src/Captioner.py

from PIL import Image
import base64
from io import BytesIO
import os
from openai import OpenAI
import json

class Captioner:
    def __init__(self, api_key_path = None, proxy=None, api_base="https://api.lingyiwanwu.com/v1"):
        
        if api_key_path is None:
            # try find datas/01_key.txt and ../datas/01_key.txt
            cand_paths = ['datas/01_key.txt', '../datas/01_key.txt']
            flag = False
            for path in cand_paths:
                if os.path.exists(path):
                    api_key_path = path
                    flag = True
                    break

            if not flag:
                raise ValueError("Please provide the path to the API key file.")


        self.api_key = self.load_access_token(api_key_path)
        self.api_base = api_base
        if proxy:
            os.environ['HTTP_PROXY'] = proxy
            os.environ['HTTPS_PROXY'] = proxy
        self.client = OpenAI(
            api_key=self.api_key,
            base_url=self.api_base
        )

        self.history = {}
        self.history_file = None

        self.load_history()

    def load_access_token(self, file_path):
        with open(file_path, 'r') as file:
            return file.read().strip()

    def image2base64(self, image_path):
        # 打开图像
        with Image.open(image_path) as img:
            # 检查图像高度是否超过480
            if img.height > 480:
                # 计算调整后的宽度，以保持宽高比不变
                aspect_ratio = img.width / img.height
                new_height = 480
                new_width = int(new_height * aspect_ratio)
                img = img.resize((new_width, new_height), Image.ANTIALIAS)
            
            # 使用BytesIO在内存中保存调整大小后的图像
            buffered = BytesIO()
            img.save(buffered, format="JPEG")
            buffered.seek(0)

            # 将图像转换为Base64编码字符串
            img_base64 = "data:image/jpeg;base64," + base64.b64encode(buffered.read()).decode('utf-8')
        
        return img_base64
    
    def load_history(self, jsonl_file_name=None):
        if jsonl_file_name is None:
            jsonl_file_name = "datas/caption_history.jsonl"
        
        self.history_file = jsonl_file_name
        
        if os.path.exists(jsonl_file_name):
            with open(jsonl_file_name, 'r', encoding='utf-8') as f:
                for line in f:
                    data = json.loads(line)
                    self.history[data['file_name']] = data['response']

    def search_from_history(self, file_name):
        return self.history.get(file_name, None)
    
    def save_history(self, jsonl_file_name=None):
        if jsonl_file_name is None:
            jsonl_file_name = self.history_file
        
        if jsonl_file_name:
            with open(jsonl_file_name, 'w', encoding='utf-8') as f:
                for file_name, response in self.history.items():
                    json.dump({'file_name': file_name, 'response': response}, f, ensure_ascii=False)
                    f.write('\n')

        # print(f"History saved to {jsonl_file_name}")

    def add_to_history(self, file_name, response):
        self.history[file_name] = response

    def caption(self, image_name):

        # Check if the caption is already in the history
        cached_response = self.search_from_history(image_name)
        if cached_response:
            # print("return the cache")
            return cached_response
        
        prompt = """Analyze the image and output in JSON format, including the following fields:
            - "detailed_description": A detailed description of the image content.
            - "major_object": Determine the main object/scene in the image based on the description, output with a simple word
            - "Chinese_name": 判断图片中主要物体的中文名
            - "real_or_composite":  Determine whether this image was taken with a camera or created/modifed by a computer, output with real or composite."""
        
        img_base64 = self.image2base64(image_name)
        
        completion = self.client.chat.completions.create(
            model="yi-vision",
            messages=[
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "text",
                            "text": prompt
                        },
                        {
                            "type": "image_url",
                            "image_url": {
                                "url": img_base64
                            }
                        }
                    ]
                }
            ],
            stream=False
        )

        response = completion.choices[0].message.content

        # Add the new response to history
        self.add_to_history(image_name, response)
        # Save history after adding the new entry
        self.save_history()

        return response

if __name__ == "__main__":
    import os
    os.environ['HTTP_PROXY'] = 'http://localhost:8234'
    os.environ['HTTPS_PROXY'] = 'http://localhost:8234'
    captioner = Captioner()
    test_image = "temp_images/3zjz9b3l.jpg"
    print(captioner.caption(test_image))