This is an implementation of YOLOv8 and CRNN network for Scene Text Recognition task
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Updated
Aug 23, 2024 - Jupyter Notebook
This is an implementation of YOLOv8 and CRNN network for Scene Text Recognition task
[YOLOv5-Seg][CRNN-CTC][CCPD]License Plate Detect/Segment/Recog
This project offers an efficient method for identifying and recognizing handwritten text from images. Using a Convolutional Recurrent Neural Network (CRNN) for Optical Character Recognition (OCR), it effectively extracts text from images, aiding in the digitization of handwritten documents and automated text extraction.
This project implement basic OCR for Vietnamese from scratch with Pytorch, using CNN and BidirectionalLSTM
CRNN model for detecting and predicting the single-line text in a given image of TRSynth100k dataset.
pytorch implementation of crnn. A sample training of license plate is provided.
Implementation of the TCS ION Remote Internship RIO-125
Convolutional recurrent network in pytorch for vietnamese handwritting
Convert handwriting images into text (OCR)
Machine printed Hangul recognition based on CRNN
Application to spot and read text in shot images. Useful for blind people in supermarket.
OCR system built with U-Net models and CRNN.
Use Convolutional Recurrent Neural Network to recognize the Handwritten Word text image without pre segmentation into words or characters. Use CTC loss Function to train.
纯前端实现图片视频的文本检测,角度检测,文本识别等功能。 无需部署,打开即享。
Robust reading challenge on scanned receipts OCR and information extraction
Convolutional Recurrent Neural Network (CRNN) for reading Captchas(驗證碼)
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