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Search results for image processing data augmentation
data-augmentation
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image-processing
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12 search results found
Dali
⭐
4,926
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
Fastdup
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1,313
fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.
Augraphy
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258
Augmentation pipeline for rendering synthetic paper printing, faxing, scanning and copy machine processes
Pilgram
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95
A python library for instagram filters
Augmennt
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22
Augmentations for Neural Networks. Implementation of Torchvision's transforms using OpenCV and additional augmentations for super-resolution, restoration and image to image translation.
Torchaug
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20
Library to perform efficient vision data augmentations for CPU/GPU per-sample/batched data.
Skin_disease_ai
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18
A Python-based computer vision and AI system for skin disease recognition and diagnosis. Led end-to-end project pipeline, including data gathering, preprocessing, and training models. Utilized Keras, TensorFlow, OpenCV, and other libraries for image processing and CNN models, showcasing expertise in deep learning and machine learning techniques.
Kopikatapi
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15
KopikatAPI is Python library for interacting with the Kopikat API.
Unets
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14
Implemenation of UNets for Lung Segmentation
Salty Wet Man
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10
Online content control dashboard. Binary classification filter/flag for inappropriate NSFW content with automated reporting
Automated Scoring Of Handwritten Test Papers
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8
Extract handwritten information like name, student ID and then recognize them with CRNN-CTC-Attention. Using lexicon search on class list to help teacher on updating score faster
Hand Gesture Recognition
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6
🖐 An implementation of a machine learning model for detecting and recognizing hand signs (0-5) accurately using Python. The project pipeline involves the following modules: Preprocessing, Feature Extraction, Model selection and training, and finally performance analysis.
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1-12 of 12 search results
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