
Image Pipeline — Batch Image Processing
在浏览器中本地批量调整、裁剪、压缩和转换图像。
@MaximMitenkov · X
🔒 Just launched Image Pipeline — batch image processing in your browser. 100% private. No signup. Pay once, use forever. #buildinpublic #webdev #privacy
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在浏览器中本地批量调整、裁剪、压缩和转换图像。
@MaximMitenkov · X
🔒 Just launched Image Pipeline — batch image processing in your browser. 100% private. No signup. Pay once, use forever. #buildinpublic #webdev #privacy

在浏览器中将文字和图片转换成 HD AI 视频,无需安装。
seedance 2.0 mini — 浏览器直出 AI 视频,文字/图片/音频多模态输入,30 秒内生成 HD 短片,无需安装

多语言代码学习助手,可在浏览器中直接编写和执行代码。
@francis7_a · X
Building - learning tools for devs and student. happy to connect.

用AI生成定制乐高设计和小人偶,支持文本、照片和动画。
Brick Center — 如果您是一位乐高爱好者,热衷与创造各种乐高形象,BrickCenter 可以将您的创意,自动生成乐高设计图。AI 乐高生成器可以将你的文字转换成定制的乐高套装。轻松地从照片创建你自己的小人偶,如果您觉得乐高头像很酷,也可以将您的自拍图片,生成乐高头像。还可以来网站浏览由爱好者精心制作的独一无二的乐高作品 - [更多介绍](https://www.bilibili.co

通过设置一个已知参考尺寸来测量照片中的物体。
@Laxman101058405 · X
A few days ago I needed to measure something from a photo. Instead of searching for the perfect tool, I thought: "Why not build it?" So over the next 2 days, I built a Photo Measurement Tool using Cursor. If you try it, I'd love to know what you think.


压缩提示词并检测重复工具调用,降低LLM代币成本
@DeveloperL92487 · X
I built my first app in 60min And now I got $500 MRR in one month Check here if you are interested It’s a tool to reduce agent token consumption, speed up agent response, and clean up memory cache

为 AI 代理提供跨 Claude Code、Cursor 等 MCP 应用的持久化内存系统。
FabianBeiner · HN
CMEM – Persistent Memory for AI Coding Agents

上传照片生成可自定义的 AI 手办收藏模型。
AI miniatur — 将照片转换为 AI 手办模型

保存和组织工作会话,用AI记忆即时检索任何工作。
@vitverb · X
hi :) One tap back to the work you meant to finish. No tasks to manage. Nothing to set up. Local-first

浏览和管理50,000+个AI提示词库,优化工作流程。
@iPranayJoshi · X
Would be honoured to come join! Built talk about vibe coding at

由AI驱动的代码审查工具,在microVM中运行代码来捕获更多错误。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db