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视觉剥夺下的姿态维持测试 Pose maintenance test under visual deprivation Model by @Zhishituji Photo by @whiteplace_1
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兄弟们,不得了了,刚才有社群有同学反馈Lovart 里面Seedream 5.0 Pro 可以生成无审查大尺度图片,试了下真的行啊,太离谱了啊,草台班子就是草台班子。 提示词 A cinematic low-angle editorial portrait of an adult East Asian female model seated extremely close to the camera, wearing elegant dark charcoal-gray lingerie. Her legs dominate the extreme foreground, creating dramatic wide-angle foreshortening and powerful near-to-far perspective exaggeration. The closest parts of her legs fall into soft optical defocus and creamy foreground bokeh. Her torso leans backward in a relaxed, self-possessed pose, head slightly tilted, distant tranquil gaze, long dark tousled hair, muted deep-red lips, natural skin texture, subtle visible pores, delicate subsurface scattering, realistic warm skin tones. Behind her is a gigantic seamless full-color semi-realistic anime mural covering the entire wall. The mural depicts an extremely dense ensemble of numerous clearly adult female characters portrayed as artistic nude figure studies. Dozens of adult anime women are packed tightly together in one continuous wall-to-wall composition, with overlapping bodies, intertwined silhouettes, flowing hair, shoulders, backs, waists, hips, arms, and legs forming a complex organic visual rhythm. The illustrated women have sophisticated semi-realistic anime anatomy, mature adult facial features, elegant body proportions, natural anatomical structure, refined facial rendering, expressive eyes, detailed hair, painterly skin shading, and subtle cel-shaded contours. Their poses feel calm, sculptural, and editorial rather than erotic. Hair, hands, arms, overlapping bodies, cropped framing, fabric fragments, and deep shadows naturally obscure explicit anatomical details, creating tasteful fine-art nudity without graphic sexual emphasis. Several large central anime women dominate the mural, surrounded by dozens of smaller partially cropped female figures at different scales. Faces and bodies overlap densely, with characters extending beyond every edge of the frame. Almost no empty negative space. The mural must feel like one enormous continuous group illustration, not separate portraits, not a collage, and not comic panels. The mural is richly colored with a sophisticated cinematic palette: warm ivory, peach, soft rose, muted coral, amber, burgundy, plum, desaturated teal, cobalt blue, smoky violet, and deep crimson. Illustrated skin tones vary naturally across the crowd, enhanced by painterly gradients, soft reflected light, luminous highlights, translucent shadow colors, and refined anime-style subsurface glow. Dark hair masses interlock with pale and warm-colored bodies, producing a dense chromatic tapestry. The background combines premium Japanese anime aesthetics with semi-realistic digital painting, mature seinen illustration, fine-art figure drawing, elegant editorial anatomy studies, painterly cel shading, clean controlled linework, realistic volumetric lighting, and highly detailed facial rendering. It should feel like a monumental museum-scale anime fresco rather than a printed poster. A hard directional spotlight shines from the upper right, producing intense chiaroscuro, sharp rim lighting, and a clearly defined cast shadow of the real model falling across multiple illustrated nude figures. The shadow follows the contours of the mural, visually embedding the physical model inside the illustrated female crowd. Strong contrast between warm photographic skin and the richly colored painted bodies behind her. The live-action model remains unmistakably photographic, while the mural remains unmistakably illustrated. Dramatic scale contrast, surreal integration of physical reality and anime art, tactile human skin against painted digital bodies, sophisticated fashion editorial atmosphere, visually striking but tasteful, cinematic and psychologically distant rather than overtly erotic. Shot with a 24mm wide-angle lens from an extremely low camera position, slight Dutch angle, shallow depth of field, exaggerated foreground perspective, realistic lens distortion, foreground bokeh, subtle cinematic film grain, restrained chromatic aberration, natural optical vignette, high dynamic range, dramatic cinematic color grading, surreal editorial photography, highly detailed, photographically believable lighting. single continuous mural, seamless female ensemble illustration, full-color semi-realistic anime artwork, clearly adult women only, tasteful artistic nudity, mature figure studies, elegant anatomy, dense overlapping composition, no comic panels, no collage, no gutters, no speech bubbles, no empty background, no monochrome artwork --ar 3:4 --style raw
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WARNING: Visual Trap. 我突然想,是不是每一次靠近, 都带着一点不该有的温度。 你刚好看见了
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感觉adobe font visual search 识别准确度比另外几个同类服务高不少
DeepSeek 多模态大语言模型的论文《Thinking with Visual Primitives》已经公开 底座是 DeepSeek-V4-Flash,MoE架构,总参数量 284B,激活参数量 13B。 自研 DeepSeek‑ViT 视觉编码模型,14×14 patch,输出后 3×3 空间压缩,再接入 LLM。 模型在回答时不仅进行文字推理,还会同时通过画框、打点等“视觉原语”进行思考。 在极低的 Token 成本下,其效果能和 GPT-5.4、Claude 以及 Gemini 在一些前沿指标上对齐,甚至有的指标能反超。
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奔赴只为赶一场云海视觉盛宴——湘西八面山# 云端秘境Rushing only for a visual feast of the sea of clouds - Xiangxi Bamianshan # Cloud Secret Realm
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让小模型看一张图回答一串选择题,常见做法是让它输出 JSON,可问题一多格式就开始出错,代码那头直接解析失败。 jev-visual 换了个思路,参考 TypeSafe 家 Jev 的做法,不让模型生成文字,而是给每个候选答案直接打分,挑分最高的那个。 它是个在 Apple 芯片 Mac 上跑的学习项目,模型用 0.8B 的 Qwen3.5。同一张图一次能问 1 到 64 个问题,选项题、是非题、分等级打分都行。 图片和上下文只算一遍,各个问题共用。作者在 M4 上测了 64 个问题,每个问题单独算要 37.30 秒,共用之后 2.40 秒。 GitHub: 仓库里带了三个小游戏演示,传送带分拣、打砖块、用摄像头手势控制粒子。 打砖块那个挺实在,小模型盯不住球,作者干脆把画面分成五块,只问球在哪一块。 首次运行要下载大约 600 MB 的模型,之后全在本地跑,有网页界面、命令行和接口三种用法,还配了中文说明。 想弄明白视觉模型推理每一步在干什么,照着 README 给的阅读顺序看代码,会顺很多。
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「我覺得我現在就#%*^… 」 「我現在又%*#¥…」# 漢:妳講話都語無倫次了欸,妳現在怎樣? (拔出,噴射式潮吹) Witness the audible/visual wonder of projectile squirting. @chuchu_1118 訂閱即可看 Subscribe to watch Onlyfans 沒有上,因為牽涉體液 Not available on Onlyfans due to bodily fluid #JustAnotherTuesday# #又是個週二#
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一行代码直接把 Python 数据分析的入门门槛给铲平了。 这就是刚在 GitHub 炸场的 PyGWalker(PyGWalker: Turn your dataframe into an interactive UI for visual analysis)。它是一个开源数据可视化与分析工具,能把原本死板的 Pandas DataFrame 瞬间变成像 Tableau 一样拖拽式的交互界面。 GitHub 星标目前已斩获 13k+ Stars,采用 Apache-2.0 开源协议,完全免费且支持本地部署。 它的核心爽点极其干脆: 零门槛拖拽:不需要写复杂的 Chart 代码,鼠标拖一拖就能出高大上的图表。 一行代码启动:只要输入 pyg.walk(df),交互界面直接在 Jupyter / Streamlit 里弹出。 数据不出本地:所有分析计算都在你本地环境跑,隐私安全直接拉满。 无缝集成工作流:完美兼容 Jupyter Notebook、Jupyter Lab 以及 Streamlit applications。 说白了,以前要折腾半小时的图表排版,现在 3 秒钟拖完,这效率提升完全是降维打击。 🔗 项目地址:
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UI/UX 到底应该怎么参考和学习优秀设计?很多新手一上来就只会刷 Dribbble,最后做出来的东西很好看,但根本不好用。 设计参考其实分成两类: 1. 视觉参考 Visual Reference Behance、Dribbble、Cosmos、Pinterest 2. 逻辑参考 Logic Reference Mobbin、Refero、GoodUX、Growth Design 视觉负责产品的情绪表达、品牌质感和用户连接;逻辑负责使用流程、交互效率和易用性。好的产品设计,两者缺一不可,有些网站也会同时兼顾视觉和逻辑,不需要分得特别死。 如果产品已经确定了 Branding,就不用继续到处找视觉风格了,把精力放在 UI 细节、交互体验和使用流程上。 尤其是 AI 时代,做出一个漂亮页面越来越简单,真正拉开差距的是:它到底好不好用。
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