test_model.py

import sys
import os
from PIL import Image
import torch
from safetensors.torch import load_file

# 添加src目录到系统路径
sys.path.append(os.path.join(os.path.dirname(__file__), '.'))

from src.model import UNet
from src.pipeline.pipeline import TattooRemovalPipeline

def test_single_image(image_path):
    """测试单张图片的纹身移除效果"""
    # 加载模型
    model = UNet()
    weights_path = "tattoo_remover.safetensors"
    
    if not os.path.exists(weights_path):
        print("错误：找不到模型权重文件")
        print("请从以下地址下载模型权重：")
        print("https://huggingface.co/erickillian/tattoo-removal/blob/main/tattoo_remover.safetensors")
        return
    
    # 加载权重
    state_dict = load_file(weights_path)
    model.load_state_dict(state_dict)
    
    # 创建pipeline
    pipeline = TattooRemovalPipeline(model=model)
    
    # 检查输入图片是否存在
    if not os.path.exists(image_path):
        print(f"错误：找不到输入图片 {image_path}")
        return
    
    try:
        # 处理图片
        input_image = Image.open(image_path).convert('RGB')
        output_image = pipeline(input_image)
        
        # 保存结果
        output_path = os.path.splitext(image_path)[0] + "_removed.png"
        output_image.save(output_path)
        print(f"处理完成！结果已保存至：{output_path}")
        
    except Exception as e:
        print(f"处理过程中出现错误：{str(e)}")

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print("使用方法：python test_model.py <图片路径>")
        print("例如：python test_model.py test_image.jpg")
        sys.exit(1)
    
    test_single_image(sys.argv[1])