Python实现多张图片合成文字效果：从批量下载到马赛克拼图

def dowmloadPicture(html, keyword):
    global num
    # t =0
    pic_url = re.findall('"objURL":"(.*?)",', html, re.S)  # 先利用正则表达式找到图片url
    print('找到关键词:' + keyword + '的图片，即将开始下载图片...')
    for each in pic_url:
        print('正在下载第' + str(num + 1) + '张图片，图片地址:' + str(each))
        try:
            if each is not None:
                pic = requests.get(each, timeout=7)
            else:
                continue
        except BaseException:
            print('错误，当前图片无法下载')
            continue
        else:
            string = file + r'\\' + keyword + '_' + str(num) + '.jpg'
            fp = open(string, 'wb')
            fp.write(pic.content)
            fp.close()
            num += 1
        if num >= numPicture:
            return

def Find(url, A):
    global List
    print('正在检测图片总数，请稍等.....')
    t = 0
    i = 1
    s = 0
    while t < 1000:
        Url = url + str(t)
        try:
            # 这里搞了下
            Result = A.get(Url, timeout=7, allow_redirects=False)
        except BaseException:
            t = t + 60
            continue
        else:
            result = Result.text
            pic_url = re.findall('"objURL":"(.*?)",', result, re.S)  # 先利用正则表达式找到图片url
            s += len(pic_url)
            if len(pic_url) == 0:
                break
            else:
                List.append(pic_url)
                t = t + 60
    return s

def dowmloadPicture(html, keyword):
    global num
    # t =0
    pic_url = re.findall('"objURL":"(.*?)",', html, re.S)  # 先利用正则表达式找到图片url
    print('找到关键词:' + keyword + '的图片，即将开始下载图片...')
    for each in pic_url:
        print('正在下载第' + str(num + 1) + '张图片，图片地址:' + str(each))
        try:
            if each is not None:
                pic = requests.get(each, timeout=7)
            else:
                continue
        except BaseException:
            print('错误，当前图片无法下载')
            continue
        else:
            string = file + r'\\' + keyword + '_' + str(num) + '.jpg'
            fp = open(string, 'wb')
            fp.write(pic.content)
            fp.close()
            num += 1
        if num >= numPicture:
            return

import photomosaic as pm
 
# 加载要拼成的图片image（jpg 格式，图片越大，得到的拼图的每个小图分辨率越高）
image = pm.imread("1.jpg", as_gray=False)
# 从指定文件夹加载图片库（需要比较多的图片才能获得较好的效果）
pool = pm.make_pool("wxl/*.jpg")
# 制作 50*50 的拼图马赛克
mosaic = pm.basic_mosaic(image, pool, (200, 200))
# 保存拼图
pm.imsave("mosaic.jpg", mosaic)

def crop_to_fit(image, shape):
    """
    Return a copy of image resized and cropped to precisely fill a shape.
    To resize a colored 2D image, pass in a shape with two entries. When
    ``len(shape) < image.ndim``, higher dimensions are ignored.
    Parameters
    ----------
    image : array
    shape : tuple
        e.g., ``(height, width)`` but any length <= ``image.ndim`` is allowed
    Returns
    -------
    cropped_image : array
    """
    # Resize smallest dimension (width or height) to fit.
    d = np.argmin(np.array(image.shape)[:2] / np.array(shape))
    enlarged_shape = (tuple(np.ceil(np.array(image.shape[:len(shape)]) *
                                    shape[d]/image.shape[d])) +
                      image.shape[len(shape):])
    resized = resize(image, enlarged_shape,
                     mode='constant', anti_aliasing=False)
    # Now the image is as large or larger than the shape along all dimensions.
    # Crop any overhang in the other dimension.
    crop_width = []
    for actual, target in zip(resized.shape, shape):
        overflow = actual - target
        # Center the image and crop, biasing left if overflow is odd.
        left_margin = int(np.floor(overflow / 2))
        right_margin = int(np.ceil(overflow / 2))
        crop_width.append((left_margin, right_margin))
    # Do not crop any additional dimensions beyond those given in shape.
    for _ in range(resized.ndim - len(shape)):
        crop_width.append((0, 0))
    cropped = crop(resized, crop_width)
    return cropped

def readSourceImages(sourcepath,blocksize):
    print('开始读取图像')
    # 合法图像列表
    sourceimages = []
    # 平均颜色列表
    avgcolors = []
    for path in tqdm(glob.glob("{}/*.jpg".format(sourcepath))):
        image = cv2.imread(path, cv2.IMREAD_COLOR)
        if image.shape[-1] != 3:
            continue
        image = cv2.resize(image, (blocksize, blocksize))
        avgcolor = np.sum(np.sum(image, axis=0), axis=0) / (blocksize * blocksize)
        sourceimages.append(image)
        avgcolors.append(avgcolor)
    print('结束读取')
    return sourceimages,np.array(avgcolors)