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57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Created on Wed Jul 19 17:54:00 2017
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@author: sgnosh
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"""
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#!/usr/bin/python
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import sys
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import os
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import cv2
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import numpy as np
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print('\nDeeptextdetection.py')
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print(' A demo script of text box alogorithm of the paper:')
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print(' * Minghui Liao et al.: TextBoxes: A Fast Text Detector with a Single Deep Neural Network https://arxiv.org/abs/1611.06779\n')
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if (len(sys.argv) < 2):
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print(' (ERROR) You must call this script with an argument (path_to_image_to_be_processed)\n')
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quit()
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#if not cv2.text.cnn_config.caffe_backend.getCaffeAvailable():
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# print"The text module was compiled without Caffe which is the only available DeepCNN backend.\nAborting!\n"
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#
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# quit()
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# check model and architecture file existance
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if not os.path.isfile('textbox.caffemodel') or not os.path.isfile('textbox_deploy.prototxt'):
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print " Model files not found in current directory. Aborting"
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print " Model files should be downloaded from https://github.com/sghoshcvc/TextBox-Models"
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quit()
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cv2.text.cnn_config.caffe_backend.setCaffeGpuMode(True);
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pathname = os.path.dirname(sys.argv[0])
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img = cv2.imread(str(sys.argv[1]))
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textSpotter=cv2.text.textDetector_create(
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"textbox_deploy.prototxt","textbox.caffemodel")
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rects,outProbs = textSpotter.textDetectInImage(img);
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# for visualization
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vis = img.copy()
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# Threshold to select rectangles : All rectangles for which outProbs is more than this threshold will be shown
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thres = 0.6
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#Visualization
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for r in range(0,np.shape(rects)[0]):
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if outProbs[r] >thres:
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rect = rects[r]
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cv2.rectangle(vis, (rect[0],rect[1]), (rect[0]+rect[2],rect[1]+rect[3]), (255, 0, 0), 2)
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# cv2.rectangle(vis, (rect[0],rect[1]), (rect[0]+rect[2],rect[1]+rect[3]), (255, 255, 255), 1)
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#Visualization
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cv2.imshow("Text detection result", vis)
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cv2.waitKey(0) |