Runtimeerror: expected scalar type half but found float
The runtimeerror: expected scalar type half but found float error typically occurs when there is a mismatch between the data type expected by a PyTorch function and the actual data …
Nameerror: name ‘open’ is not defined
In this article, we’ll delve into the solution of Python nameerror: name ‘open’ is not defined error message. This error message is confusing, especially if you’re new to this. Fortunately, this article …
Importerror cannot import name ‘_rfc_1738_quote’ from ‘sqlalchemy.engine.url’
Working with Python and its libraries, you may encounter import errors, namely, Importerror cannot import name ‘_rfc_1738_quote’ from ‘sqlalchemy.engine.url’. Purposely, this article will delve into the details of this error …
Nameerror: name ‘kwargs’ is not defined
Are you encountering and struggling to fix the Python nameerror: name ‘kwargs’ is not defined error message? Well, keep on reading because we can help you to get rid of this error. …
Nameerror: name ‘display’ is not defined
The nameerror: name ‘display’ is not defined is an error message you’ll encounter when working in Python. Are you dealing with this error right now and having a hard time trying to …
Runtimeerror: expected scalar type bfloat16 but found float
One of the common errors may encounter of a programmer in working into deep learning frameworks such as PyTorch is: Runtimeerror: expected scalar type bfloat16 but found float This error …
runtimeerror: either sqlalchemy_database_uri or sqlalchemy_binds must be set.
If you’re a Python developer working with databases, you may encounter runtimeerror: either sqlalchemy_database_uri or sqlalchemy_binds must be set. error. This error is related to the SQLAlchemy library, which is …
Runtimeerror: cudnn error: cudnn_status_mapping_error
If you are working with deep learning frameworks, encountering errors is an inevitable part of a programmer. One of the often error that can cause frustration and obstruct your progress …
cuda error: all cuda-capable devices are busy or unavailable
If you are encounter the runtimeerror: cuda error: all cuda-capable devices are busy or unavailable while working with CUDA (Compute Unified Device Architecture), you know how frustrating it can be. …
Nameerror name get_ipython is not defined
In this article, we’ll show you how to fix the nameerror name get_ipython is not defined error message. If you’re new to this error message technically, it’s quite for you to fix …
Importerror: cannot import name ‘cached_property’ from ‘werkzeug’
Have you come across the error importerror: cannot import name ‘cached_property’ from ‘werkzeug‘? Well, in particular, this error could be hard if you are not familiar with werkzeug library. So …
Importerror: cannot import name ‘paramspec’ from ‘typing_extensions’
Working with Python projects, it’s inevitable to face the “ImportError: Cannot import name ‘paramspec’ from ‘typing_extensions‘” error at some point. Actually, this error usually occurs when trying to import the …
Nameerror name ‘x_train’ is not defined
Hey, are you still stuck with the Python nameerror name ‘x_train’ is not defined error message? In this article, we’ll hand you the solution to this error because we understand the feeling …
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.