moved examples

examples/multi_trans.py

@@ -0,0 +1,56 @@
+import torch
+import warnings
+from diffusers import AutoPipelineForText2Image
+from latentblending.movie_util import concatenate_movies
+from latentblending.blending_engine import BlendingEngine
+from latentblending.diffusers_holder import DiffusersHolder
+torch.set_grad_enabled(False)
+torch.backends.cudnn.benchmark = False
+warnings.filterwarnings('ignore')
+
+# %% First let us spawn a stable diffusion holder. Uncomment your version of choice.
+pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
+pipe.to('cuda')
+dh = DiffusersHolder(pipe)
+
+# %% Let's setup the multi transition
+fps = 30
+duration_single_trans = 10
+
+# Specify a list of prompts below
+list_prompts = []
+list_prompts.append("Photo of a house, high detail")
+list_prompts.append("Photo of an elephant in african savannah")
+list_prompts.append("photo of a house, high detail")
+
+
+# You can optionally specify the seeds
+list_seeds = [95437579, 33259350, 956051013]
+fp_movie = 'movie_example2.mp4'
+be = BlendingEngine(dh)
+
+list_movie_parts = []
+for i in range(len(list_prompts) - 1):
+    # For a multi transition we can save some computation time and recycle the latents
+    if i == 0:
+        be.set_prompt1(list_prompts[i])
+        be.set_prompt2(list_prompts[i + 1])
+        recycle_img1 = False
+    else:
+        be.swap_forward()
+        be.set_prompt2(list_prompts[i + 1])
+        recycle_img1 = True
+
+    fp_movie_part = f"tmp_part_{str(i).zfill(3)}.mp4"
+    fixed_seeds = list_seeds[i:i + 2]
+    # Run latent blending
+    be.run_transition(
+        recycle_img1=recycle_img1,
+        fixed_seeds=fixed_seeds)
+
+    # Save movie
+    be.write_movie_transition(fp_movie_part, duration_single_trans)
+    list_movie_parts.append(fp_movie_part)
+
+# Finally, concatente the result
+concatenate_movies(fp_movie, list_movie_parts)

examples/single_trans.py

@@ -0,0 +1,26 @@
+import torch
+import warnings
+from diffusers import AutoPipelineForText2Image
+from latentblending.blending_engine import BlendingEngine
+from latentblending.diffusers_holder import DiffusersHolder
+
+warnings.filterwarnings('ignore')
+torch.set_grad_enabled(False)
+torch.backends.cudnn.benchmark = False
+
+# %% First let us spawn a stable diffusion holder. Uncomment your version of choice.
+pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
+pipe.to("cuda")
+
+dh = DiffusersHolder(pipe)
+
+be = BlendingEngine(dh)
+be.set_prompt1("photo of underwater landscape, fish, und the sea, incredible detail, high resolution")
+be.set_prompt2("rendering of an alien planet, strange plants, strange creatures, surreal")
+be.set_negative_prompt("blurry, ugly, pale")
+
+# Run latent blending
+be.run_transition()
+
+# Save movie
+be.write_movie_transition('movie_example1.mp4', duration_transition=12)