1import os 2os.system("pip install --pre --upgrade paddlenlp -f https://www.paddlepaddle.org.cn/whl/paddlenlp.html") # 安装nlp分支最新包3os.system("pip install paddlepaddle-gpu==0.0.0.post112 -f https://www.paddlepaddle.org.cn/whl/linux/gpu/develop.html")4os.system("pip install tqdm")5!pip install ipywidgets

 1%%capture 2os.environ["CUDA_VISIBLE_DEVICES"] = "0" 3os.environ["FLAGS_use_cuda_managed_memory"] = "true" 4import requests 5from PIL import Image 6import gradio as gr 7from tqdm import tqdm 8import ipywidgets as widgets 9from IPython.display import display10import csv    11from itertools import islice 12from paddlenlp.transformers import MiniGPT4ForConditionalGeneration, MiniGPT4Processor

1!mkdir minigpt4

 1%%capture 2os.system("wget -O  minigpt4/model_config.json https://bj.bcebos.com/v1/ai-studio-online/924ed883c17b4b8b88b4a1f98e24d34b3b00160ac9bd4b3ba478aff6974e0e9d?responseContentDisposition=attachment%3B%20filename%3Dmodel_config.json ") 3!wget -O  ./minigpt4/model_state.pdparams    https://bj.bcebos.com/v1/ai-studio-online/18bd53eaa2854263ba31fb4d75f31a5f0d38421a6da64525bff6da230389fc36?responseContentDisposition=attachment%3B%20filename%3Dmodel_state.pdparams 4!wget -O  ./minigpt4/generation_config.json  https://bj.bcebos.com/v1/ai-studio-online/f0b2129d6a934a97abcaa139ac1f28e33a6940004c7a4c859737f282640cf332?responseContentDisposition=attachment%3B%20filename%3Dgeneration_config.json 5!wget -O  ./minigpt4/preprocessor_config.json https://bj.bcebos.com/v1/ai-studio-online/748c332837d34f389d762f487470b1a7221edd36ccb5484b913bd2d3855ee9f6?responseContentDisposition=attachment%3B%20filename%3Dpreprocessor_config.json 6!wget -O  ./minigpt4/sentencepiece.bpe.model https://bj.bcebos.com/v1/ai-studio-online/0139a1bfcdf84058b77cea4631837340ea94f5fcc37445929a3414f05d07579b?responseContentDisposition=attachment%3B%20filename%3Dsentencepiece.bpe.model 7!wget  -O  ./minigpt4/special_tokens_map.json https://bj.bcebos.com/v1/ai-studio-online/90b16a96d4f94200ab417b39dcf3bce4ddef5885625c4d0c8e70b3f659cb6993?responseContentDisposition=attachment%3B%20filename%3Dspecial_tokens_map.json 8!wget -O  ./minigpt4/tokenizer.json  https://bj.bcebos.com/v1/ai-studio-online/e877a685eb86499cb87e1c4cbf85353856506d12e9a841a292e780aa4a9e188a?responseContentDisposition=attachment%3B%20filename%3Dtokenizer.json 9!wget  -O  ./minigpt4/tokenizer_config.json  https://bj.bcebos.com/v1/ai-studio-online/f93064db167c4075b1f86d6878cac9303fb8df418f7a42a7900785a6e188cc44?responseContentDisposition=attachment%3B%20filename%3Dtokenizer_config.json10--2023-07-27 10:54:29--  https://bj.bcebos.com/v1/ai-studio-online/924ed883c17b4b8b88b4a1f98e24d34b3b00160ac9bd4b3ba478aff6974e0e9d?responseContentDisposition=attachment%3B%20filename%3Dmodel_config.json11Resolving bj.bcebos.com (bj.bcebos.com)... 182.61.200.195, 182.61.200.229, 2409:8c04:1001:1002:0:ff:b001:368a12Connecting to bj.bcebos.com (bj.bcebos.com)|182.61.200.195|:443... connected.13HTTP request sent, awaiting response... 200 OK14Length: 5628 (5.5K) [application/octet-stream]15Saving to: 'minigpt4/model_config.json'

1model_path ='./minigpt4'2model = MiniGPT4ForConditionalGeneration.from_pretrained(model_path)3model.eval()4processor = MiniGPT4Processor.from_pretrained(model_path)

 1def predict_per_url_prompt(url=None,text=None): 2    if url==None: 3        url = "https://paddlenlp.bj.bcebos.com/data/images/mugs.png" 4    image = Image.open(requests.get(url, stream=True).raw) 5    if text== None: 6        text = "describe this image" 7 8    prompt = "Give the following image: <Img>ImageContent</Img>. You will be able to see the image once I provide it to you. Please answer my questions.###Human: <Img><ImageHere></Img> <TextHere>###Assistant:" 910    inputs = processor([image], text, prompt)1112    generate_kwargs = {13        "max_length": 300,14        "num_beams": 1,15        "top_p": 1.0,16        "repetition_penalty": 1.0,17        "length_penalty": 0,18        "temperature": 1,19        "decode_strategy": "greedy_search",20        "eos_token_id": [[835], [2277, 29937]],21    }22    outputs = model.generate(**inputs, **generate_kwargs)23    msg = processor.batch_decode(outputs[0])24    return msg[0][0:-5]

 1def predict_dir_and_one_prompt_out_list(dir_path=None,text=None): 2    import os  3    assert os.path.isdir(dir_path),print('请输入文件夹路径,而不是图像路径') 4    output = [] 5    for per_image_name in tqdm (os.listdir(dir_path)): 6        image = Image.open(os.path.join(dir_path,per_image_name)) 7        if text== None: 8            text = "describe this image" 9        else:10            text = text1112        prompt = "Give the following image: <Img>ImageContent</Img>. You will be able to see the image once I provide it to you. Please answer my questions.###Human: <Img><ImageHere></Img> <TextHere>###Assistant:"1314        inputs = processor([image], text, prompt)1516        generate_kwargs = {17            "max_length": 300,18            "num_beams": 1,19            "top_p": 1.0,20            "repetition_penalty": 1.0,21            "length_penalty": 0,22            "temperature": 1,23            "decode_strategy": "greedy_search",24            "eos_token_id": [[835], [2277, 29937]],25        }26        outputs = model.generate(**inputs, **generate_kwargs)27        msg = processor.batch_decode(outputs[0])28        output.append(msg[0][0:-5])29    return output

1predict_per_url_prompt(url='https://ai-studio-static-online.cdn.bcebos.com/d283b05404bd44b69b9be868fddb67616296858284bf4ad587e29432de66e930',text="描述这张图片,使用中文")2'这张图片显示了一个女性角色，穿着红色和白色的服装，手持一根金色的剑。她的头发是白色的，眼睛是红色的。她站在一张草地上，手持剑的柄子。这个角色看起来像是一个英雄，她的服装和装备显示出她的力量和勇气'