消除视频边缘白色边框：使用rembg进行背景替换的优化教程

from rembg import remove, new_session

# 创建 rembg 会话，针对不同模型
rembg_session_u2net = new_session("u2net")
rembg_session_u2net_human_seg = new_session("u2net_human_seg")

# ... (视频帧处理循环)

first_pass_output_image = remove(
    input_image,
    session=rembg_session_u2net_human_seg)

second_pass_output_image = remove(first_pass_output_image,
                                    post_process_mask=True,
                                    alpha_matting=True,
                                    alpha_matting_foreground_threshold=240,
                                    alpha_matting_background_threshold=10,
                                    alpha_matting_erode_size=15,
                                    session=rembg_session_u2net)

second_pass_output_image.save(output_path)

from rembg import remove, new_session
from PIL import Image
import cv2
import os
from moviepy.editor import VideoFileClip, ImageSequenceClip

# 创建 rembg 会话，针对不同模型
rembg_session_u2net = new_session("u2net")
rembg_session_u2net_human_seg = new_session("u2net_human_seg")

def process_frame(input_image_path, output_image_path):
    """处理单帧图像，移除背景并消除白色边框."""
    try:
        with open(input_image_path, 'rb') as f:
            input_image = f.read()

        # 第一步：使用 u2net_human_seg 模型进行初步移除
        first_pass_output_image = remove(
            input_image,
            session=rembg_session_u2net_human_seg)

        # 第二步：使用 u2net 模型进行精细边缘处理
        second_pass_output_image = remove(first_pass_output_image,
                                            post_process_mask=True,
                                            alpha_matting=True,
                                            alpha_matting_foreground_threshold=240,
                                            alpha_matting_background_threshold=10,
                                            alpha_matting_erode_size=15,
                                            session=rembg_session_u2net)

        with open(output_image_path, 'wb') as output_file:
            output_file.write(second_pass_output_image)

        return True
    except Exception as e:
        print(f"Error processing frame: {e}")
        return False


def process_video_with_audio(input_video_path, output_video_path='output_video.mp4', frame_limit=40):
    """处理视频，逐帧替换背景，并保留音频."""

    if not os.path.exists(input_video_path):
        print(f"Video file '{input_video_path}' not found.")
        return None

    video_capture = cv2.VideoCapture(input_video_path)

    if not video_capture.isOpened():
        print(f"Failed to open the video '{input_video_path}'.")
        return None

    frame_count = 0
    frame_list = []

    while frame_count < frame_limit:
        ret, frame = video_capture.read()

        if not ret:
            print(f"Failed to read frame {frame_count} from the video.")
            break

        frame_name = f'frame{frame_count}.png'
        frame_path = 'masked/' + frame_name
        cv2.imwrite(frame_path, frame)

        output_image_path = f'masked/processed_frame{frame_count}.png'

        # 使用改进的帧处理函数
        if process_frame(frame_path, output_image_path):
            background_img_path = 'Cover.jpg'  # 替换为你想要的背景图片

            if os.path.exists(background_img_path):
                background_img = Image.open(background_img_path)
                foreground_img = Image.open(output_image_path).convert("RGBA")

                background_img = background_img.resize((foreground_img.width, foreground_img.height))
                composite_img = Image.alpha_composite(background_img.convert("RGBA"), foreground_img)

                frame_list.append(np.array(composite_img))
                frame_count += 1
                print(f"Processing frame {frame_count}...")
            else:
                print(f"Background image '{background_img_path}' not found")
                break # 停止处理，因为背景图片缺失
        else:
            print(f"Failed to process frame {frame_count}, skipping.")
            break  # 停止处理，如果帧处理失败

    video_capture.release() # 释放VideoCapture对象

    if frame_list:
        original_clip = VideoFileClip(input_video_path)
        audio = original_clip.audio

        processed_clip = ImageSequenceClip(frame_list, fps=30)
        processed_clip = processed_clip.set_audio(audio)
        processed_clip = processed_clip.subclip(0, processed_clip.duration)

        processed_clip.write_videofile(output_video_path, codec='libx264', audio_codec='aac')

        print(f"Video created at '{output_video_path}' with audio.")
        return output_video_path
    else:
        print("No processed frames to create a video.")
        return None

# 确保 'masked' 目录存在
if not os.path.exists('masked'):
    os.makedirs('masked')

# 示例用法:
video_path = 'alex.mp4'  # 替换为你的视频路径
output_path = process_video_with_audio(video_path)