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brycedrennan · Nov 22, 2023 · 1705fff · 1705fff
1 parent 0af6c4a
commit 1705fff
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Showing 2 changed files with 9 additions and 6 deletions.
diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml
@@ -54,7 +54,7 @@ jobs:
         run: |
           black --diff --fast .
   test:
-    runs-on: ubuntu-latest
+    runs-on: macos-13-xlarge
     strategy:
       fail-fast: false
       matrix:

diff --git a/imaginairy/api_refiners.py b/imaginairy/api_refiners.py
@@ -126,7 +126,7 @@ def latent_logger(latents):
         init_latent = None
         if prompt.init_image:
             starting_image = prompt.init_image
-            first_step = int(prompt.steps * prompt.init_image_strength)
+            first_step = int((prompt.steps - 1) * prompt.init_image_strength)
 
             if prompt.mask_prompt:
                 mask_image, mask_grayscale = get_img_mask(
@@ -272,10 +272,10 @@ def latent_logger(latents):
                 result_images["composition-upscaled"] = comp_image
                 # noise = noise[:, :, : comp_image.height, : comp_image.shape[3]]
                 comp_cutoff = 0.60
-                first_step = int(prompt.steps * comp_cutoff)
-                noise_step = int(prompt.steps * max(comp_cutoff - 0.05, 0))
-                noise_step = max(noise_step, 0)
-                noise_step = min(noise_step, prompt.steps - 1)
+                first_step = int((prompt.steps - 1) * comp_cutoff)
+                # noise_step = int(prompt.steps * max(comp_cutoff - 0.05, 0))
+                # noise_step = max(noise_step, 0)
+                # noise_step = min(noise_step, prompt.steps - 1)
                 log_img(comp_image, "comp_image")
                 comp_image_t = pillow_img_to_torch_image(comp_image)
                 comp_image_t = comp_image_t.to(sd.device, dtype=sd.dtype)
@@ -302,6 +302,9 @@ def latent_logger(latents):
             )
 
         if init_latent is not None:
+            print(
+                f"noise step: {noise_step} first step: {first_step} len steps: {len(sd.steps)}"
+            )
             noise_step = noise_step if noise_step is not None else first_step
             noised_latent = sd.scheduler.add_noise(
                 x=init_latent, noise=noise, step=sd.steps[noise_step]