脸部LoRA训练项目：素材流水线 + Gradio控制台 + RunPod云端续炼方案（v7续炼完成）

2026-08-10 10:10:34 +08:00
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+# -*- coding: utf-8 -*-
+"""
+LoRA checkpoint 验证工具
+========================
+加载 edit-2511 底模 + 训练好的 LoRA，用多组提示词生成对比图，
+验证 LoRA 是否生效、效果如何。
+
+用法:
+  python validate_lora.py                    # 验证最新 checkpoint
+  python validate_lora.py --ckpt <路径>      # 验证指定 checkpoint
+  python validate_lora.py --all              # 验证 output/checkpoints 下所有
+"""
+import glob
+import os
+import subprocess
+import sys
+
+sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+
+VENV = r"D:\AI\sd\musubi-tuner\.venv\Scripts"
+PY = os.path.join(VENV, "python.exe")
+SRC = r"D:\AI\sd\musubi-tuner\src\musubi_tuner"
+MODELS = r"D:\AI\sd\models\qwen-edit-2511"
+PROJ = r"D:\F\NewI\opencode\daily-workspace\projects\脸部LoRA训练-Qwen-Image"
+
+TRIGGER = "lm_face_v1"
+CKPT_DIR = os.path.join(PROJ, "output", "checkpoints")
+OUT_DIR = os.path.join(PROJ, "output", "验证")
+
+# 验证提示词：同一触发词 + 不同场景，看脸是否稳定一致
+PROMPTS = [
+    ("证件照", f"{TRIGGER}, professional headshot, business attire, neutral expression, studio lighting, plain white background"),
+    ("日常", f"{TRIGGER}, natural lifestyle portrait, by a window with soft diffused sunlight, warm tones"),
+    ("户外全身", f"{TRIGGER}, full body shot, standing in a park, natural daylight, casual clothing"),
+    ("半侧脸", f"{TRIGGER}, three-quarter view portrait, soft golden hour light, shallow depth of field"),
+]
+
+BASE_CMD = [
+    PY, os.path.join(SRC, "qwen_image_generate_image.py"),
+    "--dit", os.path.join(MODELS, "transformer", "diffusion_pytorch_model-00001-of-00005.safetensors"),
+    "--vae", os.path.join(MODELS, "diffusion_pytorch_model.safetensors"),
+    "--text_encoder", os.path.join(MODELS, "text_encoder", "model-00001-of-00004.safetensors"),
+    "--model_version", "edit-2511",
+    "--fp8", "--fp8_scaled", "--blocks_to_swap", "24",
+    "--infer_steps", "25",
+    "--image_size", "1024", "1024",
+    "--seed", "42",
+]
+
+
+def pick_ckpts(args):
+    if args.ckpt:
+        return [args.ckpt]
+    if args.all and os.path.isdir(CKPT_DIR):
+        return sorted(glob.glob(os.path.join(CKPT_DIR, "*.safetensors")))
+    ckpts = sorted(glob.glob(os.path.join(CKPT_DIR, "*.safetensors")))
+    return [ckpts[-1]] if ckpts else []
+
+
+def main():
+    import argparse
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--ckpt", default=None, help="指定 checkpoint 路径")
+    ap.add_argument("--all", action="store_true", help="验证所有 checkpoint")
+    args = ap.parse_args()
+
+    ckpts = pick_ckpts(args)
+    if not ckpts:
+        print(f"[WARN] 没有找到 checkpoint: {CKPT_DIR}")
+        sys.exit(1)
+
+    os.makedirs(OUT_DIR, exist_ok=True)
+    print(f"找到 {len(ckpts)} 个 checkpoint，开始验证（每个 4 张图）...")
+
+    for ckpt in ckpts:
+        name = os.path.splitext(os.path.basename(ckpt))[0]
+        print(f"\n===== {name} =====")
+        for tag, prompt in PROMPTS:
+            out = os.path.join(OUT_DIR, f"{name}_{tag}.png")
+            cmd = BASE_CMD + ["--lora_weight", ckpt, "--lora_multiplier", "0.8",
+                              "--prompt", prompt, "--save_path", out]
+            print(f"  生成 [{tag}] ...")
+            r = subprocess.run(cmd)
+            if r.returncode == 0:
+                print(f"    OK -> {out}")
+            else:
+                print(f"    FAIL exit={r.returncode}")
+
+    print(f"\n验证完成，图片在 {OUT_DIR}")
+
+
+if __name__ == "__main__":
+    main()