add dataset

dataset/.gitignore

@@ -0,0 +1 @@
+hwdb_raw/

dataset/casia_hwdb.py

@@ -59,28 +59,25 @@ def resize_padding_or_crop(target_size, ori_img, padding_value=255):
 if __name__ == "__main__":
     gnt = CASIAHWDBGNT('samples/1001-f.gnt')
 
-    full_img = np.zeros([800, 800], dtype=np.uint8)
+    full_img = np.zeros([900, 900], dtype=np.uint8)
     charset = []
     i = 0
     for img, tagcode in gnt.get_data_iter():
-        cv2.imshow('rr', img)
-        
+        # cv2.imshow('rr', img)
         try:
-            label = struct.pack('>H', tagcode).decode('gb2312')
-            cv2.waitKey(0)
-            print(label)
-            # img_padded = resize_padding_or_crop(80, img)
-            # col_idx = i%10
-            # row_idx = i//10
-            # full_img[row_idx*80:(row_idx+1)*80, col_idx*80:(col_idx+1)*80] = img_padded
-            # charset.append(label.replace('\x00', ''))
-            # if i >= 99:
-            #     cv2.imshow('rrr', full_img)
-            #     cv2.imwrite('sample.png', full_img)
-            #     cv2.waitKey(0)
-            #     print(charset)
-            #     break
-            # i += 1
+            label = struct.pack('>H', tagcode).decode('gb2312')            
+            img_padded = resize_padding_or_crop(90, img)
+            col_idx = i%10
+            row_idx = i//10
+            full_img[row_idx*90:(row_idx+1)*90, col_idx*90:(col_idx+1)*90] = img_padded
+            charset.append(label.replace('\x00', ''))
+            if i >= 99:
+                cv2.imshow('rrr', full_img)
+                cv2.imwrite('sample.png', full_img)
+                cv2.waitKey(0)
+                print(charset)
+                break
+            i += 1
         except Exception as e:
             # print(e.with_traceback(0))
             print('decode error')

dataset/convert_to_tfrecord.py

@@ -0,0 +1,83 @@
+"""
+generates HWDB data into tfrecord
+"""
+import struct
+import numpy as np
+import cv2
+from alfred.utils.log import logger as logging
+import tensorflow as tf
+import glob
+
+
+class CASIAHWDBGNT(object):
+    """
+    A .gnt file may contains many images and charactors
+    """
+
+    def __init__(self, f_p):
+        self.f_p = f_p
+
+    def get_data_iter(self):
+        header_size = 10
+        with open(self.f_p, 'rb') as f:
+            while True:
+                header = np.fromfile(f, dtype='uint8', count=header_size)
+                if not header.size: 
+                    break
+                sample_size = header[0] + (header[1]<<8) + (header[2]<<16) + (header[3]<<24)
+                tagcode = header[5] + (header[4]<<8)
+                width = header[6] + (header[7]<<8)
+                height = header[8] + (header[9]<<8)
+                if header_size + width*height != sample_size:
+                    break
+                image = np.fromfile(f, dtype='uint8', count=width*height).reshape((height, width))
+                yield image, tagcode
+
+
+def run():
+    all_hwdb_gnt_files = glob.glob('./hwdb_raw/HWDB1.1trn_gnt/*.gnt')
+    logging.info('got all {} gnt files.'.format(len(all_hwdb_gnt_files)))
+    logging.info('gathering charset...')
+    charset = []
+    for gnt in all_hwdb_gnt_files:
+        hwdb = CASIAHWDBGNT(gnt)
+        for img, tagcode in hwdb.get_data_iter():
+            try:
+                label = struct.pack('>H', tagcode).decode('gb2312')            
+                label = label.replace('\x00', '')
+                charset.append(label)
+            except Exception as e:
+                continue
+    charset = sorted(set(charset))
+    logging.info('all got {} charactors.'.format(len(charset)))
+    with open('charactors.txt', 'w') as f:
+        f.writelines('\n'.join(charset))
+
+    tfrecord_f = 'casia_hwdb_1.0_1.1.tfrecord'
+    i = 0
+    with tf.io.TFRecordWriter(tfrecord_f) as tfrecord_writer:
+        for gnt in all_hwdb_gnt_files:
+            hwdb = CASIAHWDBGNT(gnt)
+            for img, tagcode in hwdb.get_data_iter():
+                try:
+                    img = cv.resize(img, (64, 64))
+                    label = struct.pack('>H', tagcode).decode('gb2312')            
+                    label = label.replace('\x00', '')
+                    index = charset.index(label)
+                    # save img, label as example
+                    example = tf.train.Example(features=tf.train.Features(
+                        feature={
+                        "label": tf.train.Feature(int64_list=tf.train.Int64List(value=[index])),
+                        'image': tf.train.Feature(bytes_list=tf.train.BytesList(value=[img]))
+                    }))
+                    tfrecord_writer.write(example.SerializeToString())
+                    if i%500:
+                        logging.info('solved {} examples.'.format(i))
+                    i += 1
+                except Exception as e:
+                    logging.error(e)
+                    continue
+    logging.info('done.')
+
+if __name__ == "__main__":
+    run()

dataset/get_hwdb_1.0_1.1.sh

@@ -0,0 +1,2 @@
+wget http://www.nlpr.ia.ac.cn/databases/download/feature_data/HWDB1.1trn_gnt.zip
+wget wget http://www.nlpr.ia.ac.cn/databases/download/feature_data/HWDB1.1tst_gnt.zip