from modelscope import Qwen2_5_VLForConditionalGeneration, AutoProcessor from qwen_vl_utils import process_vision_info import os currentDir=os.path.dirname(__file__) def original_list_to_json_str(text): json_str = text[0].strip() json_str = json_str[json_str.find('{'):json_str.rfind('}') + 1] return json_str class QwenVlm(): def __init__(self,model_id = None): if model_id is None: self.model_id="/models/qwen/Qwen2.5-VL-3B-Instruct/" else:


以下是调用 `QwenVlm` 类进行图像理解的示例代码: ```python # 实例化 QwenVLM 模型 vlm = QwenVlm() # 指定图片路径 image_path = "path/to/your/image.jpg" # 替换为实际图片路径 # 默认问题(描述图片) result = vlm.imageComprehension(image_path) print("默认问题结果:", result) # 自定义问题 custom_question = "图片中有多少人?" result = vlm.imageComprehension(image_path, custom_question) print("自定义问题结果:", result) ``` 使用说明: 1. 确保已安装 `modelscope` 和相关依赖 2. 图片路径可以是绝对路径或相对路径 3. 可以自定义问题来获取特定信息 4. 首次运行会自动下载模型(如果未缓存) 注意事项: - 需要 GPU 环境运行 - 大模型加载需要一定时间 - 图片尺寸不宜过大 - 问题应尽量明确具体 输出示例: ``` 默认问题结果: ['图片展示了一个阳光明媚的公园场景,有多人在草地上休闲活动。'] 自定义问题结果: ['图片有5个人,包括2名成年人和3名儿童。'] ``` [2025-05-22 13:50:33 | AI问答 | 265点数解答]
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