import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image


def load_image(filename):
    image = Image.open(filename)
    image.load()
    data = np.asarray(image, dtype="uint8")
    return data


def to_image(data):
    image = Image.fromarray(data)
    return image


r = tf.placeholder(dtype=tf.float32, shape=[None, None])
g = tf.placeholder(dtype=tf.float32, shape=[None, None])
b = tf.placeholder(dtype=tf.float32, shape=[None, None])

d = tf.placeholder(dtype=tf.float32, shape=None)

out = (0.3*r + 0.59*g + 0.11*b) * d / 255

img = load_image("HappyFish.jpg")
img_ = Image.open("HappyFish.jpg")

with tf.Session() as sess:
    plt.subplot(1, 2, 1)
    plt.imshow(to_image(img))
    plt.title("Original")
    plt.subplot(1, 2, 2)
    plt.title("Grayscaled")
    plt.imshow(to_image(sess.run(out, feed_dict={r: img_.split()[0], g: img_.split()[1], b: img_.split()[2], d: 255})))
    plt.show()