n this tutorial, you will learn how to detect fire and smoke using Computer Vision, OpenCV, and the Keras Deep Learning library.
Latest Resources in Computer Vision
Computer Vision
Fire and smoke detection with Keras and Deep Learning pyimagesearch.com
Face Detection and Recognition with Keras sitepoint.com
TensorFlow Lite is a framework for running lightweight machine learning models, and it’s perfect for low-power devices like the Raspberry Pi! This video shows how to set up TensorFlow Lite on the Raspberry Pi for running object detection models to locate and identify objects in real-time webcam feeds, videos, or images.
Traffic Sign Classification with Keras and Deep Learning pyimagesearch.com
In this tutorial, you will learn how to train your own traffic sign classifier/recognizer capable of obtaining over 95% accuracy using Keras and Deep Learning.
OpenCV – Stream video to web browser/HTML page pyimagesearch.com
In this tutorial you will learn how to use OpenCV to stream video from a webcam to a web browser/HTML page using Flask and Python.
Cyclical Learning Rates with Keras and Deep Learning pyimagesearch.com
In this tutorial, you will learn how to use Cyclical Learning Rates (CLR) and Keras to train your own neural networks. Using Cyclical Learning Rates you can dramatically reduce the number of experiments required to tune and find an optimal learning rate for your model.
Searching for Pulsars with Machine Learning medium.com
Searching for pulsars is a labor-intensive process that requires experienced astronomers and trained volunteers for their classification. In this article, we implement machine learning techniques to facilitate the process.
Keras Mask R-CNN pyimagesearch.com
In this tutorial, you will learn how to use Keras and Mask R-CNN to perform instance segmentation (both with and without a GPU).
Using Mask R-CNN we can perform both: Object detection, giving us the (x, y)-bounding box coordinates of for each object in an image; Instance segmentation, enabling us to obtain a pixel-wise mask for each individual object in an image.
Fine-tuning with Keras and Deep Learning pyimagesearch.com
In this tutorial, you will learn how to perform fine-tuning with Keras and Deep Learning.
We will take a CNN pre-trained on the ImageNet dataset and fine-tune it to perform image classification and recognize classes it was never trained on.
Today is the final post in our three-part series on fine-tuning:
- Part #1: Transfer learning with Keras and Deep Learning
- Part #2: Feature extraction with on large datasets with Keras and Deep Learning
- Part #3: Fine-tuning with Keras and Deep Learning (today’s post)
Cropping, Resizing, Rotating, Thresholding, Blurring, Drawing & Writing on an image, Face Detection & Contouring to detect objects. All Explained.
