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.ipynb_checkpoints/README-checkpoint.md
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# Flux Anime Landscape lora Usage
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- 🙂 This lora focus light up the anime landscape scene. ☀
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- Trigger word: anime style
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## Installtion
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```bash
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pip install -U diffusers transformers torch sentencepiece peft controlnet-aux moviepy protobuf
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```
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## Demo
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```python
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import torch
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from diffusers import FluxPipeline
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pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
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pipe.load_lora_weights("Flux_Anime_Landscape_Lora/my_first_flux_lora_v1_000001500.safetensors")
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pipe.enable_sequential_cpu_offload()
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prompt = "anime style ,high quality nature video featuring a red panda balancing on a bamboo stem while a bird lands on it's head, on the background there is a waterfall"
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image = pipe(prompt,
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num_inference_steps=50,
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guidance_scale=3.5,
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).images[0]
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image.save("ani0.png")
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from IPython import display
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display.Image("ani0.png", width=512, height=512)
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```
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```python
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prompt = "anime style, Sunlight filters through clouds onto a cherry blossom-filled meadow, where a blue-haired youth in an indigo coat stands by a vermilion bridge, holding a book as petals drift past his smile. The scene blends dynamic nature with human stillness, using pink, red and blue hues to create harmony, while symbolic elements like blossoms and books add depth."
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image = pipe(prompt,
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num_inference_steps=50,
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guidance_scale=3.5,
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).images[0]
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image.save("ani1.png")
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from IPython import display
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display.Image("ani1.png", width=512, height=512)
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```
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## OmniConsistency Demo
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- refer to https://github.com/showlab/OmniConsistency
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- Image Input (xiang_image.jpg)
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```python
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import time
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import torch
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import os
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from tqdm import tqdm
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from PIL import Image
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from src_inference.pipeline import FluxPipeline
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from src_inference.lora_helper import set_single_lora
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# 初始化基础模型
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base_path = "black-forest-labs/FLUX.1-dev"
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pipe = FluxPipeline.from_pretrained(base_path, torch_dtype=torch.bfloat16)
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# 设置OmniConsistency LoRA
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set_single_lora(pipe.transformer,
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"OmniConsistency/OmniConsistency.safetensors",
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lora_weights=[1], cond_size=512)
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pipe.load_lora_weights("Flux_Anime_Landscape_Lora/my_first_flux_lora_v1_000001500.safetensors")
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# 启用CPU offload节省显存
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pipe.enable_sequential_cpu_offload()
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image_path1 = "xiang_image.jpg"
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subject_images = []
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spatial_image = [Image.open(image_path1).convert("RGB")]
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width, height = 1024, 1024
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style_prompt = "anime style, A young man with black hair and glasses sits outdoors in a white T-shirt, surrounded by lush green foliage. The natural backdrop contrasts with his relaxed posture, creating a serene vibe."
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image = pipe(
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style_prompt,
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height=height,
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width=width,
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guidance_scale=3.5,
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num_inference_steps=25,
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max_sequence_length=512,
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generator=torch.Generator("cpu").manual_seed(5),
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spatial_images=spatial_image,
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subject_images=subject_images,
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cond_size=512,
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).images[0]
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image.save("im0.png")
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from IPython import display
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display.Image("im0.png", width=512, height=512)
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```
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