Free Source Code, Capstone Projects & Programming Tutorials

Your trusted resource for downloadable source code, complete capstone projects with ER diagrams and Chapter 1-5 documentation, AI-ready capstones (RAG, ChatGPT, computer vision), and step-by-step tutorials in PHP, Python, Java, JavaScript, and more. Built by working developers, tested before publishing, and updated for 2026.

📅 Updated weekly | ✅ Code tested before publishing | 👨‍💻 Built by PIES IT Solutions developers

Forced Reflow While Executing JavaScript

forced reflow while executing javascript

In this article, we’ll delve deep into forced reflow While Executing JavaScript, its causes, implications, and how to mitigate its impact effectively. What is forced reflow while executing JavaScript? Forced …

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Reverse Linked List JavaScript

Object Reference in JavaScript

In this article, we will discuss in detail the reverse linked lists in JavaScript, exploring the why, how, and when of this important task. What is Reverse Linked List JavaScript? …

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Mastering JavaScript Arithmetic Operations

javascript arithmetic operations

How can we use JavaScript arithmetic operations to manipulate numbers? Read on to discover new insights about these operations. Most of us love Math, right? Well, maybe not everyone, but …

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Object Reference in JavaScript with Example Codes

Object Reference in JavaScript

In this article, you will have to learn the fundamental concept of Object Reference in JavaScript, ensuring you will understand it thoroughly. JavaScript, usually referred to as the “language of …

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JavaScript Test if String Contains Substring

JavaScript Test if String Contains Substring

In this article, we will discuss the JavaScript Test if String Contains Substring. Whether you are a beginner or an experienced developer, this article will provide you valuable understanding into …

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How to Use JavaScript Optional Chaining Array

JavaScript Optional Chaining Array

JavaScript Optional Chaining Array, typically referred to as “?.” is a game-changer for developers. It enables you to access nested objects and arrays without the need for considerable error-checking. Let’s …

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Frequently Asked Questions

Are these deep learning projects free for capstone and thesis use?
Yes. All deep learning projects on this hub are free to download, modify, and submit. No attribution required for academic use. Most are MIT-licensed or include source-code packs with sample datasets and pretrained model weights.
What deep learning frameworks do I need installed?
Most projects use OpenCV (cv2) for video capture and image preprocessing, plus one of: TensorFlow / Keras (Caffe model loading via cv2.dnn, custom CNN training), PyTorch (research-style models, YOLO v5+, transformers), or MediaPipe (Google's optimized face/hand/pose detectors). Install with pip install opencv-python tensorflow keras torch torchvision mediapipe numpy. Python 3.10, 3.11, or 3.12 recommended (avoid 3.13 until all wheels catch up).
Do I need a GPU to run these deep learning projects?
For inference (running a pretrained model on your webcam): no, CPU runs at 15-30 FPS for most computer-vision tasks. For training a custom model on your own dataset: GPU strongly recommended (CPU works but is slow). Free GPU options: Google Colab Free (12-hour sessions, sufficient for most BSIT capstones), Kaggle Notebooks Free (30-hour weekly quota), Paperspace Free tier. No need to buy a $1000+ GPU just for a capstone defense.
Deep learning vs classical machine learning, which should I pick for my capstone?
Pick deep learning when your inputs are unstructured (images, audio, video, text) and you have 10,000+ training samples. Pick classical ML (random forest, SVM, logistic regression) for tabular data, small datasets (under 1,000 rows), or when you need explainable predictions for the panel. Many capstones combine both: deep learning for feature extraction (face embedding via FaceNet) plus classical ML on top (SVM classifier for identity matching).
Why is my OpenCV deep learning model running at 2 FPS?
Three usual causes: (1) Resolution too high, resize frames to 640x480 or 320x240 before inference. (2) Wrong cv2.dnn backend, set net.setPreferableBackend(cv2.dnn.DNN_BACKEND_OPENCV) and net.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU). (3) Heavy model on weak hardware, swap YOLO v5 for MobileNet-SSD or use Haar cascades for simple face/eye detection. Also close other applications and disable laptop battery-save throttling.
Can I extend a single OpenCV demo into a full BSIT capstone?
Yes, and you should. A standalone webcam demo (face detection alone) is too narrow for capstone scope. Wrap it in a real system: face recognition becomes Real-Time Attendance System with PHP/MySQL dashboard, object detection becomes Smart CCTV Alert System with email notifications, drowsiness detection becomes Driver Monitoring System for fleet vehicles. Add user accounts, database logging, simple admin UI, and write Chapters 1-5 manuscript to satisfy panel requirements.
How often is this deep learning projects list updated?
New deep learning projects are added periodically as we receive student requests and new models become OpenCV-compatible. Last refreshed June 2026 with 19 vision-focused projects covering face recognition, object detection, traffic-sign classification, OCR, and more.