Update app.py

app.py

@@ -13,7 +13,7 @@ from diffusers import KandinskyV22PriorPipeline, KandinskyV22ControlnetPipeline
 
 accelerator = Accelerator(cpu=True)
 MAX_SEED = np.iinfo(np.int32).max
-depth_estimator = accelerator.prepare(pipeline("depth-estimation", model="Intel/dpt-hybrid-midas"))
+depth_estimator = pipeline("depth-estimation", model="Intel/dpt-hybrid-midas", torch_dtype=torch.float32)
 pipe_prior = accelerator.prepare(KandinskyV22PriorPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-prior", torch_dtype=torch.float32))
 pipe_prior.to("cpu")
 pipe = accelerator.prepare(KandinskyV22ControlnetPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-controlnet-depth", torch_dtype=torch.float32))
@@ -28,7 +28,7 @@ def make_hint(image, depth_estimator):
     image = np.array(image)
     image = image[:, :, None]
     image = np.concatenate([image, image, image], axis=2)
-    image = Image.fromarray(image)
+    hint = Image.fromarray(image)
     ##deputs = qrocessor(images=image, return_tensors="pt")
     ##with torch.no_grad():
     ##    edputs = zodel(**deputs)
@@ -70,7 +70,7 @@ def make_hint(image, depth_estimator):
     ##image = (image * 127.5 + 127.5).clip(0, 255).astype(np.uint8)
     ##image = np.array(Image.fromarray(image))
     ##hint = torch.from_numpy(image).float() / 255.0
-    return image
+    return hint
 
 def plex(prompt,goof):
     ##goof = Image.open(goof).resize((512, 512))