{"id":26779128,"url":"https://github.com/michelecortiana/digitml","last_synced_at":"2026-04-09T18:55:03.754Z","repository":{"id":284979130,"uuid":"956691614","full_name":"michelecortiana/DigitML","owner":"michelecortiana","description":"This school project uses Machine Learning 🤖 to recognize digits and letters with an advanced algorithm. 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align=center\u003e\n\u003cimg src=\"https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/animated-logo.svg\" alt='logo animato' width=50%\u003e \u003cbr\u003e\n\u003ci width=80%\u003eProgetto scolastico per il riconoscimento di cifre e lettere attraverso Machine Learning, con backend Java, frontend PHP, app Android e server Python.\u003c/i\u003e\n\u003c/p\u003e\n\u003cbr\u003e\n\n# 🤝 Contributors\n\u003ci\u003eUn grazie speciale a queste fantastiche persone che hanno contribuito al progetto:\u003c/i\u003e\n\u003cbr\u003e\n\u003cp\u003e\n  \u003ca href=\"https://github.com/michelecortiana/DigitML/graphs/contributors\"\u003e\n    \u003cimg src=\"https://contrib.rocks/image?repo=michelecortiana/DigitML\" /\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\u003e [!NOTE]\n\u003e | PROFILO | RUOLO ||\n\u003e |---|---|---|\n\u003e | [@paolomalgarin](https://github.com/paolomalgarin) | Design e web-app | ✨ |\n\u003e | [@anItalianGeek](https://github.com/anItalianGeek) | Project manager | 💼 |\n\u003e | [@michelecortiana](https://github.com/michelecortiana) | Machine learning | 🧠 |\n\u003e | [@Phoeyuh](https://github.com/Phoeyuh) | API | 🐝 |\n\u003e | [@Benti06](https://github.com/Benti06) | Android app | 📱 |\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n# 📖 INDICE  \n * 📥 [Installation guide](https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/Documentation/INSTALLATION-OPTIONS.md)\n * 📌 [Panoramica](#-panoramica)\n * 🏗️ [Architettura \u0026 Flusso dei Dati](#%EF%B8%8F-architettura--flusso-dei-dati)  \n * 🛠️ [Tecnologie Utilizzate](#%EF%B8%8F-tecnologie-utilizzate)  \n * 📷 [Esempi d’Uso](#-esempi-duso)  \n * 📊 [Dati](#-dati)  \n * 📄 [Licenza](#-licenza)  \n\n\u003cbr\u003e\n\u003cbr\u003e\n\n# 📌 Panoramica\n\nIl progetto DigitML ci è stato assegnato come attività didattica con l’obiettivo di realizzare un’applicazione distribuita per il riconoscimento di cifre manoscritte.  \nLa consegna prevedeva la creazione di un sistema capace di identificare numeri scritti a mano, da utilizzare durante gli open‑day scolastici per mostrare le competenze acquisite nel triennio di Informatica.  \nSpinti dalla nostra curiosità e dalla voglia di sperimentare, abbiamo esteso il progetto aggiungendo numerose funzionalità extra, tra cui il riconoscimento delle lettere dell’alfabeto.\n\u003e [!TIP]\n\u003e [Installation guide](https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/Documentation/INSTALLATION-OPTIONS.md)\n\n\u003cbr\u003e\n\n---\n\u003cbr\u003e\n\n# 🏗️ Architettura \u0026 Flusso dei Dati\n\n *Le applicazioni front-end mandano le richieste all'API che è l'unico che può comunicare con il ML grazie ad un **HMAC***\n \u003cimg src=\"https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/data-flow.svg\" alt='logo animato' width=70%\u003e \u003cbr\u003e\n\n\u003cbr\u003e\n\n---\n\u003cbr\u003e\n\n# 🛠️ Tecnologie Utilizzate\n\n\u003cimg src=\"https://skillicons.dev/icons?i=php,html,css,js,python,tensorflow,java\" /\u003e \u003cbr\u003e\n\n- **Java Servlet**: comunicazione front-end e back-end  \n- **PHP 8+**: interfaccia web e autenticazione  \n- **Android (*Java*)**: app mobile (*Android*)  \n- **Python 3.8+**: server Flask  \n- **TensorFlow/Keras**: rete neurale  \n\n\u003cbr\u003e\n\n---\n\u003cbr\u003e\n\n# 📷 Esempi d’Uso  \n\u003e *Qui sotto un esempio della web-app e dell'app Android:*\n\n\u003cimg src=\"https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/guessing.gif\" alt='Web-app gui' width=79%\u003e\u003cimg src=\"https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/Android-gui.jpg\" alt='Android gui' width=21%\u003e\n\n\u003e [!WARNING]\n\u003e Per provarla vedi [installation guide](https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/Documentation/INSTALLATION-OPTIONS.md).\n\n\u003cbr\u003e\n\n---\n\u003cbr\u003e\n\n# 📊 Dati\nDataset utilizzati:\n|NOME| MNIST | A-Z Handwritten Alphabets |\n|---|---|---|\n|IMG|\u003cimg src='https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/MNIST.png' alt='mnist'\u003e|\u003cimg src='https://github.com/michelecortiana/DigitML/blob/main/README%20-%20Stuff/A-Z%20Handwritten%20Alphabets.png' alt='A-Z Handwritten Alphabets'\u003e|\n|TIPO DI RETE|CNN _(Convolutional Neural Network)_|CNN _(Convolutional Neural Network)_|\n|VAL ACCURACY|**98.6%**|**98.8%**|\n|TRAIN ACCURACY|99.3%|99.5%|\n\n\u003cbr\u003e\n\n---\n\u003cbr\u003e\n\n# 📄 Licenza\nQuesto progetto è rilasciato sotto [MIT License](https://github.com/michelecortiana/DigitML/blob/main/LICENSE.txt).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmichelecortiana%2Fdigitml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmichelecortiana%2Fdigitml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmichelecortiana%2Fdigitml/lists"}