Project Burndown
Sense
Brultech GreenEye Monitor (GEM)
Focus
Fido
RescueTime
FocusList
Kinopio
FilePane
OpenCV
Scikit-learn
Pandas
NumPy
Dataiku
Exploratory
htm.java
WEKA
OpenCVBased on our record, Sense should be more popular than OpenCV. It has been mentiond 109 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
At Sense we make a home energy monitor that provides real-time appliance-level monitoring using machine learning. Hardware is indeed hard as everyone said it would be! https://sense.com. - Source: Hacker News / 10 months ago
If you want to know exactly how much you are using, when, and approximately how much each device is pulling there are sensors that can help. Eg Https://sense.com/ There are a few others. If you are interested I recommend some googling and read reviews. Source: 10 months ago
Hi all, Wondering if you have any other recommendations or thoughts on the below. Use case: I have a solar array and want to track in one spot all the energy produced, energy imported, energy exported, and where energy is being used. Both of the following seem to do what I want with some nuances. I am looking at: 1) Sense [0], which identifies energy use patterns of different devices to determine what devices are... - Source: Hacker News / 10 months ago
Https://sense.com/ try this guy out. I got one and it seems to work fairly well. I have a light fixture that’s wildly inefficient. Source: 11 months ago
I don’t see it mentioned here, but if you really wanted to know what is using power in her whole house, you could get a “Sense” energy monitor. It gets installed by you inside the main breaker panel and lets you see/learns what uses power and allows you to pinpoint large wasters. A little pricey up front, but could easily pay for itself. Source: 11 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 4 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 5 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 9 months ago
I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest... Source: 9 months ago
You also need C++ if you're going to do things which aren't built in as part of the engine. As an example if you're looking at using compute shaders, inbuilt native APIs such as a mobile phone's location services, or a third-party library such as OpenCV, then you're going to need C++. Source: 11 months ago
Brultech GreenEye Monitor (GEM) - - One GreenEye Monitor - Choice of communication option.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Focus - New Tab page that gives you a moment of calm and inspires you to be more productive.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Fido - The safest and most minimalistic smart lock
NumPy - NumPy is the fundamental package for scientific computing with Python