与「enable-lens-region-search」相关的搜索结果

Chrome 浏览器右键菜单的“谷歌反向图像搜索”（下图），最近消失了，被 Google Lens 取代。这个新功能一点作用也没有，下面这篇文章教你怎么关闭它，恢复原来的反向搜索。 简单说，就是访问这个设置： chrome://flags/#enable-lens-region-search#

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?

🚨 SCIENTISTS JUST CREATED ULTRA-COMPACT LENSES THAT COULD SHRINK CAMERAS DRAMATICALLY. Researchers have developed wafer-level meta-aspheric lenses that combine traditional curved lenses with flat metalenses. The result is a lens system that is only 3.39 mm thick but delivers wide field-of-view near-infrared imaging something that normally requires much bulkier optics. Why this matters: • Current high-performance NIR cameras are still relatively large and expensive • These new lenses can be manufactured at wafer scale (mass production) • They achieve high image quality in a volume of just 0.02 cm³ • Could enable much smaller, cheaper sensors for phones, drones, medical devices, and AR/VR The deeper implication is practical: We are entering an era where powerful imaging systems no longer need to be bulky. This kind of compact, high-performance optics could accelerate everything from better night-vision in phones to smaller medical imaging tools and more advanced autonomous systems. What do you think which device would you most like to see get dramatically smaller thanks to better optics? Follow for more frontier materials science and future technology.

🚀 The full DeepSeek App experience, now via API Search, files, links, safety, and voice. The capabilities behind the DeepSeek App are now available through the DeepSeek API. Enable built-in features with a few parameters, or call standalone APIs such as OCR, ASR, and TTS. Build richer conversations or recreate the full DeepSeek App in your own application. Try our open-source frontend demo, with support for importing DeepSeek conversation history. 🔗 Demo: 📦 Code: 📖 Details: 1/4

对，这是 Claude Code 自己的规则：ANTHROPIC_BASE_URL 不是官方地址时，它默认关掉 tool search，MCP 工具就全部直接发出去。可以在 ~/.claude/settings.json 的 env 里加 "ENABLE_TOOL_SEARCH": "true" 打开。magpie 的网关已经支持 ToolSearch 的 tool_reference，Claude 订阅、Codex、Grok 的模型都试过能用

The goal is to enable researchers and public health officials to complement existing health information, bridge reporting gaps, and address health challenges proactively. Learn more about our latest research ↓

Halloween Mode now rolling out 🎃 This spooky update turns your Tesla into a haunted house on wheels – Ghost costume on your car's avatar – Enable Trick or Treat to play spooky sounds & flicker the lights when visitors approach – New haunting light show, wraps & lock sound – A rather chilling Photobooth – Frighten people remotely by speaking through the app...your car will say it in a voice of its own Side effects may include neighborhood notoriety

JUST IN: Human Rights Foundation's Christian Keroles says they've leaned into freedom technology like Bitcoin to "enable activists in the fight for freedom" 👀 "A lot of the activists that we support in the organizations they operate, are operating under adversarial conditions."

Day 2.1/ We have made Auto-review free for all users signed in through a ChatGPT account. You can enable it in settings > permissions > auto-review. Auto-review improves upon the default sandbox setting that requires you to approve everything, which is prone to decision fatigue unless you spend a lot of time configuring specific rules. It allows you to run long tasks while having a second agent review all actions taken by the primary agent. Its only goal is to prevent high-risk actions from being taken and to protect against unwanted actions that are not aligned with the original user intent. This Auto-review feature is now free and does not draw usage from your plan.

Seven switches stand between a stock token and a loan. The $PLEDGE desk makes you flip each one yourself. Film M follows a single example, 100 NVDAc, from raw value to a repaid loan: 1. Connect: reads your account and sends nothing 2. Approve: an exact-amount approval, never a blank check 3. Supply: its own review, then your confirm 4. Enable: collateral switched on in a separate review 5. Borrow: debt, health and fee shown before your wallet opens 6. Repay: an approval alone does not repay 7. Read back: the mined transaction is checked and your position is refreshed Before switch 1, the desk does the math in the open. 100 NVDAc is about $23,481 (oracle price times the token-to-share multiplier, on two separate clocks). A 70% factor makes a 16,438 USDC theoretical limit, caps and liquidity shrink it to real room, and choosing half lands at about 8,219 USDC. That costs 6.58 USDC a month at 0.96%, starts at health 2.00, and a simplified 50% price fall takes health to 1. $PLEDGE lives on Robinhood Chain. The loans run on Base. Holding $PLEDGE is not collateral, not a fee entitlement and not loan eligibility. Built on Aave V4 data. If their value falls too far, Aave can sell your tokens. The loan still needs to be repaid. Illustrative walkthrough of the shipped UI, nothing signed or sent. Eligible users outside the US only. @aave @PledgeDesk @ponsdotfamily @coinbase CA:0xbCeFDAB9Ea24a16ca6F993A36f74Da17c63B8C3A Trade only the contract posted from this account.