add shuffle

gen_compare_v11/README.md

@@ -100,6 +100,22 @@
 |1|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/lineartanime_anime2_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/lineartanime_anime2_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_p_sd15s2_lineart_anime_0_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_p_sd15s2_lineart_anime_0_1.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_p_sd15s2_lineart_anime_0_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_p_sd15s2_lineart_anime_0_1.png"/></a>|
 |2|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/lineartanime_anime2_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/lineartanime_anime2_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_p_sd15s2_lineart_anime_0_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_p_sd15s2_lineart_anime_0_2.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_p_sd15s2_lineart_anime_0_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_p_sd15s2_lineart_anime_0_2.png"/></a>|
 |3|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/lineartanime_anime2_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/lineartanime_anime2_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_p_sd15s2_lineart_anime_0_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_p_sd15s2_lineart_anime_0_3.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_p_sd15s2_lineart_anime_0_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_p_sd15s2_lineart_anime_0_3.png"/></a>|
+## control_v11e_sd15_shuffle
+
+|seed|conditional image|ref|diffusers|
+|:---:|:---:|:---:|:---:|
+|0|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_0.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_0.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_0.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_0.png"/></a>|
+|1|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_1.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_1.png"/></a>|
+|2|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_2.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_2.png"/></a>|
+|3|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_vermeer_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_0_3.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_0_3.png"/></a>|
+|0|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_0.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_0.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_0.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_0.png"/></a>|
+|1|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_1.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_1.png"/></a>|
+|2|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_2.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_2.png"/></a>|
+|3|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_room_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_1_3.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_1_3.png"/></a>|
+|0|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_0.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_0.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_0.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_0.png"/></a>|
+|1|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_1.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_1.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_1.png"/></a>|
+|2|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_2.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_2.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_2.png"/></a>|
+|3|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/control_images/converted/shuffle_house_512x512.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/ref/output_e_sd15_shuffle_2_3.png"/></a>|<a href="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_3.png"><img width="128" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/gen_compare_v11/output_images/diffusers/output_e_sd15_shuffle_2_3.png"/></a>|
 ## control_v11p_sd15_inpaint
 
 |seed|conditional image|ref|diffusers|

gen_compare_v11/control_images.yaml

@@ -26,9 +26,14 @@ p_sd15_seg:
   - uniformer_house_512x512.png
 p_sd15s2_lineart_anime:
   - lineartanime_anime2_512x512.png
+e_sd15_shuffle:
+  - shuffle_vermeer_512x512.png
+  - shuffle_room_512x512.png
+  - shuffle_house_512x512.png
 # p_sd15_inpaint:
-# e_sd15_shuffle:
-#   - colorshuffle_vermeer_512x512.png
-#   - shuffle_vermeer_512x512.png
 # e_sd15_ip2p:
 # u_sd15_tile:
+# f1e_sd15_tile:
+#   - dog_64x64.png
+
+  

gen_compare_v11/gen_diffusers_image.sh

@@ -11,6 +11,7 @@ models=(
     "p_sd15_softedge"
     "p_sd15_lineart"
     "p_sd15s2_lineart_anime"
+    "e_sd15_shuffle"
 )
 # models=("p_sd15_inpaint" "e_sd15_shuffle" "e_sd15_ip2p" "u_sd15_tile")
 

gen_compare_v11/gen_diffusers_image_for_tile.py

@@ -0,0 +1,92 @@
+# Diffusers' ControlNet Implementation Subjective Evaluation
+
+import torch
+import os
+
+from diffusers import DiffusionPipeline, ControlNetModel, DDIMScheduler
+
+from PIL import Image
+
+test_prompt = "best quality, extremely detailed"
+test_negative_prompt = "blur, lowres, bad anatomy, worst quality, low quality"
+
+def resize_for_condition_image(input_image: Image, resolution: int):
+    input_image = input_image.convert("RGB")
+    W, H = input_image.size
+    k = float(resolution) / min(H, W)
+    H *= k
+    W *= k
+    H = int(round(H / 64.0)) * 64
+    W = int(round(W / 64.0)) * 64
+    img = input_image.resize((W, H), resample=Image.LANCZOS if k > 1 else Image.AREA)
+    return img
+
+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,
+        controlnet_conditioning_image=control,
+        strength=1.0,
+        # guess_mode=guess_mode,
+    ).images[0]
+    return image
+
+
+if __name__ == "__main__":
+    model_name = "f1e_sd15_tile"
+    original_image_folder = "./control_images/"
+    control_image_folder = "./control_images/converted/"
+    output_image_folder = "./output_images/diffusers/"
+    os.makedirs(output_image_folder, exist_ok=True)
+
+    # model_id = f"lllyasviel/control_v11{model_name}"
+    # controlnet = ControlNetModel.from_pretrained(model_id)
+    controlnet = ControlNetModel.from_pretrained('takuma104/control_v11', 
+                                                subfolder='control_v11f1e_sd15_tile')
+
+    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 = DiffusionPipeline.from_pretrained(
+        base_model_id,
+        revision=base_model_revision,
+        custom_pipeline="stable_diffusion_controlnet_img2img",
+        controlnet=controlnet,
+        safety_checker=None,
+    ).to("cuda")
+    pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
+
+    original_image_filenames = [
+        "dog_64x64.png",
+    ]
+
+    image_conditions = [
+        resize_for_condition_image(
+            Image.open(f"{original_image_folder}{fn}"),
+            resolution=512,
+        )
+        for fn in original_image_filenames
+    ]
+
+    for i, control in enumerate(image_conditions):
+        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")

gen_compare_v11/gen_markdown.py

@@ -13,8 +13,8 @@ cnet_models = [
     "p_sd15_softedge",
     "p_sd15_lineart",
     "p_sd15s2_lineart_anime",
+    "e_sd15_shuffle",
     # "p_sd15_inpaint",
-    # "e_sd15_shuffle",
     # "e_sd15_ip2p",
     # "u_sd15_tile",
 ]

gen_compare_v11/gen_reference_image.py

@@ -8,7 +8,7 @@ import sys
 import os
 import yaml
 
-CONTROL_NET_PATH = '../../../ControlNet-v1-1-nightly'
+CONTROL_NET_PATH = '/home/takuma/Documents/co/ControlNet-v1-1-nightly/'
 CONTROL_NET_MODEL_PATH = '../../ControlNet-v1-1'
 sys.path.append(CONTROL_NET_PATH)
 
@@ -26,7 +26,11 @@ def generate(prompt, n_prompt, seed, control, ddim_steps=20, eta=0.0, scale=9.0,
     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)]}
+
+    if model.global_average_pooling:
+        un_cond = {"c_concat": None, "c_crossattn": [model.get_learned_conditioning([n_prompt] * num_samples)]}
+    else:
+        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

gen_compare_v11/gen_reference_image.sh

@@ -11,6 +11,7 @@ models=(
     "p_sd15_softedge"
     "p_sd15_lineart"
     "p_sd15s2_lineart_anime"
+    "f1e_sd15_tile"
 )
 # models=("p_sd15_inpaint" "e_sd15_shuffle" "e_sd15_ip2p" "u_sd15_tile")
 

gen_compare_v11/gen_reference_image_for_tile.py

@@ -0,0 +1,111 @@
+# 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 = '/home/takuma/Documents/co/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 = "blur, lowres, bad anatomy, worst quality, low quality"
+
+@torch.no_grad()
+def generate(prompt, n_prompt, seed, control, image, ddim_steps=20, eta=0.0, scale=9.0, H=512, W=512, strength = 1.0, guess_mode=False, denoise_strength=1.0):
+    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)
+
+    noise = torch.randn((1,) + shape, device="cpu", generator=torch.Generator(device="cpu").manual_seed(seed)).cuda()
+
+    ddim_sampler.make_schedule(ddim_steps, ddim_eta=eta, verbose=True)
+    t_enc = min(int(denoise_strength * ddim_steps), ddim_steps - 1)
+    z = model.get_first_stage_encoding(model.encode_first_stage(image))
+    z_enc = ddim_sampler.stochastic_encode(z, torch.tensor([t_enc] * num_samples).to(model.device), noise=noise)
+
+    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
+
+    samples = ddim_sampler.decode(z_enc, cond, t_enc, 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]
+
+def resize_for_condition_image(input_image: Image, resolution: int):
+    input_image = input_image.convert("RGB")
+    W, H = input_image.size
+    k = float(resolution) / min(H, W)
+    H *= k
+    W *= k
+    H = int(round(H / 64.0)) * 64
+    W = int(round(W / 64.0)) * 64
+    img = input_image.resize((W, H), resample=Image.LANCZOS if k > 1 else Image.AREA)
+    return img
+
+if __name__ == '__main__':
+    model_name = "f1e_sd15_tile"
+
+    original_image_folder = "./control_images/"
+    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)
+
+    original_image_filenames = [
+        "dog_64x64.png",
+    ]
+
+    image_conditions = [
+        resize_for_condition_image(
+            Image.open(f"{original_image_folder}{fn}"),
+            resolution=512,
+        )
+        for fn in original_image_filenames
+    ]
+
+
+    for i, control_image in enumerate(image_conditions):
+        control = np.array(control_image).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()
+
+        img = np.array(control_image).copy()
+        img = torch.from_numpy(img).float().cuda() / 127.0 - 1.0
+        img = torch.stack([img for _ in range(num_samples)], dim=0)
+        img = einops.rearrange(img, '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=img)
+            image.save(f'{output_image_folder}output_{model_name}_{i}_{seed}.png')