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add ctc reader #618

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Feb 7, 2018
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97 changes: 97 additions & 0 deletions fluid/ocr_recognition/ctc_reader.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,97 @@
import os
import cv2
import numpy as np
from PIL import Image

from paddle.v2.image import load_image


class DataGenerator(object):
def __init__(self):
pass

def train_reader(self, img_root_dir, img_label_list, batchsize):
'''
Reader interface for training.

:param img_root_dir: The root path of the image for training.
:type file_list: str

:param img_label_list: The path of the <image_name, label> file for training.
:type file_list: str

'''

img_label_lines = []
if batchsize == 1:
to_file = "tmp.txt"
cmd = "cat " + img_label_list + " | awk '{print $1,$2,$3,$4;}' | shuf > " + to_file
print "cmd: " + cmd
os.system(cmd)
print "finish batch shuffle"
img_label_lines = open(to_file, 'r').readlines()
else:
to_file = "tmp.txt"
#cmd1: partial shuffle
cmd = "cat " + img_label_list + " | awk '{printf(\"%04d%.4f %s\\n\", $1, rand(), $0)}' | sort | sed 1,$((1 + RANDOM % 100))d | "
#cmd2: batch merge and shuffle
cmd += "awk '{printf $2\" \"$3\" \"$4\" \"$5\" \"; if(NR % " + str(
batchsize) + " == 0) print \"\";}' | shuf | "
#cmd3: batch split
cmd += "awk '{if(NF == " + str(
batchsize
) + " * 4) {for(i = 0; i < " + str(
batchsize
) + "; i++) print $(4*i+1)\" \"$(4*i+2)\" \"$(4*i+3)\" \"$(4*i+4);}}' > " + to_file
print "cmd: " + cmd
os.system(cmd)
print "finish batch shuffle"
img_label_lines = open(to_file, 'r').readlines()

def reader():
sizes = len(img_label_lines) / batchsize
for i in range(sizes):
result = []
sz = [0, 0]
for j in range(batchsize):
line = img_label_lines[i * batchsize + j]
# h, w, img_name, labels
items = line.split(' ')

label = [int(c) for c in items[-1].split(',')]
img = Image.open(os.path.join(img_root_dir, items[
2])).convert('L') #zhuanhuidu
if j == 0:
sz = img.size
img = img.resize((sz[0], sz[1]))
img = np.array(img) - 127.5
img = img[np.newaxis, ...]
result.append([img, label])
yield result

return reader

def test_reader(self, img_root_dir, img_label_list):
'''
Reader interface for inference.

:param img_root_dir: The root path of the images for training.
:type file_list: str

:param img_label_list: The path of the <image_name, label> file for testing.
:type file_list: list
'''

def reader():
for line in open(img_label_list):
# h, w, img_name, labels
items = line.split(' ')

label = [int(c) for c in items[-1].split(',')]
img = Image.open(os.path.join(img_root_dir, items[2])).convert(
'L')
img = np.array(img) - 127.5
img = img[np.newaxis, ...]
yield img, label

return reader