与「gpt_image_2」相关的搜索结果

有人用GPT-5.6 Sol和Codex开发了一个完全交互式的3D人体解剖应用， 仅从一张设计图开始。 GPT Image 2.0生成了设计图。 每个器官图像都由它生成， 通过Tripo AI转换为3D模型。 Codex利用这些模型、主提示词和设计图， 构建了第一个版本。 模型最初各150MB， 运行速度仅16fps。 Codex优化了所有内容， 将每个模型缩小到2-5.5MB， 总资源从900MB减至28.6MB， 同时保持视觉质量完整。 Codex还生成了解剖插图， 标注每个器官位置， 创建了交互热点标记， 解释每个器官的不同部分。 现已上线且完全开源。

这位法国 AI 选手 Jeanviet 用 Claude 完成他 80% 的 Youtube 视频制作，果然大家都在设计内容工厂 AI Agent 要不是我把 Claude Token 烧光了，高低把转录好的视频放上来，现就将就着看文字版咯 jeanviet (Romain) 的 YouTube 自动化流水线 视频 URL: 核心步骤拆解 1. 输入脚本/URL — 把视频脚本文本或 YouTube URL 粘贴进自建工具"YouTube Rod"，作为整条流水线的起点。 2. Claude 生成标题 — Claude CLI（一次生成 10 个标题候选，每个附带 CTR 评分和选择理由，挑一个最强的。 3. 关键词→参考缩略图 — 选定标题后 Claude 自动输出关键词，用这些关键词搜出大量高点击率的参考缩略图供灵感选择。 4. AI 批量生成缩略图 — 选一张参考图后，用 GPT Image 2（通过 Replicate）生成 5+1 张变体：第一张忠实还原参考，后五张做创意发散。 5. Photoshop 精修 — 把 AI 缩略图拉进 Photoshop，用生成式填充调尺寸，抠出人物加曝光/对比度/锐度让脸部更突出，最终定稿。 6. 生成描述/标签/章节 — Claude 根据脚本自动生成视频描述、合作伙伴模板、章节标记和 500 字符内的 SEO 标签，直接复制粘贴到 YouTube 后台。 7. 一键触发全平台分发 — 点击"发布 + 创建 Lead Magnet"，系统自动生成 Instagram Story、LinkedIn 帖子、Twitter 推文、Skool 社群帖，全部从一个 URL 出发。 8. Shorts 自动工厂 — 通过 Opus Clip 自动从长视频中裁出多条短视频，顶部加 hook 文字 + CTA（评论关键词即送完整视频链接）。 9. DM 自动回复 — 用户在任何平台评论关键词（如"short"），ManyChat 自动私信发送对应视频链接，跨平台打通。 10. 周报 Newsletter 自动生成 — 每周三自动生成一期 Newsletter，以最新 YouTube 视频为核心内容，推送给邮件订阅用户。 11. YouTube 选题雷达 — 每日自动爬取 241 个同赛道频道，计算每条视频的"病毒系数"（如播放量 vs 日常均值 ×25），筛出爆款供选题参考。 12. Claude CLI 批量出脚本 — 基于选题雷达的结果，Claude 直接在 CLI 中批量产出适配自己风格的脚本和 SEO 长青选题（如"什么是 vibe coding"）。

最近观察到很多同行搞批量生图的成本失控问题 (包括电商、产品图、AI漫剧分镜等） 我们提出了一个切实的解决方案： 降价！ 现在GPT-Image-2 的 API 在 ToAPIs更新了价格： 1K 只要约 $0.015 / 张 统一base URL接口，换模型不用改代码。 适合电商主图、广告素材、批量出图。 免费额度先试：👇

Only if education could be this interactive ❤️‍🔥 I've had a looong wish to build something genuinely useful through vibe coding, and I finally did it. A 3D human anatomy application built with @threejs using GPT 5.6 Sol. It all started with a single design image that I created using GPT Image 2.0. I then used it to generate every 3D organ image, one by one. Next, I converted each of those images into 3D models using @tripoai (and no, they didn't sponsor this 😄). After that, I opened Codex, wrote a master prompt based on the design, and gave it the prompt, the design image, and all the 3D models. Codex built the first version beautifully, but there was one big problem. Every single 3D model was nearly 120-150 MB. That obviously wasn't practical for the web and was giving a performance of 16fps. After a few iterations, Codex optimized each model down to roughly 2–5.5 MB while preserving the visual quality, reducing the total asset size from ~900 MB to just 28.6 MB. And each model loads on demand. Along the way, Codex also generated those anatomical illustrations showing where each organ sits in the human body, and even created the interactive hotspot markers that explain different parts of every organ. It handled all of that. The process wasn't exactly one shot, but it also wasn't difficult. You just have to do it step by step. It genuinely felt like building something that could make learning anatomy much more engaging. The inspiration came from @DilumSanjaya's 3D animal plant cell project. I remember seeing it and thinking, "I want to build something like this one day." And I did it :D Live: Code:

Codepilot 0.63.0 版本更新 现在可以将你用 AI 生成的任何内容加入素材库了 比如 Codex 里用 GPT- Image 2.0 生成的图片和 AI 生成的 HTML 都可以加入素材库了，还能给素材打标签 同时适配了 Deepseek V4 Flash 0731，增加了可选的推理强度

已经完成了，一键榨取任意图片中的信息，进行高保真还原。让GPT Image 2性能拉满的反推方案「GPT通用特调」已经内置到我的插件中。 26日起，「照样拍」插件不再是人像反推插件，而是进化成了通用图像反推插件，兼容海报、摄影、二次元、商品图等多种类型图像，正在努力做到给所有需要反推的人群服务。 此外，针对Z Image Turbo和Nano Banana的反推方案今天已经完成了一部分，预计明天就可以向大家展示！ 多并行反推+生图也已经在计划中了，以后可以做到批量反推+批量生图/多角度宫格图，让插件进化成生产力工具。

GPT image 2 on chatgpt Prompt: Use the uploaded character reference image as the strict identity and outfit reference. Preserve the reference character’s: - face identity - facial proportions - eye shape - nose - lips - skin tone - hairstyle - hair color - visible hair accessories - overall recognizable vibe - outfit and styling shown in the reference image Do not hardcode any specific character traits that are not present in the uploaded reference. All identity, hairstyle, accessories, and clothing details must be inferred directly from the uploaded reference image. Create a high-quality mixed-style vertical portrait showing: 1. a realistic full-body version of the uploaded character/person 2. a black hand-drawn doodle-shadow version of the same character/person on the wall beside them Core concept: The real person and their doodle-shadow are doing a playful mischievous pose together. The real person performs a cute realistic version of the pose, while the doodle-shadow performs a much more exaggerated, chaotic, cartoonish version of the same pose idea. The mood should feel cute, playful, mischievous, stylish, funny, and social-media-friendly. Real person: - Must remain realistic and photogenic - Must wear the same outfit style and key visible details from the uploaded reference image - Do not replace the reference styling with unrelated fashion - Expression should be cute, slightly confused, mildly embarrassed, playful, as if thinking: “Why am I doing this with my shadow?” - The real person should not stand stiffly - The real person should actively participate in the pose, but in a natural realistic way Doodle-shadow: - Must be a black hand-drawn sketch version of the same person, drawn directly on the wall - Not a realistic second person - Not a normal physical shadow - Not a full-color anime character - Black sketch line-art only - Should resemble the person through hairstyle silhouette, accessories, outfit silhouette, and pose structure - The doodle-shadow should look more energetic, sillier, and more chaotic than the real person - Add manga-like motion lines, hearts, stars, sparkles, and comic marks around the doodle if helpful Random mischievous pose rule: The pose must NOT be fixed. For each generation, invent a new playful mischievous pose for both the real person and the doodle-shadow. The real person and the doodle-shadow should share the same general pose idea, but they do not need to match perfectly. The real person performs a cute realistic version. The doodle-shadow performs a much more exaggerated, chaotic, cartoonish version. Do not repeatedly use pointing poses. Do not repeatedly use finger-gun poses. Do not repeatedly use the same standing pose. Do not always make both figures simply point at each other. Create a different mischievous pose each time. Possible pose directions are loose inspiration only, not a fixed menu: - playful idol pose - silly dance pose - leaning sideways with one arm curved overhead - making a big heart pose - cheeky wink pose - hands near cheeks in a cute teasing pose - exaggerated “ta-da!” pose - mock surprise pose - playful running-in-place pose - mischievous tiptoe pose - arms stretched in opposite directions - pretending to sneak away - cute troublemaker pose - dramatic overreaction pose - goofy victory pose - playful balance pose - playful peekaboo pose - shy but mischievous pose - cute overconfident pose The final pose should feel fresh, cute, mischievous, and slightly chaotic. The real person should look like they are reluctantly playing along. The doodle-shadow should look like it is having way too much fun. Composition: - vertical 4:5 or 9:16 - show the real person in full-body or nearly full-body framing - place the real person on one side of the frame - place the black doodle-shadow on a clean wall beside them - the doodle-shadow should be roughly the same height or slightly taller - keep enough space around both figures so the full pose is visible - the connection between the real person and the doodle-shadow must be clear at a glance Background: - simple clean indoor studio wall or minimal room corner - white, cream, or pale gray wall - clean floor - soft natural sunlight patch or gentle wall shadow allowed - keep the background uncluttered Lighting: - soft natural studio lighting - bright, clean, polished, playful mood - keep the real person’s face clearly visible Style quality: - realistic human photography - black hand-drawn doodle-shadow on wall - matching mischievous pose interaction - strong identity resemblance - outfit and styling faithfully based on the uploaded reference - cute and stylish mixed-media portrait - clean composition - social-media-friendly - no obvious AI artifacts Negative prompt: hardcoded blue hair when not in reference, hardcoded cloud clip when not in reference, hardcoded fish clip when not in reference, hardcoded school uniform when not in reference, outfit change unrelated to reference, realistic second person, normal reflection, normal shadow only, solid black monster shadow, horror shadow, creepy shadow, full-color illustration, cartoon human, anime human, weak resemblance, unrelated sketch character, messy wall, cluttered background, repeated pointing pose, repeated finger-gun pose, same pose every time, fixed pose, boring mirrored pose, stiff pose, identical pose repetition, real person not matching shadow pose, text, watermark, logo, distorted body, extra limbs, extra fingers, bad hands

“周末打打街头篮球” GPT Image 2生成「柔光CCD风」×「夕阳篮球场生活照」。 - 旧看台和铁网负责青春记忆，夕阳负责给画面加一层温度；篮球只是让人物和场景产生联系，不需要摆出专业运动姿势。 - 高马尾轻轻甩动，一只手抱球，另一只手随意搭在栏杆上，再配合柔闪提亮，整张图就会像朋友路过场边时突然按下快门。 提示词： 摄影风格：柔光CCD风 写真方向：运动生活照 场景方向：旧式篮球场看台 / 场边铁网 / 夕阳球场 服装方向：修身短背心 + 百褶短裙 / 运动短裙 + 球鞋 气质标签：阳光、健康、元气、亲近、轻快、自信 五官方向：运动元气脸 五官细节：圆杏眼，卧蚕自然，眼神发亮，平眉舒展，笑容明亮，整体有健康感 发型方向：高马尾 发型细节：高马尾蓬松，发尾自然甩动，碎发轻微飞扬 身形方向：丰腴自然曲线 线条强调：中偏强 镜头方向：半身到大腿 姿态动作：一只手抱着篮球，另一只手自然扶在腰侧或看台栏杆上，笑着看向镜头 光线氛围：夕阳自然光 + 柔闪 滤镜效果：奶白高光 + 清透生活照色彩 + 轻颗粒 + 轻微过曝 画幅比例：9:16 补充要求：像球场边被CCD相机抓拍的一帧，人物健康、元气、曲线自然，不要过度竞技感

Made a game character selection screen with GPT-5.6 Sol Started with a few character images generated with GPT Image 2 Then asked GPT-5.6 to design a polished game character screen around them Here's what it came up with