Man's talk

轉貼至RiddlyHey all! I made a visual example of the different hairstyles you can use for your prompts. Keep in mind that you can pair the hairstyles with the length of the hair too!Shoutout to annnnnie for the hairstyle list!

轉貼至PictureWhat Makes Qwen Image Stand Out?The brilliance of Qwen Image lies in its ability to master what its predecessors have consistently failed at. It produces text that is not only legible but also visually harmonious with the surrounding image.Professional-Grade Text Integration: It's a true synergy of image and typography. Words aren't just an afterthought; they're an integral part of the design, maintaining perfect clarity and contextual harmony across all visual styles.A Global Language: Whether you need crisp English headlines or complex Chinese characters, Qwen Image handles multilingual content with exceptional precision. This makes it an invaluable tool for global brands and anyone working with diverse linguistic content.Creative Versatility: Don't be fooled by its text focus. This workflow adapts effortlessly to any artistic style, from photorealistic shots to stylized illustrations, all while keeping your text quality impeccable.Precision and Control: The workflow gives you sophisticated controls, allowing you to fine-tune the quality of your output. You can strike the perfect balance between generation speed and visual fidelity.Your Guide to Using Qwen Image in ComfyUIGetting started with Qwen Image is straightforward once you know the key steps.Setting Up Your CanvasBegin by configuring your output dimensions with the EmptySD3LatentImage node.The recommended standard is a square 1328x1328 pixels, but you can adjust this to fit your project.Keep the batch_size at 1 to ensure focused, high-quality generation.Crafting Your PromptYour prompt is your blueprint. In the CLIP Text Encode (Positive Prompt) node, provide a detailed description. Qwen Image thrives on specificity.Start with the core visual elements you want to see.Then, clearly describe the text you want rendered, including the specific words.Go further by specifying typography styles, layouts, and where you want the text placed within the scene.Include contextual details about the visual environment to help the model weave the text in seamlessly.Essential Workflow Steps for Optimal ResultsTo get the most out of the model, you need to use the right settings.Model Performance: Use the ModelSamplingAuraFlow node. Set the Shift value to 3.1. You can increase this for sharper details or decrease it for a softer look, depending on your desired outcome.Sampling Settings: In the KSampler node, these are my go-to settings:Steps: 20. While the official recommendation is 50, I've found 20 offers a fantastic balance of speed and quality.CFG: 2.5. For a speed boost, you can drop this to 1.0, but you might lose a bit of consistency.Sampler: euler for stability.Scheduler: simple, which is optimal for this workflow.Advanced Optimization TipsBalancing Speed and Quality: For even faster generations, try reducing the steps to 10-15 and the CFG to 1.0.Enhancing Detail: If your images look blurry, increase the Shift value in the ModelSamplingAuraFlow node.System Requirements: Be aware that this workflow is VRAM-intensive. It uses approximately 86% of the VRAM on an RTX 4090 24GB. Generation times are typically around 94 seconds for the first run and 71 seconds for subsequent ones.Acknowledging the PioneersThis groundbreaking workflow is a testament to the innovation of the Qwen team at Alibaba Cloud, who developed the 20B-parameter MMDiT model. Their pioneering work on advanced text rendering has brought professional-grade typography to accessible AI workflows. A huge thanks also goes out to the ComfyUI community for their seamless integration efforts. The Qwen Image model truly marks a monumental leap forward in the field of text-aware image synthesis.Setting Up Your Qwen Image GenerationConfigure image dimensions: Use the EmptySD3LatentImage node to set your output size:Standard: 1328x1328 pixels for square formatsAdjust width and height based on your Qwen Image project needsKeep batch_size at 1 for focused generationCraft your text prompt: In the CLIP Text Encode (Positive Prompt) node:Write detailed descriptions that include specific text elements you want renderedQwen Image excels with prompts that specify typography styles, layouts, and text placementInclude contextual details about the visual environment surrounding your textEssential Qwen Image Workflow StepsOptimize model performance: The ModelSamplingAuraFlow node fine-tunes the Qwen Image generation:Shift value: Set to 3.1 (increase for sharper details, decrease for softer results)This parameter significantly affects the quality balance in your Qwen Image outputConfigure sampling settings: In the KSampler node for optimal Qwen Image results:Steps: 20 (official recommendation is 50, but 20 provides excellent quality-speed balance)CFG: 2.5 (set to 1.0 for speed boost with slightly reduced consistency)Sampler: euler (recommended for Qwen Image stability)Scheduler: simple (optimal for this Qwen Image workflow)Advanced Qwen Image OptimizationQuality vs Speed Balance: For faster Qwen Image generation, reduce steps to 10-15 and set CFG to 1.0, especially when using alternative samplers like res_multistepEnhanced Detail Control: Increase the shift value in ModelSamplingAuraFlow if your Qwen Image outputs appear blurry or lack definitionMemory Management: This Qwen Image workflow requires approximately 86% VRAM on RTX4090 24GB, with generation times of ~94 seconds for first run, ~71 seconds for subsequent generations

轉貼至TensorArtRedesigned HomepageWe’ve streamlined the way you enter the creative workspace from the Toast homepage. Now it’s easier than ever to start generating images and videos right away!Each entry point is paired with inspiring examples—real works from our community—because we can’t wait to see more of your amazing creations appear here. 〰Avatar Function SupportWith just one static image and a short audio clip, you can now create cinematic-quality digital human videos. Expect natural facial expressions, perfectly synced lip movements, and fluid body gestures — up to 60 seconds per generation, with full text-based control.Applications range from livestreaming with digital avatars to film and media production, and much more.How to get started:On the homepage, click the Avatar entry to enter the workspace.Select your model type:Infinite Talk excels at voice-to-character synchronization.WAN2.2-S2V offers superior visual quality.Upload your character's imageUpload or generate your audio file online.Finding the right audio file can be tricky, so we’ve added an online audio cloning feature. The system will render your dialogue using the tone and style of your reference. Simply click Generate Audio and:Enter the dialogue text.Provide a reference audio clip.Don’t have a reference clip? No problem. We also provide preset system voices for you to choose from. Once your audio is generated, click Use to apply it directly in the workspace.Finally, set your parameters:Prompt: Keep it simple—just describe the subject. If you’d like gestures or extra actions, add them (e.g., “This man is speaking while waving his arms”).Resolution: Higher resolutions yield sharper results, but require more compute.Generation Mode:Fast Mode: quicker, cheaper, with slight quality trade-offs.Quality Mode: best results, but requires more time and compute.That’s it—you’re ready to generate. We can’t wait to see your high-quality digital humans shared in the community. We look forward to seeing your work pinned on the homepage!

轉貼至 RedHairedDamselHello! Today we're looking into how to prompt different types of eyes. Let's go~Summary:Danbooru ReferenceModel + Quality promptsIrisPupilsAround the eyesScleraDanbooru ReferenceThe list is long, and some of the eyes did not work for my model, but it might work for yours.Update: For some reason, Tensor is not letting me post a link of danbooru. But if you go to their site, just append this to the url: wiki_pages/tag_group%3Aeyes_tagsModel + Quality PromptsUsing Diviling-Illustrious Anime: https://tensor.art/models/897826979653397911Positive prompt: (masterpiece, best quality, absurdres, highres), amazing quality, very aesthetic, (volumetric lighting), digital art style, drawn aesthetic, concept painting, ultrahigh definition,Negative prompt: worst quality, early, low quality, lowres, signature, username, logo, bad hands, mutated hands, mammal, anthro, furry, ambiguous form, feral, semi-anthro, boring, uglyExample prompt: 1girl, short black hair, bangs, bob cut, red and yellow heterochromia, close up, front view, looking at viewer, focus face, simple white background,IrisJust add the color followed by "eyes" for most colors. See other styles below:PupilsThat's the small circle inside the iris.Around the eyesScleraThe white part of the eye.

在开始绘图前，请先明确你的构图场景、风格方向，以及希望传达的细节关键词。本期是一章辅助提示词分享，排版由AI帮我完成，我比较懒的排版常用提示词参考（双重曝光风格）以下是我经常使用的 Prompt 示例，适用于“双重曝光”风格。不同模型表现略有差异，仅供参考，如有问题欢迎指正：silhouette, within, blending, blended, merged, filled with / into, Jeddbleil, double exposure手部动作（Hand Gestures）互动与招呼类waving：挥手（角色打招呼、道别）【社交、迎接、离别】saluting：行军礼（正式致意）【军事、正式场合】high-five：击掌（庆祝、友好）【伙伴间庆祝、友谊】clapping：鼓掌（赞美、认可）【庆祝、演出】pointing：指向（强调方向或目标）【讲解、示意、互动】表达与情感类thumbs-up：竖起大拇指（赞同、鼓励）【积极反馈、喜好】thumbs-down：竖起大拇指向下（否定、不满意）【否定、表达失望】fist-clenching：握拳（愤怒、紧张、决心）【战斗前、内心斗争】open-palm：张开手掌（欢迎、防御、祈祷）【招呼、接纳、请求】finger-snapping：打响指（节奏感、魔法瞬间）【表演、变化】思考与姿态类hand-on-chin：手托下巴（沉思、困惑）【思考、犹豫】hand-on-hip：手叉腰（自信、不满）【质问、姿态感】hand-on-face：手捂脸（震惊、羞涩、失落）【反应瞬间、内向情绪】hand-on-heart：手放胸口（真诚、感动、发誓）【感情表达、承诺】表现与动态类grabbing：握住（紧张、抓住机会）【紧张时、紧急动作】fingertips-touching：手指尖接触（细心、低调、计划）【思考、低调交流】pinching：捏住（小心、关心、纠结）【检查、轻轻触碰】flipping：翻动（无聊、愤怒）【翻书、翻桌】palms-together：双掌合十（祈愿、感激、求助）【请求、祈祷】picking-up：捡起（专注、小心）【细致操作、动作】难度 / 节奏类spreading-fingers：张开手指（强烈、压力）【紧张、惊讶】gripping：紧握（控制、专注）【抓住、攻击】tapping-fingers：轻敲手指（焦虑、不耐）【等待、急切】其他细节表现类shaking-hand：握手（交流、协议）【社交、合作】twisting-wrist：转动手腕（疲劳、无聊）【细节动作】flexing-fingers：弯曲手指（放松、恢复、体操）【手部活动】resting-hand：手轻放（放松、休息）【情感松弛】clapping-back：背后鼓掌（偷偷支持）【暗中支持】腿部动作（Leg Gestures）姿势类standing-with-legs-apart：双腿分开站立（稳重、自信）【战斗准备、威严展示】standing-with-legs-crossed：双腿交叉站立（休闲、放松）【等待、聊天场景】sitting-cross-legged：盘腿坐（随意、放松、冥想）【居家、教室、自然场景】sitting-with-legs-stretched：双腿伸直坐（疲惫、放松）【旅行、休息】sitting-with-legs-bent：双腿弯曲坐（含蓄、少女感）【害羞、情绪细腻场景】walking-with-long-strides：大步走（自信、紧迫）【赶路、任务场景】walking-with-short-steps：小步走（谨慎、优雅）【紧张、礼仪场景】kneeling：跪姿（恳求、忠诚、礼拜）【宗教、情感高潮】squatting：蹲下（观察、调皮、准备动作）【低视角互动、行动开始】脚部动作类tip-toeing：脚尖站立（轻盈、偷偷、谨慎）【悄悄行动、偷袭】pointing-toe：指向脚尖（展现优雅、舞蹈动作）【舞蹈、优雅动作】flexing-ankles：弯曲脚踝（疲劳、恢复、舒展）【休息、放松】bouncing-on-toes：踮脚跳跃（活力、期待）【紧张、急切等】foot-tapping：脚尖敲击地面（焦虑、不耐）【等待、急切】crossing-ankles：交叉脚踝（优雅、放松）【放松、优雅的坐姿】rocking-back-and-forth：前后摇摆（焦虑、不安）【焦虑、等待】raising-heel：提起脚跟（不安、注意力集中）【紧张、预备动作】kicking：踢（愤怒、冲动）【防御、发泄愤怒】stepping-forward：向前迈步（进取、自信）【进攻、走向目标】stepping-backward：向后退步（后退、避免）【防守、撤退】twisting-feet：脚部旋转（困惑、不安）【不耐烦、焦虑】脚趾动作类wiggling-toes：脚趾扭动（放松、舒适）【休息、放松】curling-toes：脚趾蜷曲（紧张、不安）【紧张状态】pointing-toe：脚趾指向（优雅、舞蹈）【舞蹈、表现】scrunching-toes：脚趾收缩（不适、困扰）【疲惫、不适】tapping-toes：脚趾轻敲（不耐烦、急切）【等待、焦虑】spreading-toes：脚趾张开（放松、舒展）【恢复、轻松】pressing-toes：脚趾用力（紧张、力量）【控制、发力】手指动作（Finger Gestures）指令与强调类pointing-with-index-finger：用食指指向（下指令、强调）【命令、讲课、展示物品】making-a-fist：握拳（愤怒、斗志）【决斗、激动、煽动情绪】making-a-peace-sign：竖两指（胜利、和平、自拍）【合影、流行文化】making-a-come-here-gesture：招手让人过来（暗示、引导）【角色互动、引导】making-a-stop-gesture：手掌前伸（制止、警告）【争执、警觉】making-a-call-me-gesture：拇指和小指张开（联系、社交）【俏皮、暗示沟通】making-a-thumbs-up-gesture：举拇指（称赞、肯定）【胜利、认可】making-a-thumbs-down-gesture：拇指向下（反对、否定）【拒绝、嘲讽】手指与手掌互动类（Finger and Palm Interaction）pointing-with-multiple-fingers：多指指向（指示、强调方向）【指引、指向】touching-fingers：手指互相触碰（思考、犹豫、细致）【思考、谨慎】holding-a-finger-to-lips：食指放在嘴唇上（示意安静、谨慎）【安静、隐秘】index-finger-and-thumb-pinch：食指和拇指捏住（轻触、审视）【检查、敏感操作】手腕动作类（Wrist Gestures）wrist-twist：转动手腕（放松、无聊）【疲劳、细节动作】flexing-wrist：弯曲手腕（用力、强迫）【力量、控制】shaking-wrist：摇晃手腕（不耐烦、失望）【焦虑、反应】flicking-wrist：振动手腕（生气、激动）【快速反应、警告】手臂动作类（Arm Gestures）raising-arm：举臂（求救、问询）【寻求帮助、庆祝】lowering-arm：放下手臂（放松、平静）【失望、退却】crossing-arms：双臂交叉（防御、不信任）【拒绝、冷漠】stretching-arm：伸展手臂（放松、舒展）【恢复、疲劳后的动作】elbow-pointing：弯曲肘部指向（暗示、挑衅）【无声交流、态度表现】pushing-with-arm：用手臂推（推动、抵抗）【防守、推动】pulling-with-arm：用手臂拉（拉住、吸引）【控制、反向动作】其他手部细节动作（Other Hand Details）finger-waving：手指晃动（不满、警告）【反对、威胁】clenching-fingers：紧握手指（专注、愤怒）【紧张、决心】stretching-fingers：伸展手指（放松、恢复）【恢复、放松】thumb-over-finger：大拇指压住食指（决策、犹豫）【考虑、思考】头部动作（Head Gestures）同意与否定类nodding：点头（同意、认可）【正常对话、肯定答复】shaking-head：摇头（否定、不信）【拒绝、怀疑】思考与疑惑类tilting-head：侧头（疑惑、卖萌）【思考、好奇、撒娇】looking-up：向上看（幻想、灵感、请求）【祈祷、星空、想象力】looking-down：低头（思考、内敛、羞涩）【伤感、失落、沉思】情感与表达类bowing-head：低头（羞愧、礼貌、悲伤）【认错、反省、正式场合】raising-eyebrows：挑眉（惊讶、调情）【表情丰富、反应场景】furrowing-brows：皱眉（担心、生气）【冲突、压力场景】winking：眨眼（打趣、默契）【俏皮、暗号】blinking：眨眼（自然动作、困倦）【情绪缓冲、转场】面部与头部动作组合（Head + Facial Combos）head-tilt-with-smile：侧头微笑（撒娇、魅力、亲和力）【亲近、温柔】head-tilt-with-frown：侧头皱眉（疑惑、不解）【好奇、质疑】face-palming：捂脸（震惊、羞愧、失望）【意外、尴尬】looking-away：偏头看向远方（思考、逃避）【沉思、逃避目光】raising-chin：抬起下巴（自信、挑战）【坚定、不屈】颈部动作（Neck Gestures）neck-tilting：颈部倾斜（思考、质疑）【疑问、好奇】neck-craning：颈部伸展（好奇、注视远方）【寻找、观察】neck-rotation：旋转脖子（放松、缓解压力）【舒展、放松】neck-stretch：伸展脖部（疲劳、放松）【解除紧张、活动】面部组合动作（Facial Combos）smiling-with-raised-eyebrows：微笑配挑眉（高兴、调皮）【友好、轻松】frowning-with-raised-eyebrows：皱眉配挑眉（怀疑、惊讶）【困惑、质疑】smiling-with-winking：微笑配眨眼（调皮、暗示）【俏皮、暗号】frowning-with-winking：皱眉配眨眼（困惑、调皮）【打趣、示意】眼睛与头部动作组合（Eye + Head Gestures）eyes-widening：眼睛睁大（惊讶、震惊）【意外、吃惊】narrowing-eyes：眼睛眯起（怀疑、警觉）【质疑、警惕】rolling-eyes：眼睛翻白（不耐烦、嫌弃）【厌烦、失望】eye-contact：目光接触（专注、信任）【交流、示意】looking-over：眼睛扫视（挑衅、评估）【观察、对比】looking-around：眼睛环视（好奇、警觉）【寻找、四处观察】面部细节与组合动作（Facial Detail & Combinations）smiling-with-closed-eyes：微笑配闭眼（幸福、喜悦）【愉悦、感动】squinting：眯眼（困惑、仔细看）【难以看清、集中注意】grinning-with-closed-eyes：咧嘴微笑配闭眼（极度高兴、得意）【喜悦、开心】smiling-with-one-eye-closed：微笑配一只眼闭（狡猾、戏谑）【暗示、轻松】以上作者MR.Gao