Ai_tottle/ai_tottle_api.py

@@ -12,6 +12,7 @@ from queue import Queue
 import gdal2tiles as gdal2tiles
 from map_find import map_process_images
 from yolo_train import auto_train
+from map_cut import process_tiling
 from cv_video_counter import start_video_session,switch_model_session,stop_video_session,stream_sessions
 import torch
 from yolo_photo import map_process_images_with_progress # 引入你的处理函数

Ai_tottle/map_cut.py

@@ -0,0 +1,172 @@
+import os
+import tempfile
+import uuid
+import aiohttp
+import yaml
+from minio import Minio
+from minio.error import S3Error
+import subprocess
+import sys
+import json
+from osgeo import gdal, osr
+from miniohelp import load_config,upload_file
+
+# 异步下载文件函数
+async def download_file(url: str, output_path: str) -> bool:
+    try:
+        async with aiohttp.ClientSession() as session:
+            async with session.get(url) as response:
+                if response.status == 200:
+                    with open(output_path, 'wb') as f:
+                        f.write(await response.read())
+                    return True
+                else:
+                    print(f"下载失败: {url}")
+                    return False
+    except Exception as e:
+        print(f"下载错误: {e}")
+        return False
+
+# 上传文件到 MinIO
+def upload_to_minio(local_file: str, bucket: str, object_name: str,minio_client: Minio):
+    try:
+        minio_client.fput_object(bucket, object_name, local_file)
+    except S3Error as e:
+        print(f"上传失败: {local_file} -> {object_name} 错误: {e}")
+
+def generate_tiles_from_tif_cli(
+    input_tif: str,
+    output_dir: str,
+    zoom_levels: str = "0-18",
+    processes: int = 4,
+    verbose: bool = True
+):
+    # Step 1: 调用 gdal2tiles
+    args = [
+        sys.executable,
+        "-m", "osgeo_utils.gdal2tiles",
+        "-z", zoom_levels,
+        "--processes", str(processes)
+    ]
+    if verbose:
+        args.append("-v")
+    args += [input_tif, output_dir]
+    print(f"Running: {' '.join(args)}")
+    subprocess.run(args, check=True)
+
+    # Step 2: 提取地理信息
+    ds = gdal.Open(input_tif)
+    gt = ds.GetGeoTransform()
+    width = ds.RasterXSize
+    height = ds.RasterYSize
+
+    minx = gt[0]
+    maxy = gt[3]
+    pixel_width = gt[1]
+    pixel_height = gt[5]
+    maxx = minx + width * pixel_width
+    miny = maxy + height * pixel_height
+
+    # 尝试解析坐标系 EPSG 编码
+    srs = osr.SpatialReference(wkt=ds.GetProjection())
+    try:
+        proj_epsg = int(srs.GetAttrValue("AUTHORITY", 1))
+    except:
+        proj_epsg = 4326  # fallback 默认值
+
+    # Step 3: 构造 JSON 数据
+    bounds = {
+        "west": minx,
+        "south": miny,
+        "east": maxx,
+        "north": maxy
+    }
+
+    json_data = {
+        "bounds": bounds,
+        "contentType": "image/png",
+        "generatetool": "custom_script@yourdomain.com/gdal2tiles",
+        "latLonBounds": bounds,  # 和 bounds 相同
+        "maxzoom": int(zoom_levels.split("-")[-1]),
+        "minzoom": int(zoom_levels.split("-")[0]),
+        "proj": proj_epsg,
+        "tilesize": 256,
+        "tiletrans": "google",
+        "type": "image",
+        "ziped": False
+    }
+
+    # Step 4: 保存为 JSON 文件
+    json_path = output_dir.rstrip("\\/") + ".json"
+    with open(json_path, 'w', encoding='utf-8') as f:
+        json.dump(json_data, f, indent=2)
+
+    print(f"瓦片生成成功，元数据已保存到: {json_path}")
+
+# 主处理函数
+async def process_tiling(tif_url: str = None, prj_url: str = None, zoom_levels: str = "1-18", bucket: str = "300",config: str = "222.212.85.86") -> dict:
+    # 创建唯一任务ID
+    task_id = str(uuid.uuid4())
+    temp_dir = tempfile.mkdtemp()
+    tif_path = os.path.join(temp_dir, f"{task_id}.tif")
+    prj_path = os.path.join(temp_dir, f"{task_id}.prj") if prj_url else None
+    output_dir = os.path.join(temp_dir, f"tiles_{task_id}")
+    os.makedirs(output_dir, exist_ok=True)
+
+    # 下载 TIF
+    if tif_url:
+        tif_ok = await download_file(tif_url, tif_path)
+        if not tif_ok:
+            raise Exception("TIF 下载失败")
+
+    # 下载 PRJ（如果有）
+    if prj_url:
+        prj_ok = await download_file(prj_url, prj_path)
+        if prj_ok:
+            # GDAL 要求 PRJ 文件与 TIF 同名（不同后缀）
+            fixed_prj_path = tif_path.replace('.tif', '.prj')
+            os.rename(prj_path, fixed_prj_path)
+        else:
+            print("PRJ 下载失败，继续处理...")
+
+    # 切片
+    generate_tiles_from_tif_cli(tif_path, output_dir, zoom_levels=zoom_levels, processes=4, verbose=True)
+    
+    # 上传结果到 MinIO
+    minio_base_path = f"maps/{task_id}/"
+    for root, _, files in os.walk(output_dir):
+        for file in files:
+            local_path = os.path.join(root, file)
+            rel_path = os.path.relpath(local_path, output_dir)
+            object_name = os.path.join(minio_base_path, rel_path).replace("\\", "/")
+            upload_to_minio(local_path, bucket, object_name)
+
+    minio_info = load_config(config)
+    # 清洗 endpoint，去掉 http:// 或 https:// 前缀
+    endpoint = minio_info["MinIOEndpoint"].replace("http://", "").replace("https://", "")
+    
+    # 返回构建的瓦片URL信息
+    base_url = f"http://{endpoint}//{bucket}/{minio_base_path}"
+    min_zoom, max_zoom = zoom_levels.split("-")
+
+    return {
+        "tile_url": {
+            "base_url": base_url,
+            "format": "{z}/{x}/{y}.png",
+            "preview_url": f"{base_url}openlayers.html",
+            "min_zoom": min_zoom,
+            "max_zoom": max_zoom,
+            "tilejson_url": f"{base_url}tilemapresource.xml"
+        }
+    }
+
+# 示例调用
+if __name__ == "__main__":
+    # tif_url = "https://your-server.com/sample.tif"
+    # prj_url = "https://your-server.com/sample.prj"  # 可选
+    # result = asyncio.run(process_tiling(tif_url, prj_url, zoom_levels="5-15"))
+    # print(result)
+    
+    input_tif = r"e:/new.tif"
+    output_dir = r"D:/work/AI_Python/cut"
+    generate_tiles_from_tif_cli(input_tif, output_dir, zoom_levels="5-15", processes=4, verbose=True)

Ai_tottle/sent_data.py

@@ -1,6 +1,9 @@
+from minio import Minio
+from pyproj import Transformer
 import psycopg2
 import json
 import numpy as np
+import numpy as np
 import cv2
 from pyproj import Transformer
 import math