Reputation: 919
tf.image.decode_png() can output grayscale, RGB and RGBA image.
But I'd like to convert RGBA to pure black and white in Tensorflow (without using pillow).
Please give me some advice.
Upvotes: 2
Views: 5298
Reputation: 57973
Use tf.select
to do the thresholding
pil_image = PilImage.open('/temp/panda.png')
show_pil_image(pil_image)
pil_buf = open('/temp/panda.png').read()
contents = tf.placeholder(dtype=tf.string)
decode_op = tf.image.decode_png(contents, channels=1)
gray_image = tf.squeeze(decode_op) # shape (127,127,1) -> shape (127,127)
sess = create_session()
[decoded] = sess.run([gray_image], feed_dict={contents: pil_buf})
show_pil_image(PilImage.fromarray(decoded))
contents = tf.placeholder(dtype=tf.string)
decode_op = tf.image.decode_png(contents, channels=1)
gray_image = tf.squeeze(decode_op) # shape (127,127,1) -> shape (127,127)
select_op = tf.select(gray_image>127, 255*tf.ones_like(gray_image), tf.zeros_like(gray_image))
sess = create_session()
[decoded] = sess.run([select_op], feed_dict={contents: pil_buf})
show_pil_image(PilImage.fromarray(decoded))
Upvotes: 6