Search Results for "pixels."
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Showing 25 open source projects for "pixels."
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1
Ark Pixel Font
Ark pixel font - Open source Pan-CJK pixel font
...Among them, 12 pixels are the main development target. 10, 16 pixels are experimental. Efforts are currently underway to achieve the availability of 12 pixels under the GB2312 character set. We have a temporary interim solution available for production until the full font is available, check out the Stitcher Pixel Font project. -
2
folderify
Generate pixel-perfect macOS folder icons in the native style
...There is currently no simple way to set an icon that will automatically switch between light and dark when you switch the entire OS. You can only assign one version of an icon to a folder. Dark color scheme is only supported for macOS 11.0 (and later) right now. Make sure the corner pixels of the mask image are transparent. They are used for empty margins. -
3
JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture. This makes learning focus on semantics and structure, yielding features that transfer well with simple linear probes and minimal fine-tuning. ... -
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Qwen-VL
Chat & pretrained large vision language model
Qwen-VL is Alibaba Cloud’s vision-language large model family, designed to integrate visual and linguistic modalities. It accepts image inputs (with optional bounding boxes) and text, and produces text (and sometimes bounding boxes) as output. The model variants (VL-Plus, VL-Max, etc.) have been upgraded for better visual reasoning, text recognition from images, fine-grained understanding, and support for high image resolutions / extreme aspect ratios. Qwen-VL supports multilingual inputs... -
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5
vJEPA-2
PyTorch code and models for VJEPA2 self-supervised learning from video
VJEPA2 is a next-generation self-supervised learning framework for video that extends the “predict in representation space” idea from i-JEPA to the temporal domain. Instead of reconstructing pixels, it predicts the missing high-level embeddings of masked space-time regions using a context encoder and a slowly updated target encoder. This objective encourages the model to learn semantics, motion, and long-range structure without the shortcuts that pixel-level losses can invite. The architecture is designed to scale: spatiotemporal ViT backbones, flexible masking schedules, and efficient sampling let it train on long clips while remaining stable. ... -
6
SAHI
A lightweight vision library for performing large object detection
...Here comes the SAHI to help developers overcome these real-world problems with many vision utilities. Detection of small objects and objects far away in the scene is a major challenge in surveillance applications. Such objects are represented by small number of pixels in the image and lack sufficient details, making them difficult to detect using conventional detectors. In this work, an open-source framework called Slicing Aided Hyper Inference (SAHI) is proposed that provides a generic slicing aided inference and fine-tuning pipeline for small object detection. -
7
Aphantasia
CLIP + FFT/DWT/RGB = text to image/video
...Generating massive detailed textures, a la deepdream, fullHD/4K resolutions and above, various CLIP models (including multi-language from SBERT), continuous mode to process phrase lists (e.g. illustrating lyrics), pan/zoom motion with smooth interpolation. Direct RGB pixels optimization (very stable) depth-based 3D look (courtesy of deKxi, based on AdaBins), complex queries: text and/or image as main prompts, separate text prompts for style and to subtract (avoid) topics. Starting/resuming process from saved parameters or from an image. -
8
FLUX.1 Krea
Powerful open source image generation model
...It is a rectified-flow model distilled from the original Krea 1, providing enhanced sampling efficiency through classifier-free guidance distillation. The model supports generation at resolutions between 1024 and 1280 pixels with recommended inference steps between 28 and 32 for optimal balance of speed and quality. FLUX.1 Krea is fully compatible with the FLUX.1 architecture, making it easy to integrate into existing workflows and pipelines. The repository offers easy-to-use inference scripts and a Jupyter Notebook example to facilitate quick experimentation and adoption. ... -
9
Oblivion-Inverse
Open source e-mail tracker made with Flask, setup & run in 10 minutes
Oblivion-Inverse is a simple, free & open source e-mail tracking solution which based on the usage of web beacons or tracking pixels. Build with Flask and setup under 10 minutes on your own production environment. Designed to provide information about the email read status, time, IP address of the recipient's device or proxy, as well as request headers such as the user-agent, which can reveal details about the recipient's browser, operating system, and device. -
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10
Shopne-Arcade
A frontend for GnGeo emulator written purely in Python
Shopne Arcade is a front-end application designed to easily play Neo Geo system games on PC. It's interface is compatible for screens with low resolution such as 640x480 pixels. It lets users play Neo Geo system games from one interface where users will be able pick different game play experience settings such as Neo Geo games video resolutions, audio sampling rates, etc. Shopne Arcade is written in pure Python language without any external dependencies making it portable across various Linux Distributions. -
11
iJEPA
Official codebase for I-JEPA
i-JEPA (Image Joint-Embedding Predictive Architecture) is a self-supervised learning framework that predicts missing high-level representations rather than reconstructing pixels. A context encoder sees visible regions of an image and predicts target embeddings for masked regions produced by a slowly updated target encoder, focusing learning on semantics instead of texture. This objective sidesteps generative pixel losses and avoids heavy negative sampling, producing features that transfer strongly with linear probes and minimal fine-tuning. ... -
12
DensePose
A real-time approach for mapping all human pixels of 2D RGB images
...DensePose is widely used in augmented reality, motion capture, virtual try-on, and visual effects applications because it enables real-time 3D human mapping from 2D inputs. The model architecture builds on Mask R-CNN, using additional regression heads to predict UV coordinates that map image pixels to 3D surfaces. -
13
Image GPT
Large-scale autoregressive pixel model for image generation by OpenAI
Image-GPT is the official research code and models from OpenAI’s paper Generative Pretraining from Pixels. The project adapts GPT-2 to the image domain, showing that the same transformer architecture can model sequences of pixels without altering its fundamental structure. It provides scripts to download pretrained checkpoints of different model sizes (small, medium, large) trained on large-scale datasets and includes utilities for handling color quantization with a 9-bit palette. ... -
14
Consistent Depth
We estimate dense, flicker-free, geometrically consistent depth
Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. ... -
15
PixelCNN
Code for the paper "PixelCNN++: A PixelCNN Implementation..."
PixelCNN is the official implementation from OpenAI of the autoregressive generative model described in the paper Conditional Image Generation with PixelCNN Decoders. It provides code for training and evaluating PixelCNN models on image datasets, focusing on conditional image modeling where pixels are generated sequentially based on the values of previously generated pixels. The repository demonstrates how to apply masked convolutions to enforce autoregressive dependencies and achieve tractable likelihood-based training. It also includes scripts for reproducing key experimental results from the paper, such as conditional sampling on datasets like CIFAR-10. ... -
16
imgaug
Image augmentation for machine learning experiments
...Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions, hue/saturation changes, cropping/padding, blurring, etc. Rotate image and segmentation map on it by the same value sampled. Convert keypoints to distance maps, extract pixels within bounding boxes from images, clip polygon to the image plane, etc. Scale segmentation maps, average/max pool of images/maps, pad images to aspect ratios (e.g. to square them). Draw heatmaps, segmentation maps, keypoints, bounding boxes, etc. -
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PyTorch pretrained BigGAN
PyTorch implementation of BigGAN with pretrained weights
An op-for-op PyTorch reimplementation of DeepMind's BigGAN model with the pre-trained weights from DeepMind. This repository contains an op-for-op PyTorch reimplementation of DeepMind's BigGAN that was released with the paper Large Scale GAN Training for High Fidelity Natural Image Synthesis. This PyTorch implementation of BigGAN is provided with the pretrained 128x128, 256x256 and 512x512 models by DeepMind. We also provide the scripts used to download and convert these models from the... -
18
Universe
Software for measuring and training an AI's general intelligence
...It does this by packaging the program into a Docker container, and presenting the AI with the same interface a human uses: sending keyboard and mouse events, and receiving screen pixels. Our initial release contains over 1,000 environments in which an AI agent can take actions and gather observations. -
19
Simple xbm Image Editor
XBM images are displayed in actual size and in an enlarged edit grid.
...Background and foreground color selection is provided in order to experiment with colors for your application. The editor can display very large .xbm files in their actual size but the maximum bitmap size that can be edited is 2500 pixels. This limit is arbitrary and can easily be changed, but bitmap edit grid loading and, in particular, garbage collection become quite slow if the limit is a lot more than 2500 pixels. The gridMax constant sets max size. -
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lxnstack
A program to align and stack astronomical images.
... * sub-pixel precision (0.1 pixel for phase correlation and 0.01 pixel for manual alignment). * Automatic image derotation. * FITS file support (by installing the python2 package 'astropy') * Hot pixels suppression algorithm * CR2 files native support * Can load/save video * Grayscale RAW image support * Editing of result image's levels. * Light curve generation -
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scrimage
A unique python-based image editor
A unique python-based image editor with low-level control. It will be able to apply fairly complex mathematical operations to individual pixels based on the contents of a script or user input at a command line. It will then be able to apply those changes to the image for a unique effect. -
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PSP Tools
Set of tools for the Sony PSP (tm).
Set of tools for the Sony PSP (tm) for fixing and testing parts of the system. -
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EnKoDeur-Mixeur (EKD) is an open source software which makes videos, pictures and audio post-production. It can be also used to convert videos in many formats. It is written in python and use the PyQt4 bindings.
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24
Noisy Channel Simulator
Demonstrate errors in transmission of a file over a noisy channel.
...The program was intended to take monochrome bitmap files as input, so that each bit refers to a pixel in the image and thus, it would be easy to see errors in the output file, as some of the pixels would be flipped; however, it will work on any input file. -
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Shovel Library
Simple graphics, keyboard and mouse library with a C interface
is a collection of ultra-simple routines I've found useful for making small interactive graphics applications. === Functions include === * Window creation * 32-bit RGBA bitmap creation * Fast software based drawing routines (pixels, lines, text etc) * Mouse and keyboard input === Details === * Written in C * Python bindings provided * Permissive BSD licence * Win32 version currently. Linux and Mac planned. === Performance === Running on Windows XP on an Intel Core i3 530 (3.4 GHz): * Putpixel - 31 million per second * Rectangle fill - 11 billion pixels per second * Text render - 11 million characters per second (8 point, fixed width font)
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