opencv_encode_tf_image_decode.py

# Convert an numpy array image to bytes and decode it with tensorflow.
# Refers to https://stackoverflow.com/questions/50630045/how-to-turn-numpy-array-image-to-bytes/50630390

import numpy as np
import cv2
import tensorflow as tf

# img_bgr is an 16-bit BGR image
img_bgr = (np.random.rand(50, 50, 3)*65536).astype(np.uint16)
cv2.imwrite('demo.png', img_bgr, params=[cv2.CV_16U])

success, img_bytes_arr = cv2.imencode('.png', img_bgr, params=[cv2.CV_16U])
print(img_bytes_arr.dtype, img_bytes_arr.shape)   # uint8 (15130, 1)

_decode_data = tf.placeholder(dtype=tf.string)
_decode = tf.image.decode_png(_decode_data, channels=3, dtype=tf.uint16)

# Decode bytes back to an 16-bit RGB image with tensorflow
img_rgb_tf = tf.Session().run(_decode, feed_dict={_decode_data: img_bytes_arr.tobytes()})

# Convert img_rgb_tf to BGR color space
img_bgr_tf = cv2.cvtColor(img_rgb_tf, cv2.COLOR_RGB2BGR)

cv2.imwrite('demo_tf.png', img_bgr_tf, params=[cv2.CV_16U])
print(img_bgr_tf.dtype, img_bgr_tf.shape)   # uint16 (50, 50, 3)

assert (img_bgr == img_bgr_tf).all()