up

run.py

@@ -2,23 +2,16 @@ import requests
 import torch
 from PIL import Image
 from io import BytesIO
-import time
 
 from diffusers import DiffusionPipeline
 
-pipe = DiffusionPipeline.from_pretrained("/home/patrick_huggingface_co/stable-diffusion-2-1-unclip-i2i-l", torch_dtype=torch.float16)
+pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-unclip", torch_dtype=torch.float16, variant="fp16")
 pipe.to("cuda")
 
-url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/stable_unclip/image%20(13).png"
-#url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/stable_unclip/image%20(10).png"
-#url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/stable_unclip/image%20(10).png"
-#url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/stable_unclip/image%20(10).png"
-
+# get image
+url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/stable_unclip/tarsila_do_amaral.png"
 response = requests.get(url)
-init_image = Image.open(BytesIO(response.content)).convert("RGB")
-# init_image = init_image.resize((768, 512))
-
-images = pipe(4 * [init_image]).images
+image = Image.open(BytesIO(response.content)).convert("RGB")
 
-for i in range(len(images)):
-    images[i].save(f"fantasy_landscape_{i}.png")
+image = pipe(image).images[0]
+image.save(f"tarsila_variation.png")