# Copyright 2018 The Lucid Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

"""High-level wrapper for paramaterizing images."""


import tensorflow as tf

from lucid.optvis.param.color import to_valid_rgb
from lucid.optvis.param.spatial import pixel_image, fft_image


def image(w, h=None, batch=None, sd=None, decorrelate=True, fft=True, alpha=False):
    h = h or w
    batch = batch or 1
    channels = 4 if alpha else 3
    shape = [batch, w, h, channels]
    param_f = fft_image if fft else pixel_image
    t = param_f(shape, sd=sd)
    rgb = to_valid_rgb(t[..., :3], decorrelate=decorrelate, sigmoid=True)
    if alpha:
        a = tf.nn.sigmoid(t[..., 3:])
        return tf.concat([rgb, a], -1)
    return rgb

# Copyright 2018 The Lucid Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

"""High-level wrapper for paramaterizing images."""


import tensorflow as tf

from lucid.optvis.param.color import to_valid_rgb
from lucid.optvis.param.spatial import pixel_image, fft_image


def image(w, h=None, batch=None, sd=None, decorrelate=True, fft=True, alpha=False):
    h = h or w
    batch = batch or 1
    channels = 4 if alpha else 3
    shape = [batch, h, w, channels]
    param_f = fft_image if fft else pixel_image
    t = param_f(shape, sd=sd)
    rgb = to_valid_rgb(t[..., :3], decorrelate=decorrelate, sigmoid=True)
    if alpha:
        a = tf.nn.sigmoid(t[..., 3:])
        return tf.concat([rgb, a], -1)
    return rgb

Fix image width and height switching