Showing 8 open source projects for "compare images"

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  • 1
    Unstract

    Unstract

    No-code LLM Platform to launch APIs and ETL Pipelines

    ...Its platform works with a broad variety of file types — from PDFs and spreadsheets to images — and includes integrations with databases, cloud storage providers, and vector databases.
    Downloads: 2 This Week
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  • 2
    SAM 2

    SAM 2

    The repository provides code for running inference with SAM 2

    ...It retains the core promptable interface—accepting points, boxes, or masks—but incorporates architectural and training enhancements to produce higher-fidelity masks, better boundary adherence, and robustness to complex scenes. The updated model is optimized for faster inference and lower memory use, enabling real-time interactivity even on larger images or constrained hardware. SAM2 comes with pretrained weights and easy-to-use APIs, enabling developers and researchers to integrate promptable segmentation into annotation tools, vision pipelines, or downstream tasks. The project also includes scripts and notebooks to compare SAM2 against SAM on edge cases, benchmarks showing improvements, and evaluation suites to measure mask quality metrics like IoU and boundary error.
    Downloads: 3 This Week
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  • 3
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    ...You should expect it to be 33% faster and save up to 40% memory. Aim is an open-source experiment tracker that logs your training runs, and enables a beautiful UI to compare them.
    Downloads: 0 This Week
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  • 4
    StudioGAN

    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,...
    Downloads: 0 This Week
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  • 5
    Alfi Face

    Alfi Face

    Face Recognition based Attendance System for school, college...

    ALFI FACE uses facial recognition technology to record the attendance through a digital camera that detects and recognizes faces and compare the faces with students’ faces images stored in faces database. Once the recognized face matches a stored image, attendance is marked in attendance database for that person. Note: While adding a new student you have to click on" Train the Recognizer" button . In excel sheet dates are "#" so that no one can change the dates.
    Downloads: 0 This Week
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  • 6
    Perceptual Similarity Metric and Dataset

    Perceptual Similarity Metric and Dataset

    LPIPS metric. pip install lpips

    ...To answer these questions, we introduce a new dataset of human perceptual similarity judgments. We systematically evaluate deep features across different architectures and tasks and compare them with classic metrics. We find that deep features outperform all previous metrics by large margins on our dataset.
    Downloads: 0 This Week
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  • 7

    TensorImage

    Image classification library for easily training and deploying models

    (Visit our github repository at https://github.com/TensorImage/tensorimage for more information) TensorImage is and open source package for image classification. It has a wide range of data augmentation operations that can be performed over training data to prevent overfitting and increase testing accuracy. TensorImage is easy to use and manage as all files, trained models and data are organized within a workspace directory, which you can change at any time in the configuration file,...
    Downloads: 0 This Week
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  • 8
    LearningToCompare_FSL

    LearningToCompare_FSL

    Learning to Compare: Relation Network for Few-Shot Learning

    LearningToCompare_FSL is a PyTorch implementation of the “Learning to Compare: Relation Network for Few-Shot Learning” paper, focusing on the few-shot learning experiments described in that work. The core idea implemented here is the relation network, which learns to compare pairs of feature embeddings and output relation scores that indicate whether two images belong to the same class, enabling classification from only a handful of labeled examples.
    Downloads: 0 This Week
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