Write jpeg file directly to lmdb [closed]

2019-08-18 11:48发布

问题:

I managed to write numpy arrays to lmdb, howewer solution is far from perfection, but actually my X is just jpg image, so my question is how to directly write jpeg file to lmdb?

Seems like pycaffe doing similar thing but it use caffe specific Datum and I need some general solution without dependencies.

回答1:

Here is example that write image as numpy array and directly as encoded jpg.

As we can see store jpg directly is more efficient in terms of storage.

du -sh *
184K  temp.db
120K  temp_jpg.db
import numpy as np
import lmdb
import cv2

n_samples= 2

def create_random_image(filename):
    img= (np.random.rand(100,120,3)*255).astype(np.uint8)

    cv2.imwrite(filename,img)

def write_lmdb(filename):
    print 'Write lmdb'

    lmdb_env = lmdb.open(filename, map_size=int(1e9))

    X= cv2.imread('random_img.jpg')
    y= np.random.rand(1).astype(np.float32)*10.0

    for i in range(n_samples):
        with lmdb_env.begin(write=True) as lmdb_txn:
            lmdb_txn.put('X_'+str(i), X)
            lmdb_txn.put('y_'+str(i), y)

            print 'X.shape:',X.shape
            print 'y:',y

def read_lmdb(filename):
    print 'Read lmdb'

    lmdb_env = lmdb.open(filename)
    lmdb_txn = lmdb_env.begin()
    lmdb_cursor = lmdb_txn.cursor()

    #also can do it without iteration via txn.get('key1')?

    n_counter=0
    with lmdb_env.begin() as lmdb_txn:
        with lmdb_txn.cursor() as lmdb_cursor:
            for key, value in lmdb_cursor:  
                print key
                if('X' in key):
                    print 'X.shape', np.fromstring(value, dtype=np.uint8).shape
                if('y' in key):
                    print np.fromstring(value, dtype=np.float32)

                n_counter=n_counter+1

    print 'n_samples',n_counter

def write_lmdb_jpg(filename):
    print 'Write lmdb'

    lmdb_env = lmdb.open(filename, map_size=int(1e9))

    X= cv2.imread('random_img.jpg')
    y= np.random.rand(1).astype(np.float32)*10.0

    for i in range(n_samples):
        with lmdb_env.begin(write=True) as lmdb_txn:
            lmdb_txn.put('X_'+str(i), cv2.imencode('.jpg', X)[1])
            lmdb_txn.put('y_'+str(i), y)

            print 'X.shape', cv2.imencode('.jpg', X)[1].shape
            print 'y:',y

def read_lmdb_jpg(filename):
    print 'Read lmdb'

    lmdb_env = lmdb.open(filename)
    lmdb_txn = lmdb_env.begin()
    lmdb_cursor = lmdb_txn.cursor()

    #also can do it without iteration via txn.get('key1')?

    n_counter=0
    with lmdb_env.begin() as lmdb_txn:
        with lmdb_txn.cursor() as lmdb_cursor:
            for key, value in lmdb_cursor:  
                print key
                if('X' in key):
                    X_str= np.fromstring(value, dtype=np.uint8)
                    print 'X_str.shape', X_str.shape
                    X= cv2.imdecode(X_str, cv2.CV_LOAD_IMAGE_COLOR)
                    print 'X.shape', X.shape
                if('y' in key):
                    print np.fromstring(value, dtype=np.float32)

                n_counter=n_counter+1

    print 'n_samples',n_counter

create_random_image('random_img.jpg')

#Write as numpy array       
write_lmdb('temp.db')
read_lmdb('temp.db')

#Write as encoded jpg
write_lmdb_jpg('temp_jpg.db')
read_lmdb_jpg('temp_jpg.db')