TensorFlow ValueError: Cannot feed value of shape (64, 64, 3) for Tensor u'Placeholder:0', which has shape '(?, 64, 64, 3)'

image has a shape of (64,64,3).

Your input placeholder _x have a shape of (?, 64,64,3).

The problem is that you're feeding the placeholder with a value of a different shape.

You have to feed it with a value of (1, 64, 64, 3) = a batch of 1 image.

Just reshape your image value to a batch with size one.

image = array(img).reshape(1, 64,64,3)

P.S: the fact that the input placeholder accepts a batch of images, means that you can run predicions for a batch of images in parallel.You can try to read more than 1 image (N images) and than build a batch of N image, using a tensor with shape (N, 64,64,3)

Powder's comment may go undetected like I missed it so many times,. So with the hope of making it more visible, I will re-iterate his point.

Sometimes using image = array(img).reshape(a,b,c,d) will reshape alright but from experience, my kernel crashes every time I try to use the new dimension in an operation. The safest to use is

np.expand_dims(img, axis=0)

It works perfect every time. I just can't explain why. This link has a great explanation and examples regarding its usage.