https://dailypypy.org/tags/%E5%9C%96%E7%89%87%E8%A7%A3%E6%9E%90%E5%BA%A6/ Recent content in 圖片解析度 on 每日拍拍 Hugo -- gohugo.io zh-tw © 2026 每日拍拍 Fri, 23 Oct 2026 10:35:00 +0800 155076163427069952 154825760438254592 https://dailypypy.org/learn/mlx-vlm-resolution-benchmarks/ Fri, 23 Oct 2026 10:35:00 +0800 https://dailypypy.org/learn/mlx-vlm-resolution-benchmarks/ <!--- 1440x768 prompt: masterpiece, best quality, highres, clean anime illustration, japanese anime style, soft shading, flat color design, 1girl, black hair, green eyes, white off-shoulder shirt, black short skirt, side profile upper body looking over shoulder, arms folded loosely at waist, calm confident closed-mouth smile, looking at viewer, pastel pale lavender background, neat composition, detailed eyes, cute and smart vibe, minimal background, polished illustration, no text negative prompt: worst quality, bad eye, bad hand, extra limbs, manga, multiple views, monochrome, text, signature dedup note: Controlled spatial-resolution quality/resource follow-up to ../mlx-vlm-image-chat/, not another chat/preprocessing tutorial or minimal eval checklist. Observe actual processor grids and expanded image-token positions; compare fine-text recognition, strict output compliance, first-generation versus warmed calls and MLX allocator peak. ../mlx-vlm-batch-structured-output/ owns schema/batch QA; ../mlx-vlm-pdf-document-extraction/ owns PDF/OCR provenance. 199-post inventory and nearest sources reviewed before drafting. publication note: Required randomized display date retained; publishDate permits the morning release with buildFuture=false. verification: 30 formal real-model calls (3 budgets, 3 synthetic fixtures, 3 warm rounds plus first-generation); 15 checks passed, including scoring, exact article/executable identity, fixture hashes, processor token counts and timing contracts. Cover prompt 30805f26-434e-4a50-9aa4-94c6d011c274 produced DAILYPYPY_00144_.png; PNG 1440x768 verified and visually inspected. ---> <h2 class="relative group">一. 前言：圖片放大，模型就會看得更清楚嗎？ <div id="一-前言圖片放大模型就會看得更清楚嗎" class="anchor"></div> <span class="absolute top-0 w-6 transition-opacity opacity-0 ltr:-left-6 rtl:-right-6 not-prose group-hover:opacity-100"> <a class="group-hover:text-primary-300 dark:group-hover:text-neutral-700" style="text-decoration-line: none !important;" href="#%e4%b8%80-%e5%89%8d%e8%a8%80%e5%9c%96%e7%89%87%e6%94%be%e5%a4%a7%e6%a8%a1%e5%9e%8b%e5%b0%b1%e6%9c%83%e7%9c%8b%e5%be%97%e6%9b%b4%e6%b8%85%e6%a5%9a%e5%97%8e" aria-label="定位點">#</a> </span> </h2> <p>同一張截圖，224 像素看不清的小字，換成 896 像素就一定能讀對嗎？ 拍拍君今天不靠「感覺比較清楚」回答，而是做一個可以重跑的小實驗。</p>