Showing 116 open source projects for "time code"

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  • 1
    DensePose

    DensePose

    A real-time approach for mapping all human pixels of 2D RGB images

    ...This enables detailed understanding of human shape, motion, and surface appearance directly from images or videos. The repository includes the DensePose network architecture, training code, pretrained models, and dataset tools for annotation and visualization. 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.
    Downloads: 161 This Week
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  • 2
    Keepsake

    Keepsake

    Version control for machine learning

    Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage. You can get the data back out using the command-line interface or a notebook.
    Downloads: 0 This Week
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  • 3
    Semantic Segmentation in PyTorch

    Semantic Segmentation in PyTorch

    Semantic segmentation models, datasets & losses implemented in PyTorch

    Semantic segmentation models, datasets and losses implemented in PyTorch. PyTorch and Torchvision needs to be installed before running the scripts, together with PIL and opencv for data-preprocessing and tqdm for showing the training progress. PyTorch v1.1 is supported (using the new supported tensoboard); can work with earlier versions, but instead of using tensoboard, use tensoboardX. Poly learning rate, where the learning rate is scaled down linearly from the starting value down to zero...
    Downloads: 0 This Week
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  • 4
    Tabnine

    Tabnine

    Vim client for TabNine

    Tabnine is an AI-powered code completion extension trusted by millions of developers around the world. Whether you’re just getting started as a developer or if you’ve been doing it for decades, Tabnine will help you code twice as fast with half the keystrokes – all in your favorite IDE. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or content assist, you probably already know that it can save you tons of time, easily cutting your keystrokes in half. ...
    Downloads: 12 This Week
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  • 5
    BudgetML

    BudgetML

    Deploy a ML inference service on a budget in 10 lines of code

    Deploy a ML inference service on a budget in less than 10 lines of code. BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST, Uvicorn/Gunicorn, backend servers etc., that are simply not within the scope of a typical data scientist. ...
    Downloads: 0 This Week
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  • 6
    Linux-Intelligent-Ocr-Solution

    Linux-Intelligent-Ocr-Solution

    Easy-OCR solution and Tesseract trainer for GNU/Linux

    Linux-intelligent-ocr-solution Lios is a free and open source software for converting print in to text using either scanner or a camera, It can also produce text out of scanned images from other sources such as Pdf, Image, Folder containing Images or screenshot. Program is given total accessibility for visually impaired. A Tesseract Trainer GUI is also shipped with this package. Forum : https://groups.google.com/forum/#!forum/lios Video Tutorial :...
    Downloads: 9 This Week
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  • 7
    textgenrnn

    textgenrnn

    Easily train your own text-generating neural network

    ...Train models on a GPU and then use them to generate text with a CPU. Utilize a powerful CuDNN implementation of RNNs when trained on the GPU, which massively speeds up training time as opposed to typical LSTM implementations. Train the model using contextual labels, allowing it to learn faster and produce better results in some cases.
    Downloads: 0 This Week
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  • 8
    gpt2-client

    gpt2-client

    Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.

    ...Finally, gpt2-client is a wrapper around the original gpt-2 repository that features the same functionality but with more accessiblity, comprehensibility, and utilty. You can play around with all four GPT-2 models in less than five lines of code. Install client via pip. The generation options are highly flexible. You can mix and match based on what kind of text you need generated, be it multiple chunks or one at a time with prompts.
    Downloads: 0 This Week
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  • 9
    captcha_break

    captcha_break

    Identification codes

    ...It supports image verification codes and voice verification codes. We use its function of generating image verification 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.
    Downloads: 1 This Week
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  • 10
    automl-gs

    automl-gs

    Provide an input CSV and a target field to predict, generate a model

    Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model...
    Downloads: 0 This Week
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  • 11
    DetectAndTrack

    DetectAndTrack

    The implementation of an algorithm presented in the CVPR18 paper

    DetectAndTrack is the reference implementation for the CVPR 2018 paper “Detect-and-Track: Efficient Pose Estimation in Videos,” focusing on human keypoint detection and tracking across video frames. The system combines per-frame pose detection with a tracking mechanism to maintain identities over time, enabling efficient multi-person pose estimation in video. Code and instructions are organized to replicate paper results and to serve as a starting point for researchers working on pose in video. Although the repo has been archived and is now read-only, its issue tracker and artifacts remain useful for understanding implementation details and experimental settings. ...
    Downloads: 0 This Week
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  • 12
    Tangent

    Tangent

    Source-to-source debuggable derivatives in pure Python

    Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative code just like the rest of your program. Tangent is useful to researchers and students who not only want to write their models in Python, but also read and debug automatically-generated derivative code without sacrificing speed and flexibility. ...
    Downloads: 0 This Week
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  • 13
    Five video classification methods

    Five video classification methods

    Code that accompanies my blog post outlining five video classification

    Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images. This reduces model complexity, training time, and...
    Downloads: 0 This Week
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  • 14
    Universe

    Universe

    Software for measuring and training an AI's general intelligence

    ...This is the universe open-source library, which provides a simple Gym interface to each Universe environment. Universe allows anyone to train and evaluate AI agents on an extremely wide range of real-time, complex environments. Universe makes it possible for any existing program to become an OpenAI Gym environment, without needing special access to the program's internals, source code, or APIs. 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. ...
    Downloads: 2 This Week
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  • 15
    RoboComp
    RoboComp is a robotics framework providing a set of open-source, distributed, real-time robotic and artificial vision software components and the necessary tools to create and manage them.
    Downloads: 0 This Week
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  • 16

    Game of Turmites

    Conway's Game of Life and Turmites Combined!

    ...It's all very randomly generated, and there is no way for any user input. I'll consider putting some in later. I had been wanting to make the Game of Life for some time as well as make some kind of genetic algorithm based code. So, here is what I came up with. While this may just seem like simplify a graphical display of what boredom looks like... well, it really doesn't go much past that point. If you Don't know what Conway's game of life is: It's the Black (Or white, I may have changed them) cells that follow a simple set of instructions based on the state of its adjacent cells. ...
    Downloads: 0 This Week
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