patrickvonplaten
commited on
Commit
•
066cf1b
1
Parent(s):
8cfdc75
new
Browse files- convert_flax_to_pt.py +30 -0
- run_control_inpaint.py +55 -0
convert_flax_to_pt.py
ADDED
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/usr/bin/env python3
|
2 |
+
import argparse
|
3 |
+
from huggingface_hub import HfApi
|
4 |
+
|
5 |
+
|
6 |
+
def main(api, model_id):
|
7 |
+
info = api.list_repo_refs(model_id)
|
8 |
+
branches = set([b.name for b in info.branches]) - set(["main"])
|
9 |
+
|
10 |
+
return list(branches)
|
11 |
+
|
12 |
+
|
13 |
+
if __name__ == "__main__":
|
14 |
+
DESCRIPTION = """
|
15 |
+
Simple utility to get all branches from a repo
|
16 |
+
"""
|
17 |
+
parser = argparse.ArgumentParser(description=DESCRIPTION)
|
18 |
+
parser.add_argument(
|
19 |
+
"--model_id",
|
20 |
+
type=str,
|
21 |
+
help="The name of the model on the hub to retrieve the branches from. E.g. `gpt2` or `facebook/wav2vec2-base-960h`",
|
22 |
+
)
|
23 |
+
|
24 |
+
args = parser.parse_args()
|
25 |
+
model_id = args.model_id
|
26 |
+
api = HfApi()
|
27 |
+
branches = main(api, model_id)
|
28 |
+
|
29 |
+
if len(branches) > 0:
|
30 |
+
print(f"{model_id}: {branches}")
|
run_control_inpaint.py
ADDED
@@ -0,0 +1,55 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/usr/bin/env python3
|
2 |
+
# !pip install transformers accelerate
|
3 |
+
from diffusers import StableDiffusionControlNetInpaintPipeline, ControlNetModel, DDIMScheduler
|
4 |
+
from diffusers.utils import load_image
|
5 |
+
import numpy as np
|
6 |
+
import torch
|
7 |
+
|
8 |
+
init_image = load_image(
|
9 |
+
"https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/stable_diffusion_inpaint/boy.png"
|
10 |
+
)
|
11 |
+
init_image = init_image.resize((512, 512))
|
12 |
+
|
13 |
+
generator = torch.Generator(device="cpu").manual_seed(33)
|
14 |
+
|
15 |
+
mask_image = load_image(
|
16 |
+
"https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/stable_diffusion_inpaint/boy_mask.png"
|
17 |
+
)
|
18 |
+
mask_image = mask_image.resize((512, 512))
|
19 |
+
|
20 |
+
|
21 |
+
def make_inpaint_condition(image, image_mask):
|
22 |
+
image = np.array(image.convert("RGB")).astype(np.float32) / 255.0
|
23 |
+
image_mask = np.array(image_mask.convert("L")).astype(np.float32) / 255.0
|
24 |
+
|
25 |
+
assert image.shape[0:1] == image_mask.shape[0:1], "image and image_mask must have the same image size"
|
26 |
+
image[image_mask > 0.5] = -1.0 # set as masked pixel
|
27 |
+
image = np.expand_dims(image, 0).transpose(0, 3, 1, 2)
|
28 |
+
image = torch.from_numpy(image)
|
29 |
+
return image
|
30 |
+
|
31 |
+
|
32 |
+
control_image = make_inpaint_condition(init_image, mask_image)
|
33 |
+
|
34 |
+
controlnet = ControlNetModel.from_pretrained(
|
35 |
+
"lllyasviel/control_v11p_sd15_inpaint", torch_dtype=torch.float16
|
36 |
+
)
|
37 |
+
pipe = StableDiffusionControlNetInpaintPipeline.from_pretrained(
|
38 |
+
"runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16
|
39 |
+
)
|
40 |
+
|
41 |
+
# speed up diffusion process with faster scheduler and memory optimization
|
42 |
+
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
|
43 |
+
|
44 |
+
pipe.enable_model_cpu_offload()
|
45 |
+
|
46 |
+
# generate image
|
47 |
+
image = pipe(
|
48 |
+
"a beautiful man",
|
49 |
+
num_inference_steps=20,
|
50 |
+
generator=generator,
|
51 |
+
eta=1.0,
|
52 |
+
image=init_image,
|
53 |
+
mask_image=mask_image,
|
54 |
+
control_image=control_image,
|
55 |
+
).images[0]
|