up

app.py

@@ -70,19 +70,25 @@ def segmentation(img):
     
 
 def upscale(image, prompt):
-    print("upscale")
+    print("upscale",image,prompt)
 
-    image = image.thumbnail((512, 512))
+    image.thumbnail((512, 512))
+    print("resize",image)
 
-    model_id = "stabilityai/stable-diffusion-x4-upscaler"
-    pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+    pipeline = StableDiffusionUpscalePipeline.from_pretrained("stabilityai/stable-diffusion-x4-upscaler", torch_dtype=torch.float16)
     pipeline = pipeline.to("cuda")
 
 
     #pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-x4-upscaler")
     # pipeline = StableDiffusionLatentUpscalePipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16).to('cuda')
-    
-    upscaled_image = pipeline(prompt=prompt, image=image).images[0]
+    ret = pipeline(prompt=prompt, 
+                   image=image,
+                   num_inference_steps=20,
+                   guidance_scale=0)
+    print("ret",ret)
+    upscaled_image = ret.images[0]
+    print("up",upscaled_image)
+
     return upscaled_image
 
 with gr.Blocks() as app: