3.5
52 条评分
★★★☆☆
2026年4月6日
2022年9月12日
更新内容
v4.4.6We’ve improved the 2D plan generator to deliver better and more reliable results.
应用信息
- 开发者
- Elie F. Gebran
- 分类
- Productivity
- 价格
- 免费
- 版本
- 4.4.6
- App ID
- 1642347863
简介
RealScan allows you to effortlessly scan an interior space with exceptional accuracy, generating a detailed 3D plan complete with object detection and precise measurements. Editing your plan has never been easier—rearrange layouts, add new furniture, or modify dimensions with just a few taps. Our intuitive interface lets you measure any distance within your plan, ensuring every detail is perfect. Additionally, you can generate 2D floor plans for a comprehensive overview of your space. RealScan also lets you walk through your plan in augmented reality, giving you a realistic sense of the space. For even more customization, you can create a plan from scratch. Once you're satisfied with your design, share your 3D plans in both 3D and AR formats. The shared files can be instantly viewed on Apple devices with a single click, making it easy to showcase your vision. In order to scan, a device with a Lidar sensor is required. In-app purchases are purchased from and billed by Apple iTunes, not RealScan. These purchases are subject to the terms and conditions of Apple iTunes. RealScan does not have access to Apple iTunes accounts or transactions. If you wish to confirm the type of subscription that has been purchased from Apple iTunes, please consult your apple iTunes account or receipt as each subscription will have a unique billing name. Your subscription automatically renews unless auto-renew is turned off at least 24 hours before the end of the current period. You can manage your subscription and switch off auto-renewal by accessing your iTunes & App Store Account Settings after purchase. Privacy Policy and terms & and conditions : https://arvid.app/realscan Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/
下载量预测
预估总下载量
77
低 / 月
116
预估 / 月
231
高 / 月
基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。
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