Search Results for "image" - Page 23
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Showing 1099 open source projects for "image"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Crunch PNG
Insane(ly slow but wicked good) PNG image optimization
Crunch is a tool for lossy PNG image file optimization. It combines selective bit depth, color type, and color palette reduction with zopfli DEFLATE compression algorithm encoding using the pngquant and zopflipng PNG optimization tools. This approach leads to a significant file size gain relative to lossless approaches at the expense of a relatively modest decrease in image quality. -
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StudioGAN
StudioGAN is a Pytorch library providing implementations of networks
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation. StudioGAN aims to offer an identical playground for modern GANs so that machine learning researchers can readily compare and analyze a new idea. Moreover, StudioGAN provides an unprecedented-scale benchmark for generative models. The benchmark includes results from GANs (BigGAN-Deep, StyleGAN-XL), auto-regressive models (MaskGIT, RQ-Transformer), and Diffusion models (LSGM++, CLD-SGM, ADM-G-U). ... -
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AI Atelier
Based on the Disco Diffusion, version of the AI art creation software
Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. When a modified version is used to provide a service over a network, the complete source code of the modified version must be made available. ... -
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µPipenv
A lightweight wrapper for pip to support requirements.txt
...Designed for containerized Python applications but not limited to them. if requirements.txt state all the packages in a pinned version with hashes (e.g. pip-tools), micropipenv installs packages with a possible fallback if the installation order is relevant. micropipenv does not substitute Poetry it rather complements it for containerized deployments where the size of the container image and software shipped with it matters. I would like to have a tool that "rules them all" - one lightweight tool to support all Python dependency lock file managers (pip-tools, Poetry, Pipenv) and lets users decide what they want to use when deploying Python applications in containerized environments (e.g. Kubernetes, OpenShift, ...). -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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RQ-Transformer
Implementation of RQ Transformer, autoregressive image generation
...I also think there is something deeper going on, and have generalized this to any number of dimensions. You can use it by importing the HierarchicalCausalTransformer. For autoregressive (AR) modeling of high-resolution images, vector quantization (VQ) represents an image as a sequence of discrete codes. A short sequence length is important for an AR model to reduce its computational costs to consider long-range interactions of codes. However, we postulate that previous VQ cannot shorten the code sequence and generate high-fidelity images together in terms of the rate-distortion trade-off. -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the full image—making pretraining computationally efficient. ... -
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ImaGC
image editor
an easy way to personalize images. -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series forecasting framework. ... -
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Unet
Source code for unet-pytorch, which can train its own model
...The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. It is useful for developers and students who want a clear U-Net implementation for segmentation experiments, custom masks, and biomedical-style image analysis. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Django REST Framework User
This Django User Model is customised user model
...REST API to login with OTP (Same API endpoint as for OTP Verification; Set is_login: true while sending JSON request). OTP Verification for mobile and email, API to register / login with OTP (no pre-registration required) API to set user’s profile image. Mail-sending feature upon successful registration. SMS sending feature upon successful registration. Change password, update profile, and generic configuration based on settings.py. -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases, such as landmark detection and mobile photo analysis with label and face detection, so developers can see how Vision API outputs are consumed in real interfaces and workflows. ... -
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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. -
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GLIDE (Text2Im)
GLIDE: a diffusion-based text-conditional image synthesis model
...It demonstrates how diffusion-based generative models can be conditioned on text to produce highly detailed and coherent visual outputs. The repository provides both model code and pretrained checkpoints, making it possible for researchers and developers to experiment with text-to-image synthesis. GLIDE includes advanced techniques such as classifier-free guidance, which improves the quality and alignment of generated images with the input text. The project also offers sampling scripts and utilities for exploring how diffusion models can be applied to multimodal tasks. As one of the early diffusion-based text-to-image systems, glide-text2im laid important groundwork for later advances in generative AI research. -
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CCTV Frame Timestamp Extractor
CCTV Footage Timestamp Search Tool
...Link to paper: https://link.springer.com/chapter/10.1007/978-3-031-10078-9_8 The project has been divided into four modules: Framextract.py- Extracts frames from video footages Reconstruct.py- Attempts to repair unplayable video by extracting the frames. framestitch.py- Attempts to construct video using frames extracted from unplayable video. OCR.py- Performs image preprocessing & OCR on the extracted frames. -
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Cisco IOS Device Manager
Cisco IOS Device Management (backup, update image, save conf, reboot)
INFORMATION This program can be used for the following: - To collecting Cisco device information like: hostname, serial, model, IOS image, version, uptime, free memory (to CSV) - To enable the SCP service on the device (automaticly before file transfers) - To make a backup of the running-config and startup-config with SCP (with built-in MD5 hash comparison check) no TFTP/SFTP server needed. - To save the running-config to the startup-config (write memory) - To transfer a new image to the device with SCP (with built-in MD5 hash comparison check) - To change the boot target to the new image (boot system flash:/) It has got the following features: - Error handling - information and error logging to log file (Log will be appended) - information and error logging to CSV file (Log will be overwritten each run) - Transfers retry 3 times - MD5 checks after file transfers to be sure the file is transferred without problems -
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Fashion-MNIST
A MNIST-like fashion product database
Fashion-MNIST is an open-source dataset created by Zalando Research that provides a standardized benchmark for image classification algorithms in machine learning. The dataset contains grayscale images of fashion products such as shirts, shoes, coats, and bags, each labeled according to its clothing category. It was designed as a direct replacement for the original MNIST handwritten digits dataset, maintaining the same structure and image size so that researchers could easily switch datasets without modifying their experimental pipelines. ... -
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DeepLearning Tutorial
Deep Learning Tutorial, Excellent Articles, Deep Learning Tutorial
DeepLearning is an open-source repository that aggregates tutorials, articles, and educational resources related to deep learning and machine learning. The project is designed as a knowledge collection that helps beginners understand neural networks, deep learning architectures, and fundamental machine learning concepts. It contains curated learning materials covering topics such as feedforward neural networks, activation functions, backpropagation algorithms, optimization methods, and... -
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Deep Daze
Simple command line tool for text to image generation
...Simply specify the path to the image you wish to use, and optionally the number of initial training steps. We can also feed in an image as an optimization goal, instead of only priming the generator network. Deepdaze will then render its own interpretation of that image. The regular mode for texts only allows 77 tokens. If you want to visualize a full story/paragraph/song/poem, set create_story to True. -
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AugLy
A data augmentations library for audio, image, text, and video
...We designed AugLy to include many specific data augmentations that users perform in real life on internet platforms like Facebook's -- for example making an image into a meme, overlaying text/emojis on images/videos, reposting a screenshot from social media. While AugLy contains more generic data augmentations as well, it will be particularly useful to you if you're working on a problem like copy detection, hate speech detection, etc. -
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Tensorflow Transformers
State of the art faster Transformer with Tensorflow 2.0
...These models can be applied on text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like speech recognition and audio classification. Faster AutoReggressive Decoding, TFlite support, creating TFRecords is simple. Auto-Batching tf.data.dataset or tf.ragged tensors. Everything is dictionary (inputs and outputs) Multiple mask modes like causal, user-defined, prefix. tensorflow-text tokenizer support. ... -
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LayoutParser
A Unified Toolkit for Deep Learning Based Document Image Analysis
With the help of state-of-the-art deep learning models, Layout Parser enables extracting complicated document structures using only several lines of code. This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection. The full list of layout models currently available in Layout Parser.... -
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Deep Feature Rotation Multimodal Image
Implementation of Deep Feature Rotation for Multimodal Image
...Prepare your content image and style image. I provide some in the data/content and data/style and you can try to use them easily. We provide a visual comparison between other rotation angles that do not appear in the paper. The rotation angles will produce a very diverse number of outputs. This has proven the effectiveness of our method with other methods. -
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GANformer
Generative Adversarial Transformers
This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of each in light of the other and encourage the emergence of compositional representations of objects and scenes. ... -
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Interactive Deep Colorization
Deep learning software for colorizing black and white images
...The project includes both the older Caffe-based implementation and a more recent PyTorch backend, giving flexibility depending on user preference and infrastructure. Because it handles image reading, hint interpretation, and color mapping internally, users don’t need to build the colorization pipeline from scratch: they only need to supply grayscale images (and optionally hints), and the software produces a full-color version. -
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YOLOv3
Object detection architectures and models pretrained on the COCO data
...Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an expert. Students love YOLOv5 for its simplicity and there are many quickstart examples for you to get started within seconds. Export and deploy your YOLOv5 model with just 1 line of code. There are also loads of quickstart guides and tutorials available to get your model where it needs to be. ...
