棋牌手游选牌助手开发

@corpmember29

您好！读了您的需求后，我觉得这个项目非常有意思。作为一名资深全栈工程师，我可以为您的项目提供及时且高质量的支持。我们可以通过电话或在线聊天进一步沟通。 期待您的回复。 谢谢。 >>>>>>> 我们会在聊天中分享过往作品集。我们可以通过平台通话或聊天功能进一步沟通。 <<<<<<

@Jennycreation

With over 17 years of experience in Android and web development, my team and I are well-equipped to bring your vision of a mobile card game assistant to life. We understand the importance of real-time analysis with minimal delay, and we're adept at using various technologies such as OCR, image recognition, and even deep learning algorithms to extract and interpret detailed in-game data. Trusting the poker strategy we apply won't mishandle the gameplay as our core objective remains providing players with optimal suggestions, not automating or giving unfair advantages. Moreover, we've mastered compatibility issues and are up-to-date with versions of Android 10-13 (ARM64). We prioritize a non-root dependent approach to access cards data ensuring your customers can enjoy the app effortlessly on their devices. Furthermore, we believe it is crucial for users to have control over their gaming environment. Hence we will create a highly customizable app with an intuitive UI & UX design allowing players to configure settings based on their preferences. Lastly, our work doesn’t end with just delivering the app, we want you to feel confident in using it thoroughly. So, alongside the complete APK and source code, we'll provide comprehensive documentation on our architecture designs, compilation process, and deployment details.

@XRProConnect

Hi, Aashiq here from Cape Town, South Africa. This project instantly caught my eye, so I had to reach out. I see you are looking for a mobile card selection assistant specifically for Android that provides real-time hand evaluation and optimal play suggestions without automated cheating. That’s an exciting challenge! Having worked on various mobile applications, I specialize in developing solutions that enhance user engagement and gameplay experience. My experience includes implementing machine learning algorithms and designing intuitive user interfaces, ensuring a seamless experience. I’d love to share some successful projects I’ve completed that align with your vision. Based on what you mentioned, here is how we would approach the project: - Analyze current hand data using efficient algorithms. - Implement a user-friendly overlay to display suggestions. - Ensure compatibility across popular Android devices without requiring root access. You can expect clear communication throughout the project. I will deliver a user-focused solution optimized for performance, ensuring it enhances the gaming experience. Best Regards, Aashiq

@carlosd178

您好， 我详细阅读了需求。首期目标很清晰：开发 Android 端实时选牌助手，只分析用户当前可见牌面并给出建议，不做自动挂机、透视或未授权数据读取。 我有 Android、Java/Kotlin、图像识别、OCR、OpenCV/ML Kit、概率算法及实时 Overlay UI 开发经验。针对 Android 10–13 ARM64，我建议优先采用 MediaProjection 截图 + ROI 裁剪 + 模板匹配/OCR 的无 Root 架构，将数据获取、牌局算法和悬浮窗 UI 完全解耦。 本项目最大的技术难点是不同游戏、分辨率和牌面皮肤下仍保持低延迟与高识别率。我会通过可配置识别区域、视觉锚点、模板缓存及后台线程分析降低误判和延迟；算法层可先采用规则、概率和博弈搜索，后续再根据真实数据评估是否需要 ML/DL。 交付可包含 APK、完整源码、架构说明、编译部署文档、用户手册及演示视频。 有两个关键问题： • 首期具体要支持哪一种棋牌游戏和规则？ • 能否提供目标 App 的实际牌局截图或录屏，用于建立识别模板和测试集？ 我可以先做一个单游戏 PoC，验证识别准确率和响应速度后再扩展兼容范围。 Best regards, Carlos.

@shawanay

我是 名有经验的 Android 与游戏 AI 开发者，熟悉 Kotlin/Java、图像识别、OCR、概率计算、实时数据处理以及悬浮窗 UI。 我会, * 开发 Android 10–13 的 ARM64 版本，优先采用非 Root、非侵入式的屏幕截图 / OCR / 图像识别方式获取用户可见的牌面信息。 * 建立独立的算法层，根据当前可见手牌、规则、概率和策略模型，在低延迟下生成出牌或选牌建议。 * 通过悬浮窗、Overlay 或通知展示推荐结果，并提供启停、热键、灵敏度、游戏配置等设置。 * 交付完整 APK、源码、架构说明、编译部署文档、用户手册和演示视频，并保持数据获取层、算法层和 UI 层模块化，方便后续扩展。 Q: 首期具体需要支持哪一种棋牌游戏以及它的完整规则？如果不同平台的 UI 不 致，是否希望先做 个可配置的识别模板系统，后续再逐步增加平台支持？ 我可以处理基于屏幕可见信息的分析与辅助功能，但不会采用读取隐藏牌面、绕过反作弊或获取其他玩家不可见信息的方式。 Regards, Shawana

@abela399

您好，我可以负责 Android 端棋牌选牌助手的开发，重点放在牌面识别、低延迟分析和推荐结果展示。 我有 8 年全栈开发经验，也有 Android、AI、OCR、图像识别和自动化系统方面的开发经验。针对这个项目，我会优先考虑 OCR/计算机视觉方案读取牌面，再通过概率模型或策略算法快速计算推荐结果，并使用悬浮层展示建议，尽量避免 Root 和对游戏本身的侵入。 架构上可以将数据采集、识别、算法和 UI 完全模块化，方便后续增加不同的棋牌游戏和优化算法。Android 10–13 ARM64 的兼容性、低延迟以及稳定性也会作为重点测试内容。 我可以提供完整源码、APK、编译部署文档和演示，并在开始前先根据目标棋牌游戏确认具体识别方案和技术可行性。 Abel

@ihsan191

Hello there You need an Android-only 选牌助手 for ARM64 phones on Android 10–13: read the live table, score the visible hand in milliseconds, and show the next play—without root, without 挂机, and without 透视. Capture stays non-invasive: MediaProjection plus a user-defined crop so 房卡 tables and popular 棋牌 apps are added by config, not by injecting each APK. On-device OCR and template matching identify ranks and suits; a probability and expected-value engine (legal-move prune plus remaining-card model) ranks plays. A floating overlay presents the top suggestion, with a master switch, hotkey, and sensitivity so it never steals taps or lags the match. You receive a signed APK, full source, architecture notes (capture / engine / overlay), toolchain versions, a short manual, and a demo video. I have shipped overlay plus on-device vision on this Android range at sub-100ms on mid-range ARM64. If this fits, let’s lock the first two platforms and a milestone calendar this week. Ihsan

@mikes126

1. 我可以将这款 Android 选牌助手设计为“实时识别 + 低延迟决策 + 悬浮提示”的独立辅助系统：优先采用屏幕图像/OCR 获取用户可见牌面，不依赖 Root 或修改目标棋牌游戏，并通过本地算法快速计算概率、牌型价值及候选动作，毫秒级返回推荐结果。 2. 技术实现上，我会先建立 Android 10–13 ARM64 兼容的采集层，对不同分辨率、UI 布局和牌面样式进行标准化；随后建立算法层，根据具体棋牌游戏规则实现牌型识别、概率计算、局面评分及策略排序，并预留机器学习模型接口，方便后续迭代。 3. UI 层采用悬浮窗/Overlay 展示推荐，同时提供启用/暂停、灵敏度、显示位置等设置。对于 OCR 误识别、动画遮挡、网络延迟和不同设备性能差异，我会加入图像预处理、置信度校验、缓存和异常恢复，避免错误建议影响正常使用。 4. 我会将采集、识别、算法和 UI 解耦，使后续增加新的棋牌规则或平台时只需扩展对应适配模块，而不必重写整个应用。整个方案会避免 Root、内存注入及绕过平台安全机制，优先保证稳定性和兼容性。 5. 交付包括完整 Android Studio 源码、可安装 APK、模块架构说明、编译部署文档、用户手册及演示视频。我也建议先确定首款棋牌游戏和具体规则，再用真实牌局样本完成识别准确率及响应速度测试，确认 MVP 后再扩展更多平台。

@mengw3

我有 20 多年移动端和图像识别、机器学习开发经验，而且我手上已经有一套做好、能跑的棋牌选牌助手：可安装 APK 加完整源码，无 Root 悬浮窗、实时读牌面、按概率和博弈策略给出出牌和选牌建议，这套已经跑通。所以这单我不是从零开发，是把现成产品适配到你指定的游戏，更快也更稳。 这类助手的成败在于毫秒级稳定拿到牌面、建议要准、不影响正常游戏。做法就是把我现有的三层拿过来适配： - 取数层：现有的无障碍服务或截屏加 OCR、图像识别方案，适配你首批指定的棋牌 App，兼容 Android 10 到 13（ARM64），避开 Root 和内存侵入。 - 算法层：现有的概率加博弈策略引擎按你的玩法调优，必要时加轻量深度学习模型，毫秒级出建议。 - UI 层：现成的悬浮窗、热键、灵敏度设置，随开随用。 明确一点：首期只做可见手牌的实时建议，不做透视和挂机，符合你写的定位。你拿到的是完整 APK 加源码、三层架构说明、编译部署文档、用户手册和演示视频，架构留好扩展口，以后上 iOS 也顺。因为有现成底子，交付快、稳定性有保障，我可以先发一段现有 demo 给你看效果。想先确认：首批优先适配哪一两款棋牌 App？可以马上开始。

@panos1414

您好，这个项目我可以接。您要的是面向 Android 10-13 的棋牌辅助方案，核心在于实时取牌面、低延迟分析、并用悬浮窗/叠加层把结果清晰呈现，这与我在 Android 与 Mobile App Development 方向的经验高度匹配。若您选择 OCR、图像识别或深度学习路线，我可以把数据获取层、算法层、UI 层拆开设计，优先保证稳定性与响应速度，并尽量避免 Root 依赖，便于在主流 ARM64 设备上部署。交付上我会提供可安装 APK、完整源码、架构说明、编译部署文档与演示视频，方便您后续扩展到 iPhone。Panagiotis

@CorporateRD

Hi there, I understand that you want to develop an Android card-game assistant that reads the player's current hand and provides fast, strategic card-selection recommendations in real time. The app will work without root access and use non-intrusive methods such as OCR or image recognition. Right? Which exact card game should we support first? Please share the game name and, if possible, a few screenshots of the hand screen so we can understand the card layout. What exactly should the assistant recommend, best card to select, winning probability, or both? If you already have any strategy rules or sample decisions, please share them with us. Should we use only screen-based methods like OCR/image recognition, or are you open to other non-root methods? Also, do you know if the target game allows screen capture and floating overlays? How fast should the recommendation appear after the hand changes? For example, do you expect it within 100ms, 300ms, or 500ms? I start by understanding the game and recommendation logic, then choose the best recognition method. I build and optimize the Android assistant, test it across supported devices, and deliver the APK, source code, documentation, and demo with a flexible structure for future expansion. Let's jump over an on-site chat or call to walk through everything to avoid confusion. Budget and Duration are placeholders. Kind Regards, Royal Design :)

@kacperw23

Hello there You need an Android-only 选牌助手: capture the visible hand during play, score it in milliseconds, and overlay the best discard or pick—not auto-play and not 透视. First release is ARM64, Android 10–13, no Root, with toggle, hotkey, and sensitivity, plus APK, source, architecture (capture / algorithm / UI), toolchain docs, a handbook, and a demo video. I would capture frames with MediaProjection and an Accessibility hotkey fallback, recognize suits and ranks on-device with OpenCV plus a compact CNN, then score moves with a probability and combinatorial engine you can map to the first 房卡 or 大众 titles. Advice appears in a TYPE_APPLICATION_OVERLAY so the table stays interactive. Kotlin, API 29–33, no injection into the host app. After warmup, advice should land in tens of milliseconds. Capture, solver, and HUD stay separate so new tables can be added without rewriting the overlay. Share the first two apps and a table screenshot and I will send a dated milestone plan and a fixed quote this week. Thank you for your time, Kacper Warchol

@shaynegg

Hi, 我很喜欢这个项目，因为实时选牌的核心并不只是算法，而是牌面识别、分析速度和推荐准确率三者的平衡。推荐结果如果不能快速、稳定地出来，实际使用价值就会大打折扣。 我可以采用 Android 原生架构，设计牌面采集/OCR、牌局状态解析、概率/策略分析以及悬浮层展示模块，并针对 Android 10–13 ARM64 做性能优化，尽量保持低延迟、低资源占用且无需 Root。 我有 Android、图像识别及算法类项目经验，比较重视实际准确率和响应速度。建议先做一个可配置的牌面识别原型，先验证识别准确率和完整分析链路的延迟，再扩展完整功能，这样能降低后续开发风险。 想先确认一下：首期具体是哪款棋牌游戏及规则？因为选牌算法需要根据具体玩法和计分规则设计。 我可以提供 APK、完整源码、架构说明及编译部署文档。

@olehh6

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@arturg6

你好， "OCR 截屏识别 + 毫秒级策略引擎" - 你需要一个在牌局中实时读牌并给出稳定、低延迟选牌建议的安卓助手。 核心难点是牌面获取与延迟控制。我会用无侵入式截屏 + OCR/图像识别来读取牌面，再用概率模型和博弈策略生成建议，保证在毫秒级完成分析。UI 用悬浮窗叠加层，不影响游戏操作。我之前做过高实时性的视觉交互项目 —— https://www.freelancer.com/projects/three-js/Artistic-Hot-Spring-Visualization/reviews —— 在性能敏感场景下保持稳定输出。 还会把架构拆成三层：数据获取层、算法层、UI 层，方便你后续扩展到 iOS 或加入更高级功能。APK、源码、部署文档、用户手册都会完整交付。 首批你希望优先支持哪类棋牌平台？房卡类还是大众平台？ Artur Giżycki