scikit-image
NumPy
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scikit-image | NumPy | |
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10 | 272 | |
5,864 | 26,360 | |
1.3% | 1.9% | |
9.6 | 10.0 | |
5 days ago | 1 day ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
scikit-image
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How to Estimate Depth from a Single Image
We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics.
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
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.
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Converting Scikit-Learn Library Algorithms to C
scikit hog library: https://github.com/scikit-image/scikit-image/blob/main/skimage/feature/_hog.py#L302 , https://github.com/scikit-image/scikit-image/blob/main/skimage/feature/_hoghistogram.pyx
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Is it possible to add a noise to an image in python?
This is a good cv deep learning book with python examples https://www.manning.com/books/deep-learning-for-vision-systems. If you're pretty comfortable with the concepts of traditional image processing this is a good companion to cv2 (so you don't have to reinvent the wheel) https://scikit-image.org/
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A CLI that does simple image processing and also generates cool patterns
Also, don't know if you're familiar with Python, but if you need ideas for to implement for future directions : https://scikit-image.org/
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Color Matrices for scan correction
There's probably something in scikit-image to do what you want, or close enough to build on.
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Python: The Best Image Processing Libraries
Scikit-image The Scikit-image library is a collection of image processing algorithms that are designed to be easy to use and understand. It includes algorithms for common tasks like edge detection, feature extraction, and image restoration. If you are just starting out in image processing, then this is a good library to check out!
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Image Processing is Easier than you Thought! (Getting started with Python Pillow)
Python is a general-purpose programming language that provides many image processing libraries for adding image processing capabilities to digital images. Some of the most common image processing libraries in Python are OpenCV, Python Imaging Library (PIL), Scikit-image etc.
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Scikit-image for Image Processing
Then you would need to find what this plugin does for imshow. First thing you can see is that "interpolation" is not "bicubic" as you used, but "nearest"… but there are other settings here that are responsible for the difference of displays. (it's better that you look at the source code in your environment, as it might be slightly different)
- Patented algorithm removed from scikit-image shortly before merge accept
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
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:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
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.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
pillow - Python Imaging Library (Fork)
SymPy - A computer algebra system written in pure Python
OpenCV - Open Source Computer Vision Library
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
nude.py - Nudity detection with Python
blaze - NumPy and Pandas interface to Big Data
python-qrcode - Python QR Code image generator
SciPy - SciPy library main repository
thumbor - thumbor is an open-source photo thumbnail service by globo.com
Numba - NumPy aware dynamic Python compiler using LLVM
wand - The ctypes-based simple ImageMagick binding for Python
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).