TinyPNG VS NumPy
Compare TinyPNG VS NumPy and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
featured
TinyPNG
ImageOptim
TinyJPG
Caesium Image Compressor
Squoosh
JPEGmini
Compressor.io
iLoveIMG
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
TinyPNGTinyPNG might be a bit more popular than NumPy. We know about 155 links to it since March 2021 and only 107 links to NumPy. 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.
You also have things like https://tinypng.com which do (basically) lossy PNG for you. Works pretty well. - Source: Hacker News / 2 months ago
Compressing images: This technique reduces image size without compromising quality. You can achieve this using various image compression tools like TinyPNG or ImageOptim. These tools are specifically designed to manage multiple image formats and compression methods. They help reduce image files, resulting in less data transfer from the server to the user's device. It is advisable to compress images before... - Source: dev.to / 2 months ago
Tinypng.com — API to compress and resize PNG and JPEG images, offers 500 compressions for free each month. - Source: dev.to / 3 months ago
TinyPNG Smart WebP, PNG and JPEG Compression. When utilised with the Raycast extension by Ryo Kawamata image compression becomes a simple task. - Source: dev.to / 4 months ago
ImageOptim - For lossless image compression. TinyPNG - Compress PNG and JPEG images without losing quality. - Source: dev.to / 5 months ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
ImageOptim - Faster web pages and apps.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
TinyJPG - Compress JPEG images with perfect quality and file size
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Caesium Image Compressor - Compress your pictures up to 90% without visible quality loss.
OpenCV - OpenCV is the world's biggest computer vision library