Prompt: Dark light city, hurricane sky, From Outside, Art Nouveau style, hiper-realistic painting by Alexandre Benois, Victor Vasnetsov, Akihiko Yoshida, Mikhail Vrubel, Elegant, Fractal, Vibrant, In hiper-realistic, Manga, epic composition, UHD, HD, HDR ON,
Prompt: God jumping from the sky. Philosophy, Mathematics and Nuclear Magic of Creation of Worlds Horror darkness h.r.giger total destruction, dark clouds witd thunder and lightinhs: horror dali bosch canaletto giger alien planet with monsters jungle full of life, ultradetailed background
Prompt: Create a highly detailed and visually stunning digital artwork of a quill pen. The quill itself should be rendered with meticulous attention to detail, from the delicate feathers to the intricate metal nib. The entire scene should be rendered in exquisite detail.
Prompt: An architectural synthesis of coral reefs and a whimsical underwater houses made of seashells. Shimmering light, sharp focus. Intricate, elaborate, extremely detailed. Many fish. Hovik Zohrabian, Guido Borelli da Caluso style
Prompt: Bearded black man smoking cigar walking tri color pitbull on leash through leaves falling in autumn future with black women beauty skin artistic
Prompt: people walking on the streets next to canal and people in boats, manhattan city plan by joehn nolan ; dutch Venice canal plan by John Nolen mixed with 1909 chicago plan
Prompt: Surreal transformation class DeepDream(tf.Module): def __init__(self, model): self.model = model @tf.function( input_signature=( tf.TensorSpec(shape=[None,None,3], dtype=tf.float32), tf.TensorSpec(shape=[], dtype=tf.int32), tf.TensorSpec(shape=[], dtype=tf.float32),) ) def __call__(self, img, steps, step_size): print("Tracing") loss = tf.constant(0.0) for n in tf.range(steps): with tf.GradientTape() as tape: # This needs gradients relative to `img` # `GradientTape` only watches `tf.Variable`s by default tape.watch(img) loss = calc_loss(img, self.model) # Calculate the gradient of the loss with respect to the pixels of the input image. gradients = tape.gradient(loss, img) # Normalize the gradients. gradients /= tf.math.reduce_std(gradients) + 1e-8 # In gradient ascent, the "loss" is maximized so that the input image increasingly "excites" the layers. # You can update the image by directly adding the gradients (because they're the same shape!) style by dPwOrKs2
Dream Level: is increased each time when you "Go Deeper" into the dream. Each new level is harder to achieve and
takes more iterations than the one before.
Rare Deep Dream: is any dream which went deeper than level 6.
Deep Dream
You cannot go deeper into someone else's dream. You must create your own.
Deep Dream
Currently going deeper is available only for Deep Dreams.