update docs

examples/flux2/model_inference/Template-KleinBase4B-Aesthetic.py

@@ -0,0 +1,52 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+pipe.dit = pipe.enable_lora_hot_loading(pipe.dit) # Important!
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Aesthetic")],
+)
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "lora_ids": list(range(1, 180, 2)),
+        "lora_scales": 1.0,
+        "merge_type": "mean",
+    }],
+    negative_template_inputs = [{
+        "lora_ids": list(range(1, 180, 2)),
+        "lora_scales": 1.0,
+        "merge_type": "mean",
+    }],
+)
+image.save("image_Aesthetic_1.0.jpg")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "lora_ids": list(range(1, 180, 2)),
+        "lora_scales": 2.5,
+        "merge_type": "mean",
+    }],
+    negative_template_inputs = [{
+        "lora_ids": list(range(1, 180, 2)),
+        "lora_scales": 2.5,
+        "merge_type": "mean",
+    }],
+)
+image.save("image_Aesthetic_2.5.jpg")

examples/flux2/model_inference/Template-KleinBase4B-Brightness.py

@@ -0,0 +1,43 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Brightness")],
+)
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{"scale": 0.7}],
+    negative_template_inputs = [{"scale": 0.5}]
+)
+image.save("image_Brightness_light.jpg")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{"scale": 0.5}],
+    negative_template_inputs = [{"scale": 0.5}]
+)
+image.save("image_Brightness_normal.jpg")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{"scale": 0.3}],
+    negative_template_inputs = [{"scale": 0.5}]
+)
+image.save("image_Brightness_dark.jpg")

examples/flux2/model_inference/Template-KleinBase4B-ControlNet.py

@@ -0,0 +1,54 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+from modelscope import dataset_snapshot_download
+from PIL import Image
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-ControlNet")],
+)
+dataset_snapshot_download(
+    "DiffSynth-Studio/examples_in_diffsynth",
+    allow_file_pattern=["templates/*"],
+    local_dir="data/examples",
+)
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone, bathed in bright sunshine.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_depth.jpg"),
+        "prompt": "A cat is sitting on a stone, bathed in bright sunshine.",
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_depth.jpg"),
+        "prompt": "",
+    }],
+)
+image.save("image_ControlNet_sunshine.jpg")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone, surrounded by colorful magical particles.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_depth.jpg"),
+        "prompt": "A cat is sitting on a stone, surrounded by colorful magical particles.",
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_depth.jpg"),
+        "prompt": "",
+    }],
+)
+image.save("image_ControlNet_magic.jpg")

examples/flux2/model_inference/Template-KleinBase4B-Edit.py

@@ -0,0 +1,54 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+from modelscope import dataset_snapshot_download
+from PIL import Image
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Edit")],
+)
+dataset_snapshot_download(
+    "DiffSynth-Studio/examples_in_diffsynth",
+    allow_file_pattern=["templates/*"],
+    local_dir="data/examples",
+)
+image = template(
+    pipe,
+    prompt="Put a hat on this cat.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "prompt": "Put a hat on this cat.",
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "prompt": "",
+    }],
+)
+image.save("image_Edit_hat.jpg")
+image = template(
+    pipe,
+    prompt="Make the cat turn its head to look to the right.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "prompt": "Make the cat turn its head to look to the right.",
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "prompt": "",
+    }],
+)
+image.save("image_Edit_head.jpg")

examples/flux2/model_inference/Template-KleinBase4B-Inpaint.py

@@ -0,0 +1,56 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+from modelscope import dataset_snapshot_download
+from PIL import Image
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Inpaint")],
+)
+dataset_snapshot_download(
+    "DiffSynth-Studio/examples_in_diffsynth",
+    allow_file_pattern=["templates/*"],
+    local_dir="data/examples",
+)
+image = template(
+    pipe,
+    prompt="An orange cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "mask": Image.open("data/examples/templates/image_mask_1.jpg"),
+        "force_inpaint": True,
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "mask": Image.open("data/examples/templates/image_mask_1.jpg"),
+    }],
+)
+image.save("image_Inpaint_1.jpg")
+image = template(
+    pipe,
+    prompt="A cat wearing sunglasses is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "mask": Image.open("data/examples/templates/image_mask_2.jpg"),
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_reference.jpg"),
+        "mask": Image.open("data/examples/templates/image_mask_2.jpg"),
+    }],
+)
+image.save("image_Inpaint_2.jpg")
+

examples/flux2/model_inference/Template-KleinBase4B-PandaMeme.py

@@ -0,0 +1,43 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-PandaMeme")],
+)
+image = template(
+    pipe,
+    prompt="A meme with a sleepy expression.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{}],
+    negative_template_inputs = [{}],
+)
+image.save("image_PandaMeme_sleepy.jpg")
+image = template(
+    pipe,
+    prompt="A meme with a happy expression.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{}],
+    negative_template_inputs = [{}],
+)
+image.save("image_PandaMeme_happy.jpg")
+image = template(
+    pipe,
+    prompt="A meme with a surprised expression.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{}],
+    negative_template_inputs = [{}],
+)
+image.save("image_PandaMeme_surprised.jpg")

examples/flux2/model_inference/Template-KleinBase4B-Sharpness.py

@@ -0,0 +1,35 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Sharpness")],
+)
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{"scale": 0.1}],
+    negative_template_inputs = [{"scale": 0.5}],
+)
+image.save("image_Sharpness_0.1.jpg")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{"scale": 0.8}],
+    negative_template_inputs = [{"scale": 0.5}],
+)
+image.save("image_Sharpness_0.8.jpg")

examples/flux2/model_inference/Template-KleinBase4B-SoftRGB.py

@@ -0,0 +1,52 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-SoftRGB")],
+)
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "R": 128/255,
+        "G": 128/255,
+        "B": 128/255
+    }],
+)
+image.save("image_rgb_normal.jpg")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "R": 208/255,
+        "G": 185/255,
+        "B": 138/255
+    }],
+)
+image.save("image_rgb_warm.jpg")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "R": 94/255,
+        "G": 163/255,
+        "B": 174/255
+    }],
+)
+image.save("image_rgb_cold.jpg")

examples/flux2/model_inference/Template-KleinBase4B-Upscaler.py

@@ -0,0 +1,54 @@
+from diffsynth.diffusion.template import TemplatePipeline
+from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
+import torch
+from modelscope import dataset_snapshot_download
+from PIL import Image
+
+pipe = Flux2ImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
+)
+template = TemplatePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Upscaler")],
+)
+dataset_snapshot_download(
+    "DiffSynth-Studio/examples_in_diffsynth",
+    allow_file_pattern=["templates/*"],
+    local_dir="data/examples",
+)
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_lowres_512.jpg"),
+        "prompt": "A cat is sitting on a stone.",
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_lowres_512.jpg"),
+        "prompt": "",
+    }],
+)
+image.save("image_Upscaler_1.png")
+image = template(
+    pipe,
+    prompt="A cat is sitting on a stone.",
+    seed=0, cfg_scale=4, num_inference_steps=50,
+    template_inputs = [{
+        "image": Image.open("data/examples/templates/image_lowres_100.jpg"),
+        "prompt": "A cat is sitting on a stone.",
+    }],
+    negative_template_inputs = [{
+        "image": Image.open("data/examples/templates/image_lowres_100.jpg"),
+        "prompt": "",
+    }],
+)
+image.save("image_Upscaler_2.png")

examples/flux2/model_inference/Template-KleinBase4B.py

@@ -1,256 +0,0 @@
-from diffsynth.diffusion.template import TemplatePipeline
-from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
-import torch
-from PIL import Image
-import numpy as np
-
-def load_template_pipeline(model_ids):
-    template = TemplatePipeline.from_pretrained(
-        torch_dtype=torch.bfloat16,
-        device="cuda",
-        model_configs=[ModelConfig(model_id=model_id) for model_id in model_ids],
-    )
-    return template
-
-# Base Model
-pipe = Flux2ImagePipeline.from_pretrained(
-    torch_dtype=torch.bfloat16,
-    device="cuda",
-    model_configs=[
-        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
-        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
-        ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
-    ],
-    tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
-)
-# image = pipe(
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-# )
-# image.save("image_base.jpg")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-Brightness"])
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{"scale": 0.7}],
-#     negative_template_inputs = [{"scale": 0.5}]
-# )
-# image.save("image_Brightness_light.jpg")
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{"scale": 0.5}],
-#     negative_template_inputs = [{"scale": 0.5}]
-# )
-# image.save("image_Brightness_normal.jpg")
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{"scale": 0.3}],
-#     negative_template_inputs = [{"scale": 0.5}]
-# )
-# image.save("image_Brightness_dark.jpg")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-ControlNet"])
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone, bathed in bright sunshine.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_depth.jpg"),
-#         "prompt": "A cat is sitting on a stone, bathed in bright sunshine.",
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_depth.jpg"),
-#         "prompt": "",
-#     }],
-# )
-# image.save("image_ControlNet_sunshine.jpg")
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone, surrounded by colorful magical particles.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_depth.jpg"),
-#         "prompt": "A cat is sitting on a stone, surrounded by colorful magical particles.",
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_depth.jpg"),
-#         "prompt": "",
-#     }],
-# )
-# image.save("image_ControlNet_magic.jpg")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-Edit"])
-# image = template(
-#     pipe,
-#     prompt="Put a hat on this cat.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "prompt": "Put a hat on this cat.",
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "prompt": "",
-#     }],
-# )
-# image.save("image_Edit_hat.jpg")
-# image = template(
-#     pipe,
-#     prompt="Make the cat turn its head to look to the right.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "prompt": "Make the cat turn its head to look to the right.",
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "prompt": "",
-#     }],
-# )
-# image.save("image_Edit_head.jpg")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-Upscaler"])
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_lowres_512.jpg"),
-#         "prompt": "A cat is sitting on a stone.",
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_lowres_512.jpg"),
-#         "prompt": "",
-#     }],
-# )
-# image.save("image_Upscaler_1.png")
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_lowres_100.jpg"),
-#         "prompt": "A cat is sitting on a stone.",
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_lowres_100.jpg"),
-#         "prompt": "",
-#     }],
-# )
-# image.save("image_Upscaler_2.png")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-SoftRGB"])
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "R": 128/255,
-#         "G": 128/255,
-#         "B": 128/255
-#     }],
-# )
-# image.save("image_rgb_normal.jpg")
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "R": 208/255,
-#         "G": 185/255,
-#         "B": 138/255
-#     }],
-# )
-# image.save("image_rgb_warm.jpg")
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "R": 94/255,
-#         "G": 163/255,
-#         "B": 174/255
-#     }],
-# )
-# image.save("image_rgb_cold.jpg")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-PandaMeme"])
-# image = template(
-#     pipe,
-#     prompt="A meme with a sleepy expression.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{}],
-#     negative_template_inputs = [{}],
-# )
-# image.save("image_PandaMeme_sleepy.jpg")
-# image = template(
-#     pipe,
-#     prompt="A meme with a happy expression.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{}],
-#     negative_template_inputs = [{}],
-# )
-# image.save("image_PandaMeme_happy.jpg")
-# image = template(
-#     pipe,
-#     prompt="A meme with a surprised expression.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{}],
-#     negative_template_inputs = [{}],
-# )
-# image.save("image_PandaMeme_surprised.jpg")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-Sharpness"])
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{"scale": 0.1}],
-#     negative_template_inputs = [{"scale": 0.5}],
-# )
-# image.save("image_Sharpness_0.1.jpg")
-# image = template(
-#     pipe,
-#     prompt="A cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{"scale": 0.8}],
-#     negative_template_inputs = [{"scale": 0.5}],
-# )
-# image.save("image_Sharpness_0.8.jpg")
-
-# template = load_template_pipeline(["DiffSynth-Studio/Template-KleinBase4B-Inpaint"])
-# image = template(
-#     pipe,
-#     prompt="An orange cat is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "mask": Image.open("data/assets/image_mask_1.jpg"),
-#         "force_inpaint": True,
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "mask": Image.open("data/assets/image_mask_1.jpg"),
-#     }],
-# )
-# image.save("image_Inpaint_1.jpg")
-# image = template(
-#     pipe,
-#     prompt="A cat wearing sunglasses is sitting on a stone.",
-#     seed=0, cfg_scale=4, num_inference_steps=50,
-#     template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "mask": Image.open("data/assets/image_mask_2.jpg"),
-#     }],
-#     negative_template_inputs = [{
-#         "image": Image.open("data/assets/image_reference.jpg"),
-#         "mask": Image.open("data/assets/image_mask_2.jpg"),
-#     }],
-# )
-# image.save("image_Inpaint_2.jpg")