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Showing 19 open source projects for "size"
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pikepdf
A Python library for reading and writing PDF, powered by QPDF
pikepdf is a Python library allowing the creation, manipulation, and repair of PDFs. It provides a Pythonic wrapper around the C++ PDF content transformation library, QPDF. Python + QPDF = “py” + “qpdf” = “pyqpdf”, which looks like a dyslexia test and is no fun to type. But say “pyqpdf” out loud, and it sounds like “pikepdf”. pikepdf is a library intended for developers who want to create, manipulate, parse, repair, and abuse the PDF format. It supports reading and write PDFs, including... -
2
Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
3
GluCat: Clifford algebra templates
Calculation with Clifford algebras: C++ library and Python module
GluCat is a generic library of C++ templates that implement universal Clifford algebras over the field of real numbers. The PyClical extension module for Python gives users an easy Python scripting interface for calculations in Clifford algebras. The name PyClical is an homage to Pertti Lounesto's CLICAL. -
4
bidict
The bidirectional mapping library for Python
...Enterprise-level support for bidict can be obtained via the Tidelift subscription. One of the best things about bidict is that it touches a surprising number of interesting Python corners, especially given its small size and scope. Choose a tier and GitHub handles everything else. Your GitHub sponsorship will automatically go on the same bill you already have set up with GitHub, so after the one-click signup, there’s nothing else to do. -
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5
Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is... -
6
albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
albert_zh is a Chinese ALBERT pretraining and model release repository. It implements ALBERT with TensorFlow and provides Chinese pretrained models designed to reduce parameter size while preserving strong language understanding performance. The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair semantic similarity and Chinese classification benchmarks. ... -
7
YOLOV3 Pytorch
This is a source code for yolo3-pytorch
...The project added multi-GPU training, target count statistics, learning rate scheduling with step and cosine options, and optimizer selection between Adam and SGD. It also includes adaptive learning rate adjustment based on batch size, image cropping, many configurable parameters, and expanded comments for easier study. It is well suited for learners and developers who want a hands-on YOLOv3 codebase in PyTorch. -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
...It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU training, seed settings for reproducible results, adaptive learning rate behavior based on batch size, and both step and cosine learning rate schedules. It also supports Adam and SGD optimizer choices, image cropping, adjustable parameters, and extensive code comments. It is a useful educational and applied repository for users who want to understand or customize YOLOv4 in PyTorch. -
9
Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
YOLOv7 is the official implementation of the paper “YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.” It is a PyTorch-based object detection project focused on high speed and strong accuracy for real-time computer vision. The repository provides model definitions, training scripts, testing tools, inference examples, pretrained weights, and deployment-oriented materials. YOLOv7 introduced training-time improvements that raise accuracy without... -
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10
Whisper Library
Whisper is a file-based time-series database format for Graphite
Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target file, but instead, only add the missing data (e.g. where the gaps in the target file are). ... -
11
Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
...The project also includes learning rate scheduling through step and cosine methods, optimizer choices between Adam and SGD, adaptive learning rate behavior based on batch size, image cropping, FPS testing, video prediction, and batch prediction. It is a practical reference for users who want a more classical two-stage detector workflow in PyTorch. -
12
DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. It is useful for users who want a stronger semantic segmentation baseline than U-Net for scene-level segmentation tasks. -
13
Differentiable Neural Computer
A TensorFlow implementation of the Differentiable Neural Computer
The Differentiable Neural Computer (DNC), developed by Google DeepMind, is a neural network architecture augmented with dynamic external memory, enabling it to learn algorithms and solve complex reasoning tasks. Published in Nature in 2016 under the paper “Hybrid computing using a neural network with dynamic external memory,” the DNC combines the pattern recognition power of neural networks with a memory module that can be written to and read from in a differentiable way. This allows the... -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
15
Brand new cheatsheets and handouts
Matplotlib 3.1 cheat sheet
The Brand new cheatsheets and handouts repo is a compact, quick-reference summary of the most commonly used plotting commands and configurations in Matplotlib, intended to serve as a handy reference for experienced users who want to recall syntax or find the right function without digging into full documentation. It lays out common use cases (plot types, styling, figure configuration, saving/exporting, subplot layout, etc.) in a concise and organized format — often serving as a “cheat sheet”... -
16
RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
17
tkFontChooser
Simple font chooser dialog for tkinter
A simple font chooser for Tkinter that allow the user to select the font family among the fonts available on his/her system. The size and style (bold, italic, underline, strikethrough) of the text can be set too. This module contains a `FontChooser` class which implements the font chooser and an `askfont` function that displays the font chooser and returns the chosen font when the user closes the font chooser. The font is returned as a dictionary like the one returned by the function `tkFont.Font.actual`. -
18
Icon Font to PNG
Python script (and library) for exporting icons from icon fonts
Python script (and library) for easy and simple export of icons from web icon fonts (e.g. Font Awesome, Octicons) as PNG images. The best part is the provided shell script, but you can also use it’s functionality directly in your (probably awesome) Python project. There’s also font-awesome-to-png script for backward compatibility with the first iteration of the concept. You can use IconFont (and IconFontDownloader for that matter) directly inside your Python project. There's no proper... -
19
cloud-file-system-sdk
CloudFile File System SDK
...With the Cloud File SDK, the developers can implement the cloud disaster recovery (Cloud DR) solution, seamlessly integrate your existing applications to the cloud environment without affecting the original data and programs, without any modification of your existing applications. It can help the small to medium size companies to implement the Cloud DR with the lowest cost and minimal disruption to normal operation.
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