Search Results for "video-making" - Page 5
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Showing 175 open source projects for "video-making"
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...It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that can be adapted for custom datasets, making it useful for experimenting with retrieval systems in computer vision. By leveraging CNN architectures, the project showcases how learned embeddings can capture semantic similarity across varied images. This resource serves as both an educational reference and a foundation for further exploration in image retrieval research.
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molten
A minimal, extensible, fast and productive framework
molten is a minimal, extensible, fast and productive framework for building HTTP APIs with Python. molten can automatically validate requests according to predefined schemas, ensuring that your handlers only ever run if given valid input. Schemas are PEP484-compatible, which means mypy and molten go hand-in-hand, making your code more easy to maintain. Schema instances are automatically serializable and you can pick and choose which fields to exclude from responses and requests. Write clean, decoupled code by leveraging DI. Define components for everything from settings to DB access and business logic, test them in isolation and swap them out as needed. ... -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
...It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. For students preparing for technical interviews, self-learners brushing up on fundamentals, or developers wanting to understand algorithm internals, this repository provides ready-to-run examples, and can serve as a sandbox to experiment, benchmark, or adapt code. Because it’s in pure Python, it’s easy to read and modify, making it accessible even to those with modest programming experience. ... -
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Consistent Depth
We estimate dense, flicker-free, geometrically consistent depth
...This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. The project can process challenging hand-held video footage, including those with moderate dynamic motion, making it practical for real-world usage. -
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srt2vobsub
A command-line tool that converts text subtitles to vobsub
A command line tool for Linux and other Unix-like systems that generates a pair of .idx/.sub vobsub subtitles files from textual subtitles. -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights both fixed and learnable sparsity patterns that trade off computational cost and model expressiveness. By enabling tractable training on longer contexts, the project opened the door to applications in large-scale text and image generation. ... -
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macOS Simple KVM
Tools to set up a quick macOS VM in QEMU, accelerated by KVM
...The repository includes tools for preparing installation media, configuring virtual hardware, and managing VM launch scripts. By using KVM acceleration, the virtual machine runs with near-native performance, making it useful for testing, development, or personal experimentation. The project also supports GPU passthrough and other advanced configurations for users who want a more optimized macOS VM environment. While primarily intended for educational and testing purposes, it demonstrates how macOS can be virtualized outside of Apple hardware. -
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Higher
higher is a pytorch library
...The library introduces utilities that convert standard torch.nn.Module instances into “stateless” functional forms, so parameter updates can be treated as differentiable operations. It also provides differentiable implementations of common optimizers like SGD and Adam, making it possible to backpropagate through an arbitrary number of inner-loop optimization steps. By offering a clear and flexible interface, higher simplifies building complex learning algorithms that require gradient tracking across multiple update levels. Its design ensures compatibility with existing PyTorch models. -
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Top Deep Learning Projects
A list of popular github projects related to deep learning
...This way one can survey state-of-the-art projects, find learning resources, or pick stable libraries for production — without manually sifting through hundreds of repos. The repository is openly licensed under MIT, making it easy to fork, extend, or contribute updates (e.g. adding newer projects or reordering by recent popularity). -
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SageMaker Containers
Create SageMaker-compatible Docker containers
...A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Very often, an entry point needs additional information from the container that is not available in hyperparameters. SageMaker Containers writes this information as environment variables that are available inside the script. -
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Tensor2Tensor
Library of deep learning models and datasets
...In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and compare the results. Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. T2T was developed by researchers and engineers in the Google Brain team and a community of users. It is now deprecated, we keep it running and welcome bug-fixes, but encourage users to use the successor library Trax. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc. -
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API Correios
API correios.com.br in Python
pycorreios is a Python library aimed at interacting with Brazil’s postal service (Correios) APIs, making it easier for developers to track shipments, calculate postage, query service availability, and integrate with Brazilian e-commerce flows. The library abstracts the raw SOAP or REST endpoints exposed by Correios, providing Pythonic methods to perform common tasks like tracking a package by its code or computing shipping cost/lead time between postal codes. -
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SageMaker Chainer Containers
Docker container for running Chainer scripts to train and host Chainer
SageMaker Chainer Containers is an open-source library for making the Chainer framework run on Amazon SageMaker. This repository also contains Dockerfiles which install this library, Chainer, and dependencies for building SageMaker Chainer images. Amazon SageMaker utilizes Docker containers to run all training jobs & inference endpoints. The Docker images are built from the Dockerfiles specified in Docker/. -
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Pinject
A pythonic dependency injection library
...Its container supports constructor injection and fine-grained scoping so you can share expensive resources while keeping tests isolated. The library leans on Python’s introspection to minimize boilerplate, making it natural to adopt in codebases that already rely on type hints or keyword arguments. Because bindings are just Python functions and classes, refactoring remains straightforward and the DI graph is easy to reason about. Pinject is particularly useful for medium-to-large services where configuration, logging, data clients, and business logic need clean separation without resorting to manual plumbing. -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out... -
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Twint
An advanced Twitter scraping & OSINT tool written in Python
Twint is an advanced open-source Twitter scraping and OSINT tool written in Python that extracts tweets, user data, followers, likes, and more—without relying on Twitter’s API—making it highly useful for researchers, analysts, and hobbyists who want to bypass rate limits and access public Twitter data. -
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Python Patterns
A collection of design patterns/idioms in Python
Python-Patterns is a repository collecting implementations of many classical design patterns and idioms, written in Python. It serves as an educational resource: showing how to implement creational, structural, behavioral, testability, and other patterns in a Pythonic style (or sometimes less so), illustrating trade-offs, different styles, and use cases. It’s intended for learners or developers interested in software architecture or design, rather than as a production library. Includes... -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
...The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs. -
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Webterminal bastion server
ssh rdp vnc telnet sftp bastion/jump web putty xshell terminal
...For now it supports almost 90% of remote management protocols such as vnc, ssh, RDP, telnet, sftp... It supports the possibility to monitor and record user actions when users use this project to manage their server! You can also replay the user action such as a video. Hope you enjoy it. Webterminal helper support (use your favorite tools to manage and connect server) VNC, RDP, SFTP Remote file browser (download, delete, update and upload files). Ubuntu webterminal helper support. Mac webterminal helper support. Windows webterminal helper support. Commercial version provides mstsc helper. -
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captcha_break
Identification codes
...First, we set our verification code format to numbers and capital letters, and generate a string of verification codes. It is well known that tensorflow occupies all video memory by default, which is not conducive to us conducting multiple experiments at the same time, so we can use the following code when tensorflow uses the video memory it needs instead of directly occupying all video memory. -
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Defox text to speech and downloader
Written or imported text offline read or online download.
...Description : • Installation setup with two languages (English, French) • Two areas called text reading and speech downloading • Many languages supported to download center Note 1: I'm a student yet and I'm not in the software designing industry. Therefore maybe I haven't software making skills. I'm worried about that. ! Note 2 : When you double click on the software maybe it will get some seconds to open. That's not my fault. I used Python language to make this software and Python was not supported speedy to modern computers. -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. ... -
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Invenio
Invenio digital library framework
...Developed by CERN, it is designed to manage, index, and provide access to metadata-rich content such as publications, datasets, and multimedia files. Invenio provides a modular architecture, making it suitable for libraries, archives, and research institutions. -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
...The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This capability can often be leveraged by sending users to the same URL that your visualization code uses internally to load the data. While DRP is primarily a data API, it also provides a default collection of interactive visualizations through the @wq/chart library, and a @wq/pandas loader to facilitate custom JavaScript charts that work well with CSV output served by DRP. ...
