From 25a6cff6b6053f4a34379f9a88dfbeae926d4a58 Mon Sep 17 00:00:00 2001
From: Johannes Stelzer <jsdmail@gmail.com>
Date: Thu, 16 Nov 2023 16:08:01 +0100
Subject: [PATCH] tests
---
requirements.txt | 3 ++-
test_latentblending.py | 54 ++++++++++++++++++++++++++++++++++++++++++
2 files changed, 56 insertions(+), 1 deletion(-)
create mode 100644 test_latentblending.py
diff --git a/requirements.txt b/requirements.txt
index b8b178a..8d812e6 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,4 +2,5 @@ lpips==0.1.4
opencv-python==4.7.0.68
ffmpeg-python
diffusers["torch"]==0.23.0
-transformers==4.35.2
\ No newline at end of file
+transformers==4.35.2
+pytest
\ No newline at end of file
diff --git a/test_latentblending.py b/test_latentblending.py
new file mode 100644
index 0000000..78f1688
--- /dev/null
+++ b/test_latentblending.py
@@ -0,0 +1,54 @@
+import unittest
+from latent_blending import LatentBlending
+from diffusers_holder import DiffusersHolder
+from diffusers import DiffusionPipeline
+import torch
+
+default_pipe = "stabilityai/stable-diffusion-xl-base-1.0"
+
+
+class TestDiffusersHolder(unittest.TestCase):
+
+ def test_load_diffusers_holder(self):
+ pipe = DiffusionPipeline.from_pretrained(default_pipe, torch_dtype=torch.float16).to('cuda')
+ dh = DiffusersHolder(pipe)
+ self.assertIsNotNone(dh, "Failed to load DiffusersHolder")
+
+
+class TestSingleImageGeneration(unittest.TestCase):
+
+ def test_single_image_generation(self):
+ pipe = DiffusionPipeline.from_pretrained(default_pipe, torch_dtype=torch.float16).to('cuda')
+ dh = DiffusersHolder(pipe)
+ dh.set_dimensions((1024, 704))
+ dh.set_num_inference_steps(40)
+ prompt = "Your prompt here"
+ text_embeddings = dh.get_text_embedding(prompt)
+ generator = torch.Generator(device=dh.device).manual_seed(int(420))
+ latents_start = dh.get_noise()
+ list_latents_1 = dh.run_diffusion(text_embeddings, latents_start)
+ img_orig = dh.latent2image(list_latents_1[-1])
+ self.assertIsNotNone(img_orig, "Failed to generate an image")
+
+
+class TestImageTransition(unittest.TestCase):
+
+ def test_image_transition(self):
+ pipe = DiffusionPipeline.from_pretrained(default_pipe, torch_dtype=torch.float16).to('cuda')
+ dh = DiffusersHolder(pipe)
+ lb = LatentBlending(dh)
+
+ lb.set_prompt1('photo of my first prompt1')
+ lb.set_prompt2('photo of my second prompt')
+ depth_strength = 0.6
+ t_compute_max_allowed = 10
+ num_inference_steps = 30
+ imgs_transition = lb.run_transition(
+ depth_strength=depth_strength,
+ num_inference_steps=num_inference_steps,
+ t_compute_max_allowed=t_compute_max_allowed)
+
+ self.assertTrue(len(imgs_transition) > 0, "No transition images generated")
+
+if __name__ == '__main__':
+ unittest.main()