diff --git a/gen_compare_v11/README.md b/gen_compare_v11/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bfbad02c9b28f1f7ecf0f6c03e78024e4bfba77b
--- /dev/null
+++ b/gen_compare_v11/README.md
@@ -0,0 +1,102 @@
+# ControlNet Generation Comparison
+
+## control_v11p_sd15_canny
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_depth
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_mlsd
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_normalbae
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_openpose
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_scribble
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_seg
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+|0||||
+|1||||
+|2||||
+|3||||
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_softedge
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15_lineart
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
+## control_v11p_sd15s2_lineart_anime
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0||||
+|1||||
+|2||||
+|3||||
diff --git a/gen_compare_v11/control_images.yaml b/gen_compare_v11/control_images.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..de8f1e97dce5719532fe32053860162d46e4f3ac
--- /dev/null
+++ b/gen_compare_v11/control_images.yaml
@@ -0,0 +1,34 @@
+p_sd15_canny:
+ - canny_vermeer_512x512.png
+p_sd15_depth:
+ - zoe_pexels-sound-on-3760767_512x512.png
+ - midas_pexels-sound-on-3760767_512x512.png
+p_sd15_lineart:
+ - lineart_wolf_512x512.png
+p_sd15_mlsd:
+ - mlsd_room_512x512.png
+p_sd15_normalbae:
+ - normalbae_person_leaves_512x512.png
+p_sd15_openpose:
+ - openpose_pexels-sound-on-3760847_512x512.png
+ # - openpose_pexels-sound-on-3760693_512x512.png
+ # - openpose_pexels-sound-on-3760767_512x512.png
+ # - openpose_pexels-wallace-chuck-2383750_512x512.png
+p_sd15_scribble:
+ - hed_pexels-wallace-chuck-2383750_512x512.png
+ - pidi_pexels-sound-on-3760767_512x512.png
+p_sd15_softedge:
+ - hed_pexels-wallace-chuck-2383750_512x512.png
+ - pidi_pexels-sound-on-3760767_512x512.png
+p_sd15_seg:
+ - oneformer_adk20_house_512x512.png
+ - oneformer_coco_house_512x512.png
+ - uniformer_house_512x512.png
+p_sd15s2_lineart_anime:
+ - lineartanime_anime2_512x512.png
+# p_sd15_inpaint:
+# e_sd15_shuffle:
+# - colorshuffle_vermeer_512x512.png
+# - shuffle_vermeer_512x512.png
+# e_sd15_ip2p:
+# u_sd15_tile:
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+size 174446
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+version https://git-lfs.github.com/spec/v1
+oid sha256:908c6992542673c592e37d78cde5928ebaa77d40f7e3a78ac14e305c0137bb1d
+size 268618
diff --git a/gen_compare_v11/gen_diffusers_image.py b/gen_compare_v11/gen_diffusers_image.py
new file mode 100644
index 0000000000000000000000000000000000000000..0819fe94e543d20bc8079769b206a4b3cb91e90b
--- /dev/null
+++ b/gen_compare_v11/gen_diffusers_image.py
@@ -0,0 +1,73 @@
+# Diffusers' ControlNet Implementation Subjective Evaluation
+
+import einops
+import numpy as np
+import torch
+import sys
+import os
+import yaml
+
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, DDIMScheduler
+
+from PIL import Image
+
+test_prompt = "best quality, extremely detailed"
+test_negative_prompt = "lowres, bad anatomy, worst quality, low quality"
+
+def generate_image(seed, prompt, negative_prompt, control, guess_mode=False):
+ latent = torch.randn((1,4,64,64), device="cpu", generator=torch.Generator(device="cpu").manual_seed(seed)).cuda()
+ image = pipe(
+ prompt=prompt,
+ negative_prompt=negative_prompt,
+ guidance_scale=4.0 if guess_mode else 9.0,
+ num_inference_steps=50 if guess_mode else 20,
+ latents=latent,
+ image=control,
+ # guess_mode=guess_mode,
+ ).images[0]
+ return image
+
+def control_images(control_image_folder, model_name):
+ with open('./control_images.yaml', 'r') as f:
+ d = yaml.safe_load(f)
+ filenames = d[model_name]
+ return [Image.open(f'{control_image_folder}/{fn}').convert("RGB") for fn in filenames]
+
+if __name__ == '__main__':
+ model_name = sys.argv[1]
+ control_image_folder = './control_images/converted/'
+ output_image_folder = './output_images/diffusers/'
+ os.makedirs(output_image_folder, exist_ok=True)
+
+ model_id = 'takuma104/control_v11'
+ subfolder = f'control_v11{model_name}'
+
+ controlnet = ControlNetModel.from_pretrained(model_id, subfolder=subfolder)
+ if model_name == 'p_sd15s2_lineart_anime':
+ base_model_id = 'Linaqruf/anything-v3.0'
+ base_model_revision = None
+ else:
+ base_model_id = "runwayml/stable-diffusion-v1-5"
+ base_model_revision = 'non-ema'
+
+ pipe = StableDiffusionControlNetPipeline.from_pretrained(base_model_id,
+ revision=base_model_revision,
+ controlnet=controlnet,
+ safety_checker=None).to("cuda")
+ pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
+
+ for i, control_image in enumerate(control_images(control_image_folder, model_name)):
+ control = np.array(control_image)[:,:,::-1].copy()
+ control = torch.from_numpy(control).float().cuda() / 255.0
+ control = torch.stack([control for _ in range(1)], dim=0)
+ control = einops.rearrange(control, 'b h w c -> b c h w').clone()
+
+ # if model_name == 'p_sd15_normalbae': # workaround, this should not be necessary
+ # control = torch.flip(control, dims=[1]) # RGB -> BGR
+
+ for seed in range(4):
+ image = generate_image(seed=seed,
+ prompt=test_prompt,
+ negative_prompt=test_negative_prompt,
+ control=control)
+ image.save(f'{output_image_folder}output_{model_name}_{i}_{seed}.png')
diff --git a/gen_compare_v11/gen_diffusers_image.sh b/gen_compare_v11/gen_diffusers_image.sh
new file mode 100755
index 0000000000000000000000000000000000000000..e08adc674bf0406be8e9a3c90e4bfc35793c6f98
--- /dev/null
+++ b/gen_compare_v11/gen_diffusers_image.sh
@@ -0,0 +1,21 @@
+#!/bin/bash
+
+models=(
+ "p_sd15_canny"
+ "p_sd15_depth"
+ "p_sd15_mlsd"
+ "p_sd15_normalbae"
+ "p_sd15_openpose"
+ "p_sd15_scribble"
+ "p_sd15_seg"
+ "p_sd15_softedge"
+ "p_sd15_lineart"
+ "p_sd15s2_lineart_anime"
+)
+# models=("p_sd15_inpaint" "e_sd15_shuffle" "e_sd15_ip2p" "u_sd15_tile")
+
+for model in "${models[@]}"
+do
+ echo $model
+ python gen_diffusers_image.py $model
+done
\ No newline at end of file
diff --git a/gen_compare_v11/gen_markdown.py b/gen_compare_v11/gen_markdown.py
new file mode 100644
index 0000000000000000000000000000000000000000..5665e51aeb9d0e806e565ee7710a62d8de2bcde4
--- /dev/null
+++ b/gen_compare_v11/gen_markdown.py
@@ -0,0 +1,66 @@
+import sys
+import yaml
+import os
+
+cnet_models = [
+ "p_sd15_canny",
+ "p_sd15_depth",
+ "p_sd15_mlsd" ,
+ "p_sd15_normalbae",
+ "p_sd15_openpose",
+ "p_sd15_scribble",
+ "p_sd15_seg",
+ "p_sd15_softedge",
+ "p_sd15_lineart",
+ "p_sd15s2_lineart_anime",
+ # "p_sd15_inpaint",
+ # "e_sd15_shuffle",
+ # "e_sd15_ip2p",
+ # "u_sd15_tile",
+]
+
+processors = ["ref", "diffusers"]
+
+print(f"# ControlNet Generation Comparison")
+print("")
+
+def control_image_filenames(model_name):
+ with open('./control_images.yaml', 'r') as f:
+ d = yaml.safe_load(f)
+ return d[model_name]
+
+def print_header():
+ print("|seed|conditional image|", end="")
+ for proc in processors:
+ print(f"{proc}|", end="")
+ print("")
+
+ print("|", end="")
+ for _ in range(len(processors) + 2):
+ print(":---:|", end="")
+ print("")
+
+def get_url(path):
+ url = "./"
+ # url = 'https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/'
+ return url + path
+
+control_image_folder = './control_images/converted/'
+
+for cnet in cnet_models:
+ print(f"## control_v11{cnet}")
+ print("")
+ print_header()
+
+ for i, control_image_fn in enumerate(control_image_filenames(cnet)):
+ for seed in range(4):
+ print(f"|{seed}|", end="")
+
+ url = get_url(path=f"{control_image_folder}/{control_image_fn}")
+ print(f'|', end="")
+
+ for proc in processors:
+ url = get_url(path=f"output_images/{proc}/output_{cnet}_{i}_{seed:01d}.png")
+ print(f'|', end="")
+
+ print("")
diff --git a/gen_compare_v11/gen_markdowns.sh b/gen_compare_v11/gen_markdowns.sh
new file mode 100755
index 0000000000000000000000000000000000000000..077da3381dad3df721f9fe3be217815fa6f6a924
--- /dev/null
+++ b/gen_compare_v11/gen_markdowns.sh
@@ -0,0 +1,4 @@
+#!/bin/bash
+
+python gen_markdown.py > README.md
+
diff --git a/gen_compare_v11/gen_reference_image.py b/gen_compare_v11/gen_reference_image.py
new file mode 100644
index 0000000000000000000000000000000000000000..de042612c257c94f010fd90a723d920dc8f3bcf7
--- /dev/null
+++ b/gen_compare_v11/gen_reference_image.py
@@ -0,0 +1,77 @@
+# from https://github.com/lllyasviel/ControlNet/blob/main/gradio_canny2image.py
+
+import einops
+import numpy as np
+import torch
+from PIL import Image
+import sys
+import os
+import yaml
+
+CONTROL_NET_PATH = '../../../ControlNet-v1-1-nightly'
+CONTROL_NET_MODEL_PATH = '../../ControlNet-v1-1'
+sys.path.append(CONTROL_NET_PATH)
+
+from share import *
+from pytorch_lightning import seed_everything
+from cldm.model import create_model, load_state_dict
+from cldm.ddim_hacked import DDIMSampler
+from diffusers.utils import load_image
+
+test_prompt = "best quality, extremely detailed"
+test_negative_prompt = "lowres, bad anatomy, worst quality, low quality"
+
+@torch.no_grad()
+def generate(prompt, n_prompt, seed, control, ddim_steps=20, eta=0.0, scale=9.0, H=512, W=512, strength = 1.0, guess_mode=False):
+ seed_everything(seed)
+
+ cond = {"c_concat": [control], "c_crossattn": [model.get_learned_conditioning([prompt] * num_samples)]}
+ un_cond = {"c_concat": None if guess_mode else [control], "c_crossattn": [model.get_learned_conditioning([n_prompt] * num_samples)]}
+ shape = (4, H // 8, W // 8)
+
+ model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13) # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
+ latent = torch.randn((1,) + shape, device="cpu", generator=torch.Generator(device="cpu").manual_seed(seed)).cuda()
+ samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
+ shape, cond, x_T=latent,
+ verbose=False, eta=eta,
+ unconditional_guidance_scale=scale,
+ unconditional_conditioning=un_cond)
+ x_samples = model.decode_first_stage(samples)
+ x_samples = (einops.rearrange(x_samples, 'b c h w -> b h w c') * 127.5 + 127.5).cpu().numpy().clip(0, 255).astype(np.uint8)
+
+ return Image.fromarray(x_samples[0])
+
+def control_images(control_image_folder, model_name):
+ with open('./control_images.yaml', 'r') as f:
+ d = yaml.safe_load(f)
+ filenames = d[model_name]
+ return [Image.open(f'{control_image_folder}/{fn}').convert("RGB") for fn in filenames]
+
+if __name__ == '__main__':
+ model_name = sys.argv[1]
+
+ control_image_folder = './control_images/converted/'
+ output_image_folder = './output_images/ref/'
+ os.makedirs(output_image_folder, exist_ok=True)
+
+ if model_name == 'p_sd15s2_lineart_anime':
+ base_model_file = 'anything-v3-full.safetensors'
+ else:
+ base_model_file = 'v1-5-pruned.ckpt'
+
+ num_samples = 1
+ model = create_model(f'{CONTROL_NET_MODEL_PATH}/control_v11{model_name}.yaml').cpu()
+ model.load_state_dict(load_state_dict(f'{CONTROL_NET_PATH}/models/{base_model_file}', location='cuda'), strict=False)
+ model.load_state_dict(load_state_dict(f'{CONTROL_NET_MODEL_PATH}/control_v11{model_name}.pth', location='cuda'), strict=False)
+ model = model.cuda()
+ ddim_sampler = DDIMSampler(model)
+
+ for i, control_image in enumerate(control_images(control_image_folder, model_name)):
+ control = np.array(control_image)[:,:,::-1].copy()
+ control = torch.from_numpy(control).float().cuda() / 255.0
+ control = torch.stack([control for _ in range(num_samples)], dim=0)
+ control = einops.rearrange(control, 'b h w c -> b c h w').clone()
+
+ for seed in range(4):
+ image = generate(test_prompt, test_negative_prompt, seed=seed, control=control)
+ image.save(f'{output_image_folder}output_{model_name}_{i}_{seed}.png')
diff --git a/gen_compare_v11/gen_reference_image.sh b/gen_compare_v11/gen_reference_image.sh
new file mode 100755
index 0000000000000000000000000000000000000000..1671b78e9690e4d99d5fce90d74247bf4c518402
--- /dev/null
+++ b/gen_compare_v11/gen_reference_image.sh
@@ -0,0 +1,21 @@
+#!/bin/bash
+
+models=(
+ "p_sd15_canny"
+ "p_sd15_depth"
+ "p_sd15_mlsd"
+ "p_sd15_normalbae"
+ "p_sd15_openpose"
+ "p_sd15_scribble"
+ "p_sd15_seg"
+ "p_sd15_softedge"
+ "p_sd15_lineart"
+ "p_sd15s2_lineart_anime"
+)
+# models=("p_sd15_inpaint" "e_sd15_shuffle" "e_sd15_ip2p" "u_sd15_tile")
+
+for model in "${models[@]}"
+do
+ echo $model
+ python gen_reference_image.py $model
+done
\ No newline at end of file
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