在crnn训练的时候需要用到lmdb格式的数据集，下面是python生成lmdb个是数据集的代码，注意一定要在linux系统下，否则会读入图像的时候出问题，可能遇到的问题都在代码里面注释了，看代码即可。

#-*- coding:utf-8 -*- import osimport lmdb#先pip install这个模块哦import cv2import globimport numpy as np def checkImageIsValid(imageBin): if imageBin is None: return False imageBuf = np.fromstring(imageBin, dtype=np.uint8) img = cv2.imdecode(imageBuf, cv2.IMREAD_GRAYSCALE) if img is None: return False imgH, imgW = img.shape[0], img.shape[1] if imgH * imgW == 0: return False return True def writeCache(env, cache): with env.begin(write=True) as txn: for k, v in cache.iteritems(): txn.put(k, v) def createDataset(outputPath, imagePathList, labelList, lexiconList=None, checkValid=True): """ Create LMDB dataset for CRNN training.# ARGS: outputPath : LMDB output path imagePathList : list of image path labelList : list of corresponding groundtruth texts lexiconList : (optional) list of lexicon lists checkValid : if true, check the validity of every image """ # print (len(imagePathList) , len(labelList)) assert(len(imagePathList) == len(labelList)) nSamples = len(imagePathList) print '...................' env = lmdb.open(outputPath, map_size=8589934592)#1099511627776)所需要的磁盘空间的最小值，之前是1T，我改成了8g，否则会报磁盘空间不足，这个数字是字节 cache = {} cnt = 1 for i in xrange(nSamples): imagePath = imagePathList[i] label = labelList[i] if not os.path.exists(imagePath): print('%s does not exist' % imagePath) continue with open(imagePath, 'r') as f: imageBin = f.read() if checkValid: if not checkImageIsValid(imageBin): print('%s is not a valid image' % imagePath)#注意一定要在linux下，否则f.read就不可用了，就会输出这个信息 continue imageKey = 'image-%09d' % cnt labelKey = 'label-%09d' % cnt cache[imageKey] = imageBin cache[labelKey] = label if lexiconList: lexiconKey = 'lexicon-%09d' % cnt cache[lexiconKey] = ' '.join(lexiconList[i]) if cnt % 1000 == 0: writeCache(env, cache) cache = {} print('Written %d / %d' % (cnt, nSamples)) cnt += 1 nSamples = cnt - 1 cache['num-samples'] = str(nSamples) writeCache(env, cache) print('Created dataset with %d samples' % nSamples) def read_text(path): with open(path) as f: text = f.read() text = text.strip() return text if __name__ == '__main__': # lmdb 输出目录 outputPath = 'D:/ruanjianxiazai/tuxiangyangben/fengehou/train'#训练集和验证集要跑两遍这个程序，分两次生成 path = "D:/ruanjianxiazai/tuxiangyangben/fengehou/chenguang/*.jpg"#将txt与jpg的都放在同一个文件里面 imagePathList = glob.glob(path) print '------------',len(imagePathList),'------------' imgLabelLists = [] for p in imagePathList: try: imgLabelLists.append((p, read_text(p.replace('.jpg', '.txt')))) except: continue # imgLabelList = [ (p, read_text(p.replace('.jpg', '.txt'))) for p in imagePathList] # sort by labelList imgLabelList = sorted(imgLabelLists, key = lambda x:len(x[1])) imgPaths = [ p[0] for p in imgLabelList] txtLists = [ p[1] for p in imgLabelList] createDataset(outputPath, imgPaths, txtLists, lexiconList=None, checkValid=True)

以上这篇python生成lmdb格式的文件实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。