99 lines
3.3 KiB
Python
99 lines
3.3 KiB
Python
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# 当前为语义分割的脚本，从现场minio读取图片，进而做语义分割，最终将结果存储到本地minio
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import datetime
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import json
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import os
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from cropland_module.change_detection_module import ChangeDetectionModule
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from middleware.minio_util import downFile, upload_file, upload_file_from_buffer
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from io import BytesIO
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from mqtt_pub import MQTTClient
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mqtt_client=None
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# MQTT 代理地址和端口
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# broker = "112.44.103.230" # 公共 MQTT 代理（免费）
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broker = "8.137.54.85" # 公共 MQTT 代理（免费）
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port = 1883 # MQTT 默认端口
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# 主题
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topic = "thing/product/ai/events"
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def detection_func(task_id, s3_id, early_pic_url, later_pic_url, func_id):
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print("\n=== 变化检测系统 ===")
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# args = parse_args()
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gpu_id = "0"
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img_size = 256
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lr = 0.0001
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model_path = r'cropland_module/netCD_epoch_34.pth'
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# # image1_path = r'D:\project\dlfg\LEVIR-CD\test\A1\00201.png'
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# # image1_path = r'C:\Users\14867\Desktop\0613-building\Axz\xz\270\00201.jpg'
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#
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# # # 平移 5%-10%
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# # image1_path = r'C:\Users\14867\Desktop\0613-building\Axz\pingyi\00201.png'
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# # image2_path = r'D:\project\dlfg\LEVIR-CD\test\B1\00201.png'
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# image1_path = r'C:\Users\14867\Desktop\0613-building\Axz\pingyi\00205.png'
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# image2_path = r'C:\Users\14867\Desktop\0613-building\B\00205.png'
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# # image1_path=r'C:\Users\14867\Desktop\0613-building\B\00201.png'
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# # image2_path=r'C:\Users\14867\Desktop\0613-building\A\00201.png'
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cd = ChangeDetectionModule(gpu_id, img_size, lr)
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cd.load_model(model_path)
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early_pic = downFile(early_pic_url)
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later_pic = downFile(later_pic_url)
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from PIL import Image
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# image1 = Image.open(image1_path).convert('RGB')
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# image2 = Image.open(image2_path).convert('RGB')
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image1 = Image.open(early_pic).convert('RGB')
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image2 = Image.open(later_pic).convert('RGB')
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output, binary_result = cd.predict_without_label(image1, image2)
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pic_name = os.path.basename(later_pic)
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# # # 保存结果（可选）
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# result = Image.fromarray(binary_result)
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# result.save("output.png")
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#
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result = Image.fromarray(binary_result)
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# 将图像保存到 BytesIO 对象中
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buffer = BytesIO()
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result.save(buffer, format="PNG") # 保存为 PNG 格式
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buffer.seek(0) #
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# 现在 image_data 是图片的二进制数据
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# 你可以将其写入文件、发送到网络等
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# with open("output.png", "wb") as f:
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# f.write(image_data)
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date_str = datetime.datetime.now().strftime("%Y%m%d")
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time_s = datetime.datetime.now().timestamp()
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mqtt_client = MQTTClient(broker, port, topic)
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pic_name_1=f"{date_str}/{time_s}-1-{pic_name}"
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pic_name_2=f"{date_str}/{time_s}-2-{pic_name}"
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pic_name=f"{date_str}/{time_s}-result-{pic_name}"
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minio_path_1, file_type_1 = upload_file(early_pic, None)
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minio_path_2, file_type_2 = upload_file(later_pic, None)
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minio_path_result, file_type_result = upload_file_from_buffer(buffer,pic_name)
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message = {
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"flight_task_id": task_id,
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"minio": {
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"minio_path_1": minio_path_1,
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"minio_path_2": minio_path_2,
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"minio_path_result": minio_path_result,
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"file_type": file_type_result
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}
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}
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json_message = json.dumps(message, indent=4, ensure_ascii=False)
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mqtt_client.publish_message(json_message)
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