与「ORANGE_TAXI_CLUB」相关的搜索结果

[📢] Check out our track “SPOTLIGHT” on The Global Chart Show w/ @BrookeReese on @AppleMusic. September 4 (Thu) 3PM PT / 6PM ET Listen here: #ATEEZ# #에이티즈# #YUNHO# #윤호# #ORANGE_TAXI_CLUB# #SPOTLIGHT#

[📢] 'SPOTLIGHT' was added to the Korean Drama Hits playlist on @AppleMusic Listen now on Apple Music! 🎧 #ATEEZ# #에이티즈# #YUNHO# #윤호# #ORANGE_TAXI_CLUB# #SPOTLIGHT#

[📢] Check out ‘SPOTLIGHT’ in Spatial Audio on Apple Music Experience 'SPOTLIGHT' all around in #SpatialAudio# with #DolbyAtmos# @AppleMusic 🔗 #ATEEZ# #에이티즈# #YUNHO# #윤호# #ORANGE_TAXI_CLUB# #SPOTLIGHT#

[📢] SPOTLIGHT - ORANGE TAXI CLUB [Back! Stage OST] 에이티즈 윤호가 참여한 Back! Stage OST 'SPOTLIGHT'가 Apple Music을 통해 선공개되었습니다. 에이티니의 많은 관심과 사랑 부탁드립니다🥰 🔗 #ATEEZ# #에이티즈# #YUNHO# #윤호# #ORANGE_TAXI_CLUB# #SPOTLIGHT#

Bro actually walked away from an active trade mid-round just to sit there and peel an orange, Peak unbothered energy for the Grand Final on Nov 14. Trade on Phantom and use code PHANTOM for 10% off. @solana @phantom #phantom# #solana# #frontiertraders# #trading# #crypto# NFA · DYOR

255M views on a 3D Short by Zack D. Films i tried to rebuild his style with ONE Claude prompt, then ran it on Opus 5.5 and Fable 5.2 (they did NOT make the same Short) the full prompt is below ↓ paste it into Claude Code in an empty folder and answer its 2 questions. it shows u the script and waits for ur go. u need Blender + its free MPFB add-on and a graphics card. give it a few hours (the prompt is minus one optional paid-voice line) Ask me 2 things, then wait: 1. The story in one line: a strange TRUE event where one person did one odd physical thing ("He tied 42 weather balloons to a lawn chair."). If I say "you pick", pitch 3 with one source link each and take the first unless I choose. 2. The voice. Default: Kokoro (free, runs on my computer), a calm, warm male narrator. Then tell me everything else is free: Blender (find my install, or tell me the one download), its free MPFB extension for human bodies (ask me before you install it) and into this folder a Python venv with FFmpeg (imageio-ffmpeg), kokoro-onnx + its model files (kokoro-v1.0.onnx and voices-v1.0.bin from the kokoro-onnx GitHub releases), faster-whisper (small.en), numpy and Pillow. It needs no API key or account and renders on my graphics card with EEVEE. The look: a clean, realistic 3D world, like a good game cutscene. Bright, saturated, a little filmic. - People: realistic bodies with generic faces and big readable expressions (shock, a smirk, a scream). Plain clothes, no logos. Never a real person's likeness: for a real person keep the face out of close-ups (hands, back, side, distance, straight top-down). - CALM shots only. Bodies in fast action or contact (running, jumping, fighting, falling) look stiff, so tell the story with frozen moments under a slowly moving camera, macro inserts of hands and objects, rooms, vehicles, the sky, top-down views and the aftermath. - One new picture for every caption chunk (2-4 words, about 1-1.5 s): a new framing, a new action or a camera move. Nothing ever holds still: every shot drifts, pushes in or orbits. - The shot kit: macro insert (extreme close-up of the key object or hands, very shallow depth of field), hero low angle (wide lens at waist height), god's-eye top-down with a slow rotate, tracked object, over the shoulder, smash zoom on the word that matters, whip pan between beats, glow highlight (the named object glows orange with a rim, then fades), a big 3D number lying in the scene, a thought bubble (a cloud ring showing what he hoped for), a TV in the scene replaying the event. - Light: a bright warm sun, blue sky with clouds, soft shadows. Night scenes use hard lamps and a dark sky. Wide lens up close, depth of field on every shot, motion blur on every fast camera move. - Captions: 2-4 words at a time, white bold rounded sans, about 64 px on a 1080 px-wide frame, centred, 78% down the frame, soft dark shadow, no box. Each chunk replaces the last on the same frame as its picture. - Banned: real footage, photos, downloaded textures or 3D models, logos, AI images or AI video, downloaded music, gore. 38-50 s, 100-140 words, 150-180 words a minute. The voice starts at 0.0 s. - Line 1: the most surprising physical act, in past tense, opening with "He" (or "She"). No name, date or setup. Frame 1 shows that act. - Then a cause-and-effect chain: every sentence starts with a hinge word (Then, Suddenly, So, Because, But, Later) and is ONE visible action. - The context arrives late, after "You see,". - A reveal: someone looks closer and the story turns. - The last line is the consequence. No call to action, no question. - Names are rare: use one only when it pays off. Title = "He ..." or "The Man Who ...". The cover is the first frame. Save every stage to disk so a crash never costs more than one stage. - sources.md: every fact with its link and the date you read it. Anything you can't verify stays out. - script.json: the lines and the caption chunks cut by hand (2-4 words, one picture each), each chunk with its shot: the set, the camera, what moves. - Kokoro reads the whole script in one take (speed 1.0-1.1) and pauses are squeezed to 0.35 s at most; faster-whisper times every word (pass it a 16 kHz numpy array, not a path); write chunks.json with each chunk's start and end. A picture and its caption switch together on frame round(start*30)+1. - blender/: Python scripts run headless (blender -b -P). makes one .blend with the sets, the cast, the props and every shot baked with a key on every frame. sets EEVEE with ray tracing, the AgX view with the Punchy look, motion blur, depth of field and bloom in the compositor. Bodies come from MPFB or are built by you; clothes, hair, props and sets are built in code. - Stills first: one half-size still per shot as a contact sheet. Look at every tile and fix what's off before any full render. Time one full-size frame and tell me the estimate. - Render 1080x1920 at 30 fps to PNG frames, skipping frames already on disk. - numpy only: a light music bed, a sound on every action (a whoosh on each whip pan, hits, wind, room tone), ducked under the voice, mastered to -14 LUFS on the whole stereo mix. - burn the captions in from chunks.json. Encode out/_9x16.mp4 (1080x1920, 30 fps, TV-range yuv420p) and out/_x_7x8.mp4 (1008x1152, under 10 MB, 2-pass): a crop of the 9:16 frame that keeps the subject and the caption. - Blender paths: pass absolute output paths (a relative one lands on the drive root). - MPFB headless: enable it with addon_utils.enable("bl_ext.user_default.mpfb"). Bake a body's shape keys before you pose it: the rig is fitted to the baked shape. - Clothes: cut them from the body mesh and push them 7-16 mm out along the normals; keep two rings of body faces under every hem. - Nothing coplanar: keep every resting object 1 cm off its neighbour and draw ground markings into the texture, or they flicker. - Hair: EEVEE draws hair only from a Curves object, hair type STRIP. Use a Principled BSDF on it (the Hair BSDF renders black). - Skin: keep subsurface weight near 0.2 (more turns faces black in EEVEE) and add a soft fill light from below under a noon sun. - Hands: a curled hand reads as a claw from the palm side, so shoot a grip from behind the knuckles. - Motion blur: shutter position START, a key on every frame, plus a key half a frame after each shot's last frame, so blur never reaches across a cut. - Check: run a black-frame and one-frame-flicker check on the render. Make a contact sheet (a frame every 0.5 s) and look at every tile: the act reads in the first 2 s, faces are lit, nothing clips through anything, captions stay off faces and key objects. Then step through the first 2 s, the middle and the end frame by frame. Fix, render only the changed shots again. Pitch (or take my story), then show me the script with the word count, the caption chunks with their seconds and the shot list with what the first frame shows. Build nothing until I say go. how the two runs went: one run each on the same PC, so it's one sample, not a ranking. both took under 3 hours on one shared 8 GB graphics card. the story for both: a man who tied 42 weather balloons to a lawn chair in 1982 where they split: -> Opus opened wide on the balloons over the yard. Fable opened on the man kneeling at the chair with his Jeep behind him -> Opus put 5 big 3D numbers in its scenes, Fable 2 -> Fable followed the caption spec (white text, soft shadow). Opus went ALL CAPS with a thick outline -> Fable pulled the Smithsonian's own record and ended on the chair in the museum. Opus ended on the $1,500 fine -> a few Opus shots are hazy and one opens on a blank grey frame save this for ur next Short. who did it better, Opus or Fable?

张婉莹案完整时间线：从北京国际关系学院同学牵线，到 LAX（洛杉矶国际机场）被 FBI 抓捕 2022年9月22日 张婉莹在微信问老同学：“你现在又在哪个部的哪个局工作？” 2024年10月19日 两人参加北京国际关系学院公共管理学院2014届毕业十周年聚会。 2025年3月3日 张询问一个 Irvine（尔湾） 的地址。对方回复：“那件事我们已经弄清楚了，不用麻烦你。” 起诉书称，该地址与一名强烈反中共立场的台湾民选官员有关。 6月9日 老同学告诉张，一名国际关系学院“学长”想认识她，并把她的微信推给对方。 6月10日 “官员2”联系张。张称其为“学长”。 6月27—30日｜长沙 张与“官员2”等人见面，并订下一个10人包厢。 7月7日 “官员2”提到继续谈“上次我们的事”，还说原本想当面“给你一些保证”。 8月21日前后｜杭州 张再次与“官员2”见面，酒店由对方安排。 8月26日｜Los Angeles（洛杉矶） 张告诉对方： “下周大概会去 Seattle（西雅图）。” 对方回复： “好。辛苦了。” 8月29日｜Orange County（橙县）→ Las Vegas（拉斯维加斯） 张与同行者A从 John Wayne Airport（约翰·韦恩机场） 飞往拉斯维加斯。 9月1日｜Las Vegas（拉斯维加斯）→ Seattle（西雅图） 张与同行者A搭乘阿拉斯加航空629号航班前往西雅图。 抵达后，在 Seattle-Tacoma International Airport（西雅图-塔科马国际机场） 租下一辆黑色 2025 Nissan Rogue。 9月1日｜Seattle（西雅图） 两人在目标住宅附近停留、拍摄。 FBI称监视目标是台湾总统赖清德的儿子赖廷与及其家人。 张随后向“官员2”发送： — 两个车牌号码 — 住宅照片/影像 — 一段约16秒的视频 视频中同行者说：“到了，就是这个房子。” 张回答：“对。” 对方收到后回了三个“Strong”表情。 9月1日晚8:42｜西雅图机场 两人归还租车。 从租车到还车，不到7个小时。 9月2日｜Seattle（西雅图）→ LAX（洛杉矶国际机场） 张与同行者返回洛杉矶。 9月8日 张要求同行者把“西雅图照片”传给她： “不要用微信或短信，要用 AirDrop。” 并说：“我得传回去，他今天要我传回去。” 9月11日 “官员2”再次索要房屋照片。 同行者告诉张，照片已经全部删除，连“最近删除”也清空。 10月10—24日 张又与对方讨论一名大型社交媒体网红赴 上海的行程，并表示如果“你们”有兴趣，可以帮忙介绍。 2026年3月9日｜California Central District（加州中区联邦法院） 美国联邦法院签发搜索令。 FBI取得张婉莹及同行者相关的 iCloud 数据。 2026年10月4日｜LAX（洛杉矶国际机场） 张婉莹准备搭飞机前往 Shanghai（上海）。 FBI在机场将她逮捕。 目前她被指控未登记充当中华人民共和国政府代理人，尚未被定罪。 整条线只有一句话： 国关学院同学牵线 → 中国见面 → 西雅图监视赖清德儿子 → 拍住宅和车牌 → AirDrop传资料 → 删除照片 → FBI查iCloud → 飞上海前被抓。

I blocked the lips in a warm red first, then added the gloss with a lighter stroke only on the lower lip. The orange lollipop needed a second layer or it looked flat next to the mouth.