handwriting-recognition

Transform an image of handwritten notes to text [closed]

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问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 3 months ago . I have hundreds of images of handwritten notes. They were written from different people but they are in sequence so you know that for example person1 wrote img1.jpg -> img100.jpg . The style of handwriting varies a lot from person to person but there are parts of the notes which

Improve real-life results of neural network trained with mnist dataset

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问题 I've built a neural network with keras using the mnist dataset and now I'm trying to use it on photos of actual handwritten digits. Of course I don't expect the results to be perfect but the results I currently get have a lot of room for improvement. For starters I test it with some photos of individual digits written in my clearest handwriting. They are square and they have the same dimensions and color as the images in the mnist dataset. They are saved in a folder called individual_test

Increasing Label Error Rate (Edit Distance) and Fluctuating Loss?

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问题 I am training a handwriting recognition model of this architecture: { "network": [ { "layer_type": "l2_normalize" }, { "layer_type": "conv2d", "num_filters": 16, "kernel_size": 5, "stride": 1, "padding": "same" }, { "layer_type": "max_pool2d", "pool_size": 2, "stride": 2, "padding": "same" }, { "layer_type": "l2_normalize" }, { "layer_type": "dropout", "keep_prob": 0.5 }, { "layer_type": "conv2d", "num_filters": 32, "kernel_size": 5, "stride": 1, "padding": "same" }, { "layer_type": "max

Android handwriting recognition [closed]

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问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 5 years ago . I need to analyse android handwriting recognition SDK's. Can anybody tell me what SDK's are available on the market. I've found MyScript from VisionObjects, but I cant find any download link from the SDK, because I need to test to see the accuracy. 回答1: I'm working for MyScript, you can try online recognition

Text extraction and segmentation open CV

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问题 I've never used OpenCV before, but I'm trying to write my neural network system to recognize text and I need some tool for text extraction/ segmentation. How can I use java OpenCV to preprocess and segmentate an image containing text. I don't need to recognize the text, I just need to get each letter in a separate image. Something like this : 回答1: Try this code .No need of OpenCV import java.awt.image.BufferedImage; import java.util.ArrayList; import java.util.List; import org.neuroph.imgrec

Detect space between text (OpenCV, Python)

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问题 I have the following code (which is in fact just 1 part of 4 needed to run all the project I am working on..): #python classify.py --model models/svm.cpickle --image images/image.png from __future__ import print_function from sklearn.externals import joblib from hog import HOG import dataset import argparse import mahotas import cv2 ap = argparse.ArgumentParser() ap.add_argument("-m", "--model", required = True, help = "path to where the model will be stored") ap.add_argument("-i", "--image",

Handwriting gesture recognition for multiple characters android

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问题 I have implemented handwriting gestures for android character recognition for a single character as shown here. But i want to read multiple characters at a single time, .i.e Android . I am able to read a single character by the following implementation. But, I need help to recognize a complete word like Android at the same time. My implementation so far is shown below. GestureLibrary mLibrary; @Override protected void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState);

Hand-written custom shapes recognition

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问题 I am trying to implement a small recognition program, which should take an image with hand-written shapes as an input (shape objects can be nested), and tell me which shapes it consists of, their type, size and at least coordinates of one point in a shape. Where should I start? Maybe, some machine learning technics could be used for such a task? I've tried to look for some examples or tutorials dealing with handwriting recognition of custom shapes, but haven't found something worth looking at

Not Converging CTC Loss and Fluctuating Label Error Rate (Edit Distance) on Single Example?

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问题 I am trying to overfit a handwriting recognition model of this architecture: features = slim.conv2d(features, 16, [3, 3]) features = slim.max_pool2d(features, 2) features = mdrnn(features, 16) features = slim.conv2d(features, 32, [3, 3]) features = slim.max_pool2d(features, 2) features = mdrnn(features, 32) features = slim.conv2d(features, 64, [3, 3]) features = slim.max_pool2d(features, 2) features = mdrnn(features, 64) features = slim.conv2d(features, 128, [3, 3]) features = mdrnn(features,

Increasing Label Error Rate (Edit Distance) and Fluctuating Loss?

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I am training a handwriting recognition model of this architecture: { "network": [ { "layer_type": "l2_normalize" }, { "layer_type": "conv2d", "num_filters": 16, "kernel_size": 5, "stride": 1, "padding": "same" }, { "layer_type": "max_pool2d", "pool_size": 2, "stride": 2, "padding": "same" }, { "layer_type": "l2_normalize" }, { "layer_type": "dropout", "keep_prob": 0.5 }, { "layer_type": "conv2d", "num_filters": 32, "kernel_size": 5, "stride": 1, "padding": "same" }, { "layer_type": "max_pool2d", "pool_size": 2, "stride": 2, "padding": "same" }, { "layer_type": "l2_normalize" }, { "layer_type"