Modulenotfounderror: no module named ‘spacy’ [SOLVED]
Are you encountering an error in Python that says modulenotfounderror: no module named ‘spacy’? Worry no more, as this article will show you how to solve that error. What does …
Python Capitalization Method with Examples
With the help of examples, this tutorial will teach you about the Python capitalization method. What is Python capitalization? The Python capitalization method returns a copy of the original string …
Everything You Should Know About Python Hash
In this tutorial, you will learn about Python Hash. This is a built-in function that returns an object hash value. When looking at a dictionary, the hash value is an …
Python timeit with Best Example
Python timeit() is a method that enables programmers to measure the execution time of their programs. In this tutorial, you will know what and how the Python timeit function works …
Heap Implementation Python with Example
This article will explain what is heap implementation in Python. We will learn the difference between max-heap and min-heap and how max-heap and min-heap are used in Python programs. What is …
modulenotfounderror no module named tensorflow keras
In this article, we will discuss on how to solve the no module named tensorflow keras for all the programmers who encountered this error. Why the no module named ‘tensorflow.keras’ …
Modulenotfounderror: No Module Named ‘imblearn’ [SOLVED]
This article will show you how to solve the error “modulenotfounderror: no module named ‘imblearn’” in Python. Aside from that, we will also discuss with you the meaning of “imblearn.” …
Modulenotfounderror: no module named elasticsearch [Solved]
In this article, we will show how to solve Modulenotfounderror: no module named elasticsearch. Along with step by step guide in order to understand what causes this error. Why Modulenotfounderror: …
Modulenotfounderror: no module named ‘flask._compat’
This article will solve the “modulenotfounderror: no module named ‘flask._compat’” error message. That you encounter when working on your Flask project, especially when you are new to using Python. Fortunately, …
How To Make A Venn Diagram In PowerPoint
Enhance your PowerPoint skills by learning how to make a Venn diagram in PowerPoint with this simple guide. Follow the step-by-step instructions for creating one below to help you with your presentation and make …
How To Add Notes To PowerPoint: Quick And Easy Guide
In this tutorial, we’ll talk through how to add speaker notes to a PowerPoint for an effective presentation. Start to learn how to add notes in PowerPoint with our comprehensive …
modulenotfounderror: no module named imwatermark
In this article, we will discuss the solution on how to solve the error no module named imwatermark. Also, we will discuss what is python imwatermark? Why this error occur? …
Keyboard Shortcuts On PowerPoint Presentations
Do you always use PowerPoint for your presentations, but you still don’t know the keyboard shortcuts on PowerPoint? This article will show you the keyboard shortcuts for PowerPoint slideshow presentations. …
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.