如何用Python源码从视频生成GIF 动图生成的Python源码操作示例

import imageio
import os
from PIL import Image

def video_to_gif(video_path, gif_path, fps=10, resize=None):
    """
    将视频转换为GIF。

    Args:
        video_path: 视频文件路径。
        gif_path: GIF文件保存路径。
        fps: GIF的帧率，默认为10。
        resize: 缩放尺寸，例如 (320, 240)，默认为None，不缩放。
    """
    try:
        reader = imageio.get_reader(video_path)
        frames = []
        for i, frame in enumerate(reader):
            img = Image.fromarray(frame)
            if resize:
                img = img.resize(resize)
            frames.append(img)

        imageio.mimsave(gif_path, [frame for frame in frames], fps=fps)
        print(f"视频已成功转换为GIF: {gif_path}")

    except Exception as e:
        print(f"转换失败: {e}")

# 示例用法
if __name__ == "__main__":
    video_file = "input.mp4"  # 替换为你的视频文件
    gif_file = "output.gif"  # 替换为你的GIF文件
    video_to_gif(video_file, gif_file, fps=15, resize=(640, 480)) # 调整fps和resize

# 使用 Pillow 进行颜色量化 (示例)
from PIL import Image

def optimize_gif(gif_path, optimized_path):
    """
    优化GIF颜色表。
    """
    try:
        im = Image.open(gif_path)
        im = im.convert('P', palette=Image.ADAPTIVE, colors=256) # 颜色量化
        im.save(optimized_path, optimize=True)
        print(f"GIF已优化: {optimized_path}")
    except Exception as e:
        print(f"优化失败: {e}")

# 示例用法
# optimize_gif("output.gif", "optimized.gif")

import imageio
from PIL import Image

def video_to_gif_chunked(video_path, gif_path, chunk_size=100, fps=10, resize=None):
    """
    分块处理视频，避免内存溢出。
    """
    try:
        reader = imageio.get_reader(video_path)
        total_frames = reader.count_frames()  # 获取总帧数 (可能不准确，取决于视频格式)
        print(f"总帧数: {total_frames}")

        with imageio.get_writer(gif_path, mode='I', fps=fps) as writer: # 使用 imageio 的 writer
            for i in range(0, total_frames, chunk_size):
                print(f"处理帧: {i} - {i + chunk_size}")
                for j in range(i, min(i + chunk_size, total_frames)):
                    try:
                        frame = reader.get_data(j) # 直接获取指定帧
                        img = Image.fromarray(frame)
                        if resize:
                            img = img.resize(resize)
                        writer.append_data(frame) # 添加到 GIF
                    except Exception as e:
                        print(f"读取帧 {j} 失败: {e}")

        print(f"视频已成功转换为GIF (分块处理): {gif_path}")

    except Exception as e:
        print(f"转换失败: {e}")

# 示例用法
# video_to_gif_chunked("large_video.mp4", "large_output.gif", chunk_size=50, fps=5, resize=(320, 240))

import imageio
from PIL import Image, ImageDraw

def video_to_gif_filtered(video_path, gif_path, filter_func=None, fps=10, resize=None):
    """
    将视频转换为GIF，并进行帧过滤。
    """
    try:
        reader = imageio.get_reader(video_path)
        frames = []
        for i, frame in enumerate(reader):
            img = Image.fromarray(frame)
            if resize:
                img = img.resize(resize)

            if filter_func is None or filter_func(img, i): # 应用过滤器
                frames.append(img)

        imageio.mimsave(gif_path, [frame for frame in frames], fps=fps)
        print(f"视频已成功转换为GIF (已过滤): {gif_path}")

    except Exception as e:
        print(f"转换失败: {e}")

def add_watermark(img, frame_index):
    """
    添加水印的示例过滤器。
    """
    draw = ImageDraw.Draw(img)
    text = f"Frame: {frame_index}"
    draw.text((10, 10), text, fill=(255, 255, 255))  # 白色水印
    return True  # 保留所有帧

# 示例用法
if __name__ == "__main__":
    video_file = "input.mp4"
    gif_file = "filtered.gif"
    video_to_gif_filtered(video_file, gif_file, filter_func=add_watermark, fps=10, resize=(320, 240))