Search Results for "face recognition using python" - Page 7
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Showing 169 open source projects for "face recognition using python"
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FaceAccess Facial Recognition System
FaceAccess is an Access Control System based on Facial Recognition
With the growing need to exchange information and share resources, information security has become more important than ever in both the public and private sectors. Although many technologies have been developed to control access to files or resources, to enforce security policies, and to audit network usages, there does not exist a technology that can verify that the user who is using the system is the same person who logged in. FaceAccess provides a prototype implementation as a "login... -
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Bush Face Recognition
Face recognition using OpenCV
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Face Detection and Recognition over Commandline. simply move the detected Faces into the folder 'faces' and Faceregocgnition will show the name in a Commandline Window. Using Blob-Detection for better CPU-load. FaceDetection uses Eigen, Fisher and LBPHF. Part of EVAGui2 Project
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ProximityForest
Efficient Approximate Nearest Neighbors for General Metric Spaces
A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer... -
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EMGU Face Recognition
Using EMGU to perform Principle Component Analysis (PCA)
This article is designed to be the first in several to explain the use of the EMGU image processing wrapper. For more information on the EMGU wrapper please visit the EMGU website. You will start with 3 warnings for the references not being found. Expand the References folder within the solution explorer delete the 3 with yellow warning icons and Add fresh references to them. Face Recognition has always been a popular subject for image processing and this article builds upon the good... -
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Ivolution
Timelapse creation using Face Recognition
Ivolution is a face timelapse generator. Feed it with a bunch of images and it will generate a movie with your face centered on the screen. Ivolution uses face detection and modifies the images so that your face always keeps the same size and location over the movie. Images are processed in chronological order, so that you can see your face evoluate over time ! -
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Face Detect (JavaCV)
Face Detection and Facial Feature Extraction using JavaCV
A simple Face detection program using JavaCV and OpenCV . Implementing facial feature extraction and face recognition. -
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iFace is a human face recognition open scource project which developed by python. It is developed based on some code of PyVision project.
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Face recognition using BPNN. Contains 1.Face recognition using Back propagation neural network (customize code) code using matlab. 2. Face recognition using Back propagation network (builtin) code using matlab.Project closed for now,Adeel Raza Azeemi
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iFace is a human face recognition open scource project which developed by python. It is developed based on some code of PyVision project.
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Libface is a cross platform framework for developing face recognition algorithms and testing its performance.
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ASR-Builder provides an easy-to-use interface to the HTK toolkit, that allows users to build ASR systems. ASR-Builder provides a platform that performs house-keeping tasks when using HTK and also provides default training/testing/recognition scripts.
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The OpenCV DLLCapture project goal is to provide an easy way for using the Intel OpenCV library face recognition feature within custom built applications.
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The tre project is simply the author\'s attempt at mimicking artificial intelligence, using a home-made HTTP daemon and simple text recognition.
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wav2vec2-large-xlsr-53-portuguese
Portuguese ASR model fine-tuned on XLSR-53 for 16kHz audio input
...It achieves a WER of 11.3% (or 9.01% with LM) on Common Voice test data, demonstrating high accuracy for a single-language ASR model. Inference can be done using HuggingSound or via a custom PyTorch script using Hugging Face Transformers and Librosa. Training scripts and evaluation methods are open source and available on GitHub. It is released under the Apache 2.0 license and intended for ASR tasks in Brazilian Portuguese. -
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wav2vec2-large-xlsr-53-russian
Russian ASR model fine-tuned on Common Voice and CSS10 datasets
wav2vec2-large-xlsr-53-russian is a fine-tuned automatic speech recognition (ASR) model based on Facebook’s wav2vec2-large-xlsr-53 and optimized for Russian. It was trained using Mozilla’s Common Voice 6.1 and CSS10 datasets to recognize Russian speech with high accuracy. The model operates best with audio sampled at 16kHz and can transcribe Russian speech directly without a language model. It achieves a Word Error Rate (WER) of 13.3% and Character Error Rate (CER) of 2.88% on the Common Voice test set, with even better results when used with a language model. ... -
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Bio_ClinicalBERT
ClinicalBERT model trained on MIMIC notes for clinical NLP tasks
Bio_ClinicalBERT is a domain-specific language model tailored for clinical natural language processing (NLP), extending BioBERT with additional training on clinical notes. It was initialized from BioBERT-Base v1.0 and further pre-trained on all clinical notes from the MIMIC-III database (~880M words), which includes ICU patient records. The training focused on improving performance in tasks like named entity recognition and natural language inference within the healthcare domain. Notes were... -
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mms-300m-1130-forced-aligner
CTC-based forced aligner for audio-text in 158 languages
mms-300m-1130-forced-aligner is a multilingual forced alignment model based on Meta’s MMS-300M wav2vec2 checkpoint, adapted for Hugging Face’s Transformers library. It supports forced alignment between audio and corresponding text across 158 languages, offering broad multilingual coverage. The model enables accurate word- or phoneme-level timestamping using Connectionist Temporal Classification (CTC) emissions. Unlike other tools, it provides significant memory efficiency compared to the...
