GenImageLmdb.py 文件源码

def make_datum(img, label):  
    #image is numpy.ndarray format. BGR instead of RGB  
    return caffe_pb2.Datum(  
        channels=3,  
        width=IMAGE_WIDTH,  
        height=IMAGE_HEIGHT,  
        label=label,
        data=np.transpose(img, (2, 0, 1)).tostring()) 
        # or .tobytes() if numpy < 1.9

# key = 0
# env = lmdb.open(img_lmdb_path, map_size=int(1e12))
# with env.begin(write=True) as txn:
#     for idx in xrange(numSample):
#         info = data[idx].split(" ")
#         OriImg = cv2.imread(datadir + info[0])
#         img = cv2.resize(OriImg,(IMAGE_WIDTH,IMAGE_HEIGHT))
#         label = int(info[1])
#         img = np.transpose(img, (2, 0, 1))
#         datum = caffe.io.array_to_datum(img, label)
#         key_str = '{:08}'.format(key)
# #        txn.put(key_str.encode('ascii'), datum.SerializeToString())
#         txn.put(key_str, datum.SerializeToString())
#         key += 1
#     for idx in xrange(numSample):
#         info = data[idx].split(" ")
#         OriImg = cv2.imread(datadir + info[0])
#         img = cv2.resize(OriImg,(IMAGE_WIDTH,IMAGE_HEIGHT))
#         label = int(info[1])
#         img = cv2.flip(img,1)
#         img = np.transpose(img, (2, 0, 1))
#         datum = caffe.io.array_to_datum(img, label)
#         key_str = '{:08}'.format(key)
# #        txn.put(key_str.encode('ascii'), datum.SerializeToString())
#         txn.put(key_str, datum.SerializeToString())
#         key += 1
# print key