Create app.py

app.py

@@ -0,0 +1,43 @@
+from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
+import gradio as gr
+
+# 加载模型和处理器
+model = Qwen2_5_VLForConditionalGeneration.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct", device_map="auto")
+processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct")
+
+# 定义识别和分析函数
+def recognize_and_analyze(image, text_prompt):
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "image", "image": image},
+                {"type": "text", "text": text_prompt},
+            ],
+        }
+    ]
+
+    # 处理视觉信息
+    inputs = processor(images=image, return_tensors="pt")
+    inputs = inputs.to(model.device)
+
+    # 生成输出
+    generated_ids = model.generate(**inputs)
+    output_text = processor.batch_decode(generated_ids, skip_special_tokens=True)
+    return output_text[0]
+
+# 设置Gradio界面
+interface = gr.Interface(
+    fn=recognize_and_analyze,
+    inputs=[
+        gr.inputs.Image(type="filepath", label="上传图像"),
+        gr.inputs.Textbox(label="输入描述文本"),
+    ],
+    outputs=gr.outputs.Textbox(label="识别结果"),
+    title="Qwen2.5-VL 物体识别与分析",
+    description="上传图像并输入描述文本以获取识别和分析结果。",
+)
+
+# 启动Gradio应用
+if __name__ == "__main__":
+    interface.launch()