python 用OpenCV 将图片转视频

  1. import os
  2. import cv2
  3. import numpy as np
  4.  
  5. cv2.VideoWriter（）参数  cv2.VideoWriter() 是 OpenCV 中用于创建视频文件的类。它的参数如下：
  6. filename：保存视频的文件名。
  7. fourcc：指定视频编解码器的 FourCC 代码，用于将视频压缩成指定格式，例如：“XVID”、“MJPG”, "mp4v"等。可以使用 cv2.VideoWriter_fourcc() 函数来获取 FourCC 代码。
  8. fps：指定视频帧率，即每秒显示的帧数。
  9. frameSize：指定视频帧的大小，即视频的分辨率，可以使用 (width, height) 形式的元组来指定。
  10. isColor：指定是否为彩色视频。如果为 True，则为彩色视频；如果为 False，则为灰度视频。
  11. 其中，前三个参数是必需的，后两个参数是可选的。例如：
  12. fps = 25
  13. cv2.VideoWriter('output.avi', cv2.VideoWriter_fourcc(*'XVID'), fps, (640, 480))
  14.  
  15. def resize_img():
  16.     target_size = (1000, 1000)  # 所有图片缩放设置一致尺寸，目标尺寸
  17.     path = './images'
  18.     path_new = './images_new'
  19.     if not os.path.exists(path_new):
  20.         os.makedirs(path_new)
  21.     filelists = []
  22.     imglist = []
  23.     for i in os.listdir(path):
  24.         file_path = os.path.join(path, i)
  25.         print(file_path)
  26.         img = cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), cv2.IMREAD_COLOR)
  27.         size = img.shape
  28.         h, w = size[0], size[1]
  29.         target_h, target_w = target_size[1], target_size[0]
  30.         # 确定缩放的尺寸
  31.         scale_h, scale_w = float(h / target_h), float(w / target_w)
  32.         print(f'scale_h:{scale_h}, scale_w:{scale_w}')
  33.         scale = max(scale_h, scale_w) # 选择最大的缩放比率
  34.         new_w, new_h = int(w / scale), int(h / scale)
  35.         # 缩放后其中一条边和目标尺寸一致
  36.         resize_img = cv2.resize(img, (new_w, new_h))
  37.         # 图像上、下、左、右边界分别需要扩充的像素数目
  38.         top = int((target_h - new_h) / 2)
  39.         bottom = target_h - new_h - top
  40.         left = int((target_w - new_w) / 2)
  41.         right = target_w - new_w - left
  42.         print(f'top:{top} bottom:{bottom} left:{left} right:{right}') 
  43.         cv2.imwrite(os.path.join(path_new, f'new_{i}'), resize_img) # 写入本地文件
  44.         # 填充至 target_w * target_h
  45.         pad_img = cv2.copyMakeBorder(resize_img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=[0, 0, 0])
  46.         # cv2.imshow('img', pad_img)
  47.         # cv2.waitKey(1000)
  48.         filelists.append(os.path.join(path_new, f'new_{i}'))
  49.         imglist.append(pad_img)
  50.     return filelists, imglist
  51.  
  52.  
  53. def cut_img(scale):
  54.     path = './images'
  55.     path_new = './images_new'
  56.     if not os.path.exists(path_new):
  57.         os.makedirs(path_new)
  58.     filelists = []
  59.     imglist = []
  60.     for i in os.listdir(path):
  61.         file_path = os.path.join(path, i)
  62.         print(file_path)
  63.         img = cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), cv2.IMREAD_COLOR)
  64.         size = img.shape
  65.         h, w = size[0], size[1]
  66.         rate1 = scale.split(':')
  67.         w1 = int((w - w * int(rate1[0]) / int(rate1[1])) / 2)
  68.         w2 = int(w - (w - w * int(rate1[0]) / int(rate1[1])) / 2)
  69.         resize_img = img[0:h, w1:w2]
  70.         cv2.imwrite(os.path.join(path_new, f'new_{i}'), resize_img) # 写入本地文件
  71.         filelists.append(os.path.join(path_new, f'new_{i}'))
  72.         imglist.append(resize_img)
  73.     return filelists, imglist
  74.  
  75.  
  76. def cut_img1(images, scale):
  77.     imglist = []
  78.     filelists = []
  79.     for i in images:
  80.         img_url = i
  81.         file_name = img_url.split('/')[-1]
  82.         path_new = f'./images_new/{file_name}'
  83.         try:
  84.             res = requests.get(img_url)
  85.         except:
  86.             continue
  87.         if 'RIFF' in str(res.content)[:500] or 'GIF' in str(res.content)[:500]:
  88.             file_name = file_name.split('.')[0] + '.jpg'
  89.             path_new1 = f'./images_new/{file_name}'
  90.             img = Image.open(BytesIO(res.content)).convert('RGB')
  91.             img.save(path_new1)
  92.             img = cv2.imdecode(np.fromfile(path_new1, dtype=np.uint8), cv2.IMREAD_COLOR)
  93.         else:
  94.             image = np.asarray(bytearray(res.content), dtype="uint8")
  95.             img = cv2.imdecode(image, cv2.IMREAD_COLOR)
  96.         size = img.shape
  97.         h, w = size[0], size[1]
  98.         rate1 = scale.split(':')
  99.         w1 = int((w - w * int(rate1[0]) / int(rate1[1])) / 2)
  100.         w2 = int(w - (w - w * int(rate1[0]) / int(rate1[1])) / 2)
  101.         resize_img = img[0:h, w1:w2]
  102.         imglist.append(resize_img)
  103.         filelists.append(resize_img.shape)
  104.     return filelists, imglist
  105.  
  106. def image_to_video():
  107.     scale = '1:1'  # 裁剪比例,并保持高度不变
  108.     # scale = '3:4'
  109.     # scale = '9:16'
  110.     filelists, imglist = cut_img(scale) # 裁剪
  111.     # filelists, imglist = resize_img() # 缩放
  112.     fourcc = cv2.VideoWriter.fourcc(*'mp4v')
  113.     im = cv2.imread(filelists[0])
  114.     print(im.shape)
  115.     shape1 = (im.shape[1], im.shape[0])    #需要转为视频的图片的尺寸, 视频的分辨率
  116.     print('shape1:', shape1)
  117.     fps = 1
  118.     writer = cv2.VideoWriter('./output.mp4', fourcc, fps , shape1)
  119.     # for file_path in filelists:
  120.     #     img = cv2.imread(file_path)
  121.     #     writer.write(img)
  122.  
  123.     for i in imglist:
  124.         writer.write(i)
  125.     writer.release()
  126.  
  127.  
  128. image_to_video()
  129.  
  130.

 我们无法打开output3.mp4。这可能是因为文件类型不受支
持、文件扩展名不正确或文件已损坏，0xC00D36C4

如果生成的视频报这个错，一般是视频的分辨率 设置的不匹配

  1. import os
  2. import cv2
  3. import numpy as np
  4.  
  5. cv2.VideoWriter（）参数  cv2.VideoWriter() 是 OpenCV 中用于创建视频文件的类。它的参数如下：
  6. filename：保存视频的文件名。
  7. fourcc：指定视频编解码器的 FourCC 代码，用于将视频压缩成指定格式，例如：“XVID”、“MJPG”, "mp4v"等。可以使用 cv2.VideoWriter_fourcc() 函数来获取 FourCC 代码。
  8. fps：指定视频帧率，即每秒显示的帧数。
  9. frameSize：指定视频帧的大小，即视频的分辨率，可以使用 (width, height) 形式的元组来指定。
  10. isColor：指定是否为彩色视频。如果为 True，则为彩色视频；如果为 False，则为灰度视频。
  11. 其中，前三个参数是必需的，后两个参数是可选的。例如：
  12. fps = 25
  13. cv2.VideoWriter('output.avi', cv2.VideoWriter_fourcc(*'XVID'), fps, (640, 480))
  14.  
  15. def resize_img():
  16.     target_size = (1000, 1000)  # 所有图片缩放设置一致尺寸，目标尺寸
  17.     path = './images'
  18.     path_new = './images_new'
  19.     if not os.path.exists(path_new):
  20.         os.makedirs(path_new)
  21.     filelists = []
  22.     imglist = []
  23.     for i in os.listdir(path):
  24.         file_path = os.path.join(path, i)
  25.         print(file_path)
  26.         img = cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), cv2.IMREAD_COLOR)
  27.         size = img.shape
  28.         h, w = size[0], size[1]
  29.         target_h, target_w = target_size[1], target_size[0]
  30.         # 确定缩放的尺寸
  31.         scale_h, scale_w = float(h / target_h), float(w / target_w)
  32.         print(f'scale_h:{scale_h}, scale_w:{scale_w}')
  33.         scale = max(scale_h, scale_w) # 选择最大的缩放比率
  34.         new_w, new_h = int(w / scale), int(h / scale)
  35.         # 缩放后其中一条边和目标尺寸一致
  36.         resize_img = cv2.resize(img, (new_w, new_h))
  37.         # 图像上、下、左、右边界分别需要扩充的像素数目
  38.         top = int((target_h - new_h) / 2)
  39.         bottom = target_h - new_h - top
  40.         left = int((target_w - new_w) / 2)
  41.         right = target_w - new_w - left
  42.         print(f'top:{top} bottom:{bottom} left:{left} right:{right}') 
  43.         cv2.imwrite(os.path.join(path_new, f'new_{i}'), resize_img) # 写入本地文件
  44.         # 填充至 target_w * target_h
  45.         pad_img = cv2.copyMakeBorder(resize_img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=[0, 0, 0])
  46.         # cv2.imshow('img', pad_img)
  47.         # cv2.waitKey(1000)
  48.         filelists.append(os.path.join(path_new, f'new_{i}'))
  49.         imglist.append(pad_img)
  50.     return filelists, imglist
  51.  
  52.  
  53. def cut_img(scale):
  54.     path = './images'
  55.     path_new = './images_new'
  56.     if not os.path.exists(path_new):
  57.         os.makedirs(path_new)
  58.     filelists = []
  59.     imglist = []
  60.     for i in os.listdir(path):
  61.         file_path = os.path.join(path, i)
  62.         print(file_path)
  63.         img = cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), cv2.IMREAD_COLOR)
  64.         size = img.shape
  65.         h, w = size[0], size[1]
  66.         rate1 = scale.split(':')
  67.         w1 = int((w - w * int(rate1[0]) / int(rate1[1])) / 2)
  68.         w2 = int(w - (w - w * int(rate1[0]) / int(rate1[1])) / 2)
  69.         resize_img = img[0:h, w1:w2]
  70.         cv2.imwrite(os.path.join(path_new, f'new_{i}'), resize_img) # 写入本地文件
  71.         filelists.append(os.path.join(path_new, f'new_{i}'))
  72.         imglist.append(resize_img)
  73.     return filelists, imglist
  74.  
  75.  
  76. def cut_img1(images, scale):
  77.     imglist = []
  78.     filelists = []
  79.     for i in images:
  80.         img_url = i
  81.         file_name = img_url.split('/')[-1]
  82.         path_new = f'./images_new/{file_name}'
  83.         try:
  84.             res = requests.get(img_url)
  85.         except:
  86.             continue
  87.         if 'RIFF' in str(res.content)[:500] or 'GIF' in str(res.content)[:500]:
  88.             file_name = file_name.split('.')[0] + '.jpg'
  89.             path_new1 = f'./images_new/{file_name}'
  90.             img = Image.open(BytesIO(res.content)).convert('RGB')
  91.             img.save(path_new1)
  92.             img = cv2.imdecode(np.fromfile(path_new1, dtype=np.uint8), cv2.IMREAD_COLOR)
  93.         else:
  94.             image = np.asarray(bytearray(res.content), dtype="uint8")
  95.             img = cv2.imdecode(image, cv2.IMREAD_COLOR)
  96.         size = img.shape
  97.         h, w = size[0], size[1]
  98.         rate1 = scale.split(':')
  99.         w1 = int((w - w * int(rate1[0]) / int(rate1[1])) / 2)
  100.         w2 = int(w - (w - w * int(rate1[0]) / int(rate1[1])) / 2)
  101.         resize_img = img[0:h, w1:w2]
  102.         imglist.append(resize_img)
  103.         filelists.append(resize_img.shape)
  104.     return filelists, imglist
  105.  
  106. def image_to_video():
  107.     scale = '1:1'  # 裁剪比例,并保持高度不变
  108.     # scale = '3:4'
  109.     # scale = '9:16'
  110.     filelists, imglist = cut_img(scale) # 裁剪
  111.     # filelists, imglist = resize_img() # 缩放
  112.     fourcc = cv2.VideoWriter.fourcc(*'mp4v')
  113.     im = cv2.imread(filelists[0])
  114.     print(im.shape)
  115.     shape1 = (im.shape[1], im.shape[0])    #需要转为视频的图片的尺寸, 视频的分辨率
  116.     print('shape1:', shape1)
  117.     fps = 1
  118.     writer = cv2.VideoWriter('./output.mp4', fourcc, fps , shape1)
  119.     # for file_path in filelists:
  120.     #     img = cv2.imread(file_path)
  121.     #     writer.write(img)
  122.  
  123.     for i in imglist:
  124.         writer.write(i)
  125.     writer.release()
  126.  
  127.  
  128. image_to_video()
  129.  
  130.

 我们无法打开output3.mp4。这可能是因为文件类型不受支
持、文件扩展名不正确或文件已损坏，0xC00D36C4

如果生成的视频报这个错，一般是视频的分辨率 设置的不匹配

注：本文转载自blog.csdn.net的FOAF-lambda的文章"https://blog.csdn.net/lwdfzr/article/details/135158033"。版权归原作者所有，此博客不拥有其著作权，亦不承担相应法律责任。如有侵权，请联系我们删除。
复制链接
相关推荐
发表评论

评论记录：

未查询到任何数据！