使用多图输入,模型并不能区分每一张图片,而是把它当作了一张拼接的图片?

#17
by jamestang0219 - opened

似乎从代码上看,处理vit到llm的embedding是这样的。那是否说明模型其实并不能理解哪些token属于一张图片?

OpenGVLab org
edited Jul 7

刚刚更新了代码,现在多图对话有两种做法,一种是每张图的token分别有各自的<img></img> token,另一种是把多图拼起来作为单图处理:

# multi-image multi-round conversation, combined images (多图多轮对话,拼接图像)
pixel_values1 = load_image('./examples/image1.jpg', max_num=6).to(torch.bfloat16).cuda()
pixel_values2 = load_image('./examples/image2.jpg', max_num=6).to(torch.bfloat16).cuda()
pixel_values = torch.cat((pixel_values1, pixel_values2), dim=0)

question = '<image>\nDescribe the two images in detail.'
response, history = model.chat(tokenizer, pixel_values, question, generation_config,
                               history=None, return_history=True)

question = 'What are the similarities and differences between these two images.'
response, history = model.chat(tokenizer, pixel_values, question, generation_config,
                               history=history, return_history=True)
print(f'User: {question}')
print(f'Assistant: {response}')

# multi-image multi-round conversation, separate images (多图多轮对话,独立图像)
pixel_values1 = load_image('./examples/image1.jpg', max_num=6).to(torch.bfloat16).cuda()
pixel_values2 = load_image('./examples/image2.jpg', max_num=6).to(torch.bfloat16).cuda()
pixel_values = torch.cat((pixel_values1, pixel_values2), dim=0)
num_patches_list = [pixel_values1.size(0), pixel_values2.size(0)]

question = 'Image-1: <image>\nImage-2: <image>\nDescribe the two images in detail.'
response, history = model.chat(tokenizer, pixel_values, question, generation_config,
                               num_patches_list=num_patches_list,
                               history=None, return_history=True)
print(f'User: {question}')
print(f'Assistant: {response}')
czczup changed discussion status to closed

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