def image_generator(df, batch_size, img_size): num_samples = len(df) while True: for offset in range(0, num_samples, batch_size): batch_df = df[offset:offset+batch_size] images = [] for path in batch_df['path']: img = Image.open(path).resize(img_size) images.append(np.asarray(img)) X = np.array(images) yield X batch_size = 32 img_size = (600, 450) gen = image_generator(df, batch_size, img_size) # 读取生成器中的每个批次，并将所有图像数据存储在 df['image'] 列中 for i, batch_images in enumerate(gen): start_index = i * batch_size end_index = start_index + batch_images.shape[0] df.loc[start_index:end_index, 'image'] = batch_images代码为何出现ValueError: Must have equal len keys and value when setting with an iterable报错

这个错误是因为在将生成器中的每个批次数据存储到df['image']列时，使用了不同长度的迭代器或列表。这可能是由于生成器的最后一个批次数据的长度不足batch_size导致的。

为了解决这个问题，您可以在存储每个批次数据之前，先检查批次数据的长度，并将其与batch_size进行比较。如果批次数据的长度不足batch_size，则只将前面的数据存储到df['image']列中。修改后的代码如下：

def image_generator(df, batch_size, img_size):
    num_samples = len(df)
    while True:
        for offset in range(0, num_samples, batch_size):
            batch_df = df[offset:offset+batch_size]
            images = []
            for path in batch_df['path']:
                img = Image.open(path).resize(img_size)
                images.append(np.asarray(img))
            X = np.array(images)
            yield X
            
batch_size = 32
img_size = (600, 450)
gen = image_generator(df, batch_size, img_size)

# 读取生成器中的每个批次，并将所有图像数据存储在 df['image'] 列中
for i, batch_images in enumerate(gen):
    start_index = i * batch_size
    end_index = start_index + batch_images.shape[0]
    if batch_images.shape[0] != batch_size:
        df.loc[start_index:start_index+batch_images.shape[0]-1, 'image'] = batch_images
    else:
        df.loc[start_index:end_index, 'image'] = batch_images

这样，就可以避免ValueError错误，确保所有的图像数据都能够正确地存储到df['image']列中。