a really useful explanation for FluxHow Flux “reads” prompts (practical version)Flux doesn't read like a human reads a sentence. It works like this:Beginning = framing & compositionMiddle = subject & poseEnd = cosmetics (style, lighting, mood)It means:What you write in the first 25–30% of the prompt determines the camera.If “full body” and “feet visible” appear later, Flux has often already “decided” on the portrait framing.IDEAL sequence for full body (must follow)[1] Framing & Camera (FRONT) [2] Main subject (human) [3] Pose & physical [4] Clothing & visual details [5] Environment & background [6] Lighting & styleHard rules (brief but important)✅ MANDATORY at the beginningfull body / head to toefeet touching groundframing (close / medium / wide)subject portion in frameno cropped body⚠️ CAN be in the middleposegenderageexpression🎨 AT THE ENDcinematicfashionstreetlightingmoodrealismWhy does it often fail if it is placed at the end?Because Flux:Determine the crop earlyDon't “repeat” framing unless you force it.Trust initial instructions more than final revisionsConclusion 🎯Framing = frontDetail = backFull body fails → almost always because the framing comes too lateFinal note: This is just a guide, you don't need to 100% copy the prompt I made, you can modify it according to your own taste as long as you stick to the prompt placement rules. ✌👍👌That's all, folks. Hopefully, this guide helps you create text2image with Flux, especially full-body images, with satisfying results. 😁✨🤩