1b87a98261
## 主要更新 - ✨ 更新所有依赖到最新稳定版本 - 📝 添加详细的项目文档和模型推荐 - 🔧 配置 VSCode Cloud Studio 预览功能 - 🐛 修复 PyTorch API 弃用警告 ## 依赖更新 - diffusers: 0.27.2 → 0.35.2 - gradio: 4.21.0 → 5.46.0 - peft: 0.7.1 → 0.18.0 - Pillow: 9.5.0 → 11.3.0 - fastapi: 0.108.0 → 0.116.2 ## 新增文件 - CLAUDE.md - 项目架构和开发指南 - UPGRADE_NOTES.md - 详细的升级说明 - .vscode/preview.yml - 预览配置 - .vscode/LAUNCH_GUIDE.md - 启动指南 - .gitignore - 更新的忽略规则 ## 代码修复 - 修复 iopaint/model/ldm.py 中的 torch.cuda.amp.autocast() 弃用警告 ## 文档更新 - README.md - 添加模型推荐和使用指南 - 完整的项目源码（iopaint/） - Web 前端源码（web_app/） 🤖 Generated with Claude Code
119 lines
3.3 KiB
Python
119 lines
3.3 KiB
Python
import os
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from iopaint.const import SD_CONTROLNET_CHOICES
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from iopaint.tests.utils import current_dir, check_device, get_config, assert_equal
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os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
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from pathlib import Path
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import pytest
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import torch
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from iopaint.model_manager import ModelManager
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from iopaint.schema import HDStrategy, SDSampler
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model_name = "runwayml/stable-diffusion-inpainting"
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def convert_controlnet_method_name(name):
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return name.replace("/", "--")
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@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
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@pytest.mark.parametrize("controlnet_method", [SD_CONTROLNET_CHOICES[0]])
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def test_runway_sd_1_5(device, controlnet_method):
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sd_steps = check_device(device)
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model = ModelManager(
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name=model_name,
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device=torch.device(device),
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disable_nsfw=True,
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sd_cpu_textencoder=device == "cuda",
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enable_controlnet=True,
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controlnet_method=controlnet_method,
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)
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cfg = get_config(
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prompt="a fox sitting on a bench",
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sd_steps=sd_steps,
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enable_controlnet=True,
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controlnet_conditioning_scale=0.5,
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controlnet_method=controlnet_method,
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)
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name = f"device_{device}"
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assert_equal(
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model,
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cfg,
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f"sd_controlnet_{convert_controlnet_method_name(controlnet_method)}_{name}.png",
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
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)
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@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
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def test_controlnet_switch(device):
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sd_steps = check_device(device)
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model = ModelManager(
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name=model_name,
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device=torch.device(device),
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disable_nsfw=True,
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sd_cpu_textencoder=False,
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cpu_offload=True,
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enable_controlnet=True,
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controlnet_method="lllyasviel/control_v11p_sd15_canny",
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)
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cfg = get_config(
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prompt="a fox sitting on a bench",
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sd_steps=sd_steps,
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enable_controlnet=True,
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controlnet_method="lllyasviel/control_v11f1p_sd15_depth",
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)
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assert_equal(
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model,
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cfg,
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f"controlnet_switch_canny_to_depth_device_{device}.png",
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
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fx=1.2
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)
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@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
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@pytest.mark.parametrize(
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"local_file", ["sd-v1-5-inpainting.ckpt", "v1-5-pruned-emaonly.safetensors"]
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)
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def test_local_file_path(device, local_file):
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sd_steps = check_device(device)
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controlnet_kwargs = dict(
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enable_controlnet=True,
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controlnet_method=SD_CONTROLNET_CHOICES[0],
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)
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model = ModelManager(
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name=local_file,
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device=torch.device(device),
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disable_nsfw=True,
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sd_cpu_textencoder=False,
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cpu_offload=True,
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**controlnet_kwargs,
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)
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cfg = get_config(
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prompt="a fox sitting on a bench",
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sd_steps=sd_steps,
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**controlnet_kwargs,
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)
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name = f"device_{device}"
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assert_equal(
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model,
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cfg,
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f"{convert_controlnet_method_name(controlnet_kwargs['controlnet_method'])}_local_model_{name}.png",
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
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)
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