finish

combined_pipe.py

@@ -1,4 +1,73 @@
 #!/usr/bin/env python3
-from diffusers import KandinskyV22CombinedPipeline
+from diffusers import AutoPipelineForText2Image, AutoPipelineForImage2Image,  AutoPipelineForInpainting
+from diffusers.utils import load_image
+from pathlib import Path
+import torch
+import numpy as np
+import requests
+from io import BytesIO
+from PIL import Image
+from huggingface_hub import HfApi
+import os
 
-pipe = KandinskyV22CombinedPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-decoder")
+api = HfApi()
+
+url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"
+response = requests.get(url)
+original_image = Image.open(BytesIO(response.content)).convert("RGB")
+original_image = original_image.resize((768, 512))
+
+original_image = load_image(
+    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main" "/kandinsky/cat.png"
+)
+
+mask = np.ones((768, 768), dtype=np.float32)
+# Let's mask out an area above the cat's head
+mask[:250, 250:-250] = 0
+
+# pipe = AutoPipelineForText2Image.from_pretrained("kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16)
+# pipe = AutoPipelineForImage2Image.from_pretrained("kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16)
+pipe = AutoPipelineForInpainting.from_pretrained("kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16)
+
+# pipe = AutoPipelineForText2Image.from_pretrained("kandinsky-community/kandinsky-2-2-decoder", torch_dtype=torch.float16)
+# pipe = AutoPipelineForImage2Image.from_pretrained("kandinsky-community/kandinsky-2-2-decoder", torch_dtype=torch.float16)
+# pipe = AutoPipelineForInpainting.from_pretrained("kandinsky-community/kandinsky-2-2-decoder-inpaint", torch_dtype=torch.float16)
+pipe.enable_model_cpu_offload()
+
+prompt = "A lion in galaxies, spirals, nebulae, stars, smoke, iridescent, intricate detail, octane render, 8k"
+negative_prompt = ""
+
+prompt = "A fantasy landscape, Cinematic lighting"
+prompt = "a hat"
+negative_prompt = "low quality, bad quality"
+
+# rompts = ["a cat playing with a ball++ in the forest", "a cat playing with a ball++ in the forest", "a cat playing with a ball-- in the forest"]
+
+# prompt_embeds = torch.cat([compel.build_conditioning_tensor(prompt) for prompt in prompts])
+
+# generator = [torch.Generator(device="cuda").manual_seed(0) for _ in range(prompt_embeds.shape[0])]
+#
+# url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"
+ 
+# response = requests.get(url)
+# image = Image.open(BytesIO(response.content)).convert("RGB")
+# image.thumbnail((768, 768))
+
+
+generator = torch.Generator(device="cpu").manual_seed(0)
+# images = pipe(prompt=prompt, generator=generator, num_images_per_prompt=1, num_inference_steps=25).images
+# images = pipe(prompt=prompt, image=original_image, generator=generator, num_images_per_prompt=1, num_inference_steps=25).images
+images = pipe(prompt=prompt, image=original_image, mask_image=mask, generator=generator, num_images_per_prompt=1, num_inference_steps=25).images
+
+for i, image in enumerate(images):
+    file_name = f"bb_1_{i}"
+    path = os.path.join(Path.home(), "images", f"{file_name}.png")
+    image.save(path)
+
+    api.upload_file(
+        path_or_fileobj=path,
+        path_in_repo=path.split("/")[-1],
+        repo_id="patrickvonplaten/images",
+        repo_type="dataset",
+    )
+    print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/{file_name}.png")

control_net_canny.py

@@ -47,6 +47,8 @@ else:
     )
     size = 512
 
+import ipdb; ipdb.set_trace()
+
 # pipe.enable_model_cpu_offload()
 pipe.to("cuda")