yooooger
This commit is contained in:
parent
aa702653d7
commit
42f6f1fa02
@ -1,20 +1,19 @@
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from sanic import Sanic, json, Blueprint,response
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from sanic.exceptions import Unauthorized, NotFound
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from sanic.exceptions import Unauthorized
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from sanic.response import json as json_response
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from sanic_cors import CORS
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from datetime import datetime
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import numpy as np
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import logging
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import uuid
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import os
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import os,traceback
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import asyncio
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from ai_image import process_images # 你实现的图片处理函数
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from queue import Queue
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from map_find import map_process_images
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from yolo_train import auto_train
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from cv_video_counter import start_video_session,switch_model_session,stop_video_session,stream_sessions
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import torch
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from yolo_photo import map_process_images_with_progress # 引入你的处理函数
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from tiles import TilesetProcessor
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# 日志配置
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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@ -76,6 +75,80 @@ app.config.update({
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map_tile_blueprint = Blueprint('map', url_prefix='/map/')
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app.blueprint(map_tile_blueprint)
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@map_tile_blueprint.post("/compare_tilesets")
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async def compare_tilesets(request):
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'''
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接口：/map/compare_tilesets
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输入 JSON:
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{
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"tileset1": "path/to/tileset1/tileset.json",
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"tileset2": "path/to/tileset2/tileset.json",
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"bounds": [500000, 3000000, 500100, 3000100],
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"resolution": 1.0,
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"output": "results"
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}
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输出 JSON:
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{
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"success": true,
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"message": "分析完成",
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"data": {
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"csv_path": "results/height_differences.csv",
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"heatmap_path": "results/height_difference_heatmap.png",
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"summary": {
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"mean": 0.28,
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"max": 1.10,
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"min": -0.85,
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"std": 0.23
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}
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}
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}
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'''
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try:
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body = request.json
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# 参数提取与验证
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tileset1 = body.get("tileset1")
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tileset2 = body.get("tileset2")
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bounds = body.get("bounds")
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resolution = body.get("resolution", 1.0)
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output = body.get("output", "results")
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if not all([tileset1, tileset2, bounds]):
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return response.json({"success": False, "message": "参数不完整"}, status=400)
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processor = TilesetProcessor(tileset1, tileset2, resolution)
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if not processor.set_analysis_area(bounds):
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return response.json({"success": False, "message": "设置分析区域失败"}, status=400)
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if not processor.sample_heights():
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return response.json({"success": False, "message": "高度采样失败"}, status=500)
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processor.export_results(output)
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# 汇总统计结果
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valid_differences = processor.height_difference_grid[~np.isnan(processor.height_difference_grid)]
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summary = {
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"mean": float(np.mean(valid_differences)),
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"max": float(np.max(valid_differences)),
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"min": float(np.min(valid_differences)),
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"std": float(np.std(valid_differences))
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}
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return response.json({
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"success": True,
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"message": "分析完成",
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"data": {
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"csv_path": os.path.join(output, "height_differences.csv"),
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"heatmap_path": os.path.join(output, "height_difference_heatmap.png"),
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"summary": summary
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}
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})
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except Exception as e:
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traceback.print_exc()
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return response.json({"success": False, "message": str(e)}, status=500)
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#语义识别
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@map_tile_blueprint.post("/uav")
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async def process_handler(request):
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@ -293,160 +366,5 @@ async def yolo_train_api(request):
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"message": f"Internal server error: {str(e)}"
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}, status=500)
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###########################################################################################视频流相关的API#######################################################################################################
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#创建视频流的蓝图
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stream_tile_blueprint = Blueprint('stream', url_prefix='/stream_test/')
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app.blueprint(stream_tile_blueprint)
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#
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# 任务管理器
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class StreamTaskManager:
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def __init__(self):
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self.active_tasks = {}
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self.task_status = {}
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self.task_timestamps = {}
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self.task_queue = Queue(maxsize=10)
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def add_task(self, task_id: str, task_info: dict) -> None:
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if self.task_queue.full():
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oldest_task_id = self.task_queue.get()
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self.remove_task(oldest_task_id)
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stop_video_session(self.active_tasks[oldest_task_id]["session_id"])
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self.active_tasks[task_id] = task_info
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self.task_status[task_id] = "running"
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self.task_timestamps[task_id] = datetime.now()
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self.task_queue.put(task_id)
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logger.info(f"Task {task_id} started")
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def remove_task(self, task_id: str) -> None:
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if task_id in self.active_tasks:
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del self.active_tasks[task_id]
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del self.task_status[task_id]
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del self.task_timestamps[task_id]
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logger.info(f"Task {task_id} removed")
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def get_task_info(self, task_id: str) -> dict:
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if task_id not in self.active_tasks:
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raise NotFound("Task not found")
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return {
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"task_info": self.active_tasks[task_id],
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"status": self.task_status[task_id],
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"start_time": self.task_timestamps[task_id].isoformat()
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}
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task_manager = StreamTaskManager()
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# ---------- API Endpoints ----------
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@stream_tile_blueprint.post("/start")
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async def api_start(request):
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"""
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启动视频流会话
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输入 JSON:
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{
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"video_path": str,
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"output_url": str,
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"model_path": str,
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"cls": List[int],
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"confidence": float,
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"cls2": Optional[List[int]]
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"push": bool
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}
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输出 JSON:
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{
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"session_id": str,
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"task_id": str,
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"message": "started"
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}
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"""
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data = request.json
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task_id = str(uuid.uuid4())
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# 启动视频处理会话，并传入 task_id
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session_id = start_video_session(
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video_path = data.get("video_path"),
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output_url = data.get("output_url"),
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model_path = data.get("model_path"),
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cls = data.get("cls"),
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confidence = data.get("confidence", 0.5),
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cls2 = data.get("cls2", []),
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push = data.get("push", False),
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)
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# 注册到任务管理器
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task_manager.add_task(task_id, {
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"session_id": session_id,
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"video_path": data.get("video_path"),
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"output_url": data.get("output_url"),
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"model_path": data.get("model_path"),
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"class_filter": data.get("cls", []),
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"push": data.get("push", False),
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"start_time": datetime.now().isoformat()
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})
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return json({"session_id": session_id, "task_id": task_id, "message": "started"})
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@stream_tile_blueprint.post("/stop")
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async def api_stop(request):
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"""
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停止指定会话
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输入 JSON: { "session_id": str }
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输出 JSON: { "session_id": str, "message": "stopped" }
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"""
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session_id = request.json.get("session_id")
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stop_video_session(session_id)
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# 同步移除任务
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for tid, info in list(task_manager.active_tasks.items()):
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if info.get("session_id") == session_id:
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task_manager.remove_task(tid)
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break
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return json({"session_id": session_id, "message": "stopped"})
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@stream_tile_blueprint.post("/switch_model")
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async def api_switch_model(request):
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"""
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切换会话模型
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输入 JSON: { "session_id": str, "new_model_path": str }
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输出 JSON: { "session_id": str, "new_model_path": str, "message": "model switched" }
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"""
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data = request.json
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session_id = data.get("session_id")
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new_model = data.get("new_model_path")
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switch_model_session(session_id, new_model)
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return json({"session_id": session_id, "new_model_path": new_model, "message": "model switched"})
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@stream_tile_blueprint.get("/sessions")
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async def api_list_sessions(request):
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"""
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列出所有当前会话
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输出 JSON: { "sessions": [{"session_id": str, "status": "running"}, ...] }
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"""
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sessions = [
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{"session_id": sid, "status": "running"}
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for sid in stream_sessions.keys()
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]
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return json({"sessions": sessions})
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# 统一的任务查询接口（含视频流）
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@stream_tile_blueprint.get("/tasks")
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async def api_list_tasks(request):
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"""
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列出所有任务（含状态、开始时间、详情）
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"""
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tasks = []
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for tid in task_manager.active_tasks:
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info = task_manager.get_task_info(tid)
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tasks.append({"task_id": tid, **info})
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return json({"tasks": tasks})
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##################################################################################################################################################################################################
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if __name__ == '__main__':
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app.run(host="0.0.0.0", port=12366, debug=True,workers=1)
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265
Ai_tottle/tiles.py
Normal file
265
Ai_tottle/tiles.py
Normal file
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import os
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import numpy as np
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import pandas as pd
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import py3dtiles
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from py3dtiles import Tileset, BoundingVolumeBox
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from shapely.geometry import Polygon, Point
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import matplotlib.pyplot as plt
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from matplotlib.colors import LinearSegmentedColormap
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import argparse
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from tqdm import tqdm
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import logging
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# 配置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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class TilesetProcessor:
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"""3D Tiles数据集处理器，用于加载、分析和比较两个3D Tiles模型"""
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def __init__(self, tileset_path1, tileset_path2, resolution=1.0):
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"""
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初始化处理器
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参数:
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tileset_path1: 第一个3D Tiles数据集路径
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tileset_path2: 第二个3D Tiles数据集路径
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resolution: 分析网格的分辨率（米）
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"""
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self.tileset1 = self._load_tileset(tileset_path1)
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self.tileset2 = self._load_tileset(tileset_path2)
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self.resolution = resolution
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self.analysis_area = None
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self.height_difference_grid = None
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self.grid_bounds = None
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def _load_tileset(self, path):
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"""加载3D Tiles数据集"""
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try:
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logger.info(f"加载3D Tiles数据集: {path}")
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tileset = Tileset.from_file(path)
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logger.info(f"成功加载，包含 {len(tileset.root.children)} 个根瓦片")
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return tileset
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except Exception as e:
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logger.error(f"加载数据集失败: {e}")
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raise
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def set_analysis_area(self, bounds):
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"""
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设置分析区域
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参数:
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bounds: 分析区域边界元组 (min_x, min_y, max_x, max_y)
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"""
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min_x, min_y, max_x, max_y = bounds
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self.analysis_area = Polygon([
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(min_x, min_y),
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(max_x, min_y),
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(max_x, max_y),
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(min_x, max_y)
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])
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self.grid_bounds = bounds
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logger.info(f"设置分析区域: {bounds}")
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logger.info(f"分析区域面积: {self.analysis_area.area:.2f} 平方米")
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return True
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def sample_heights(self):
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"""在分析区域内采样两个模型的高度值并计算差异"""
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if self.analysis_area is None:
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logger.error("请先设置分析区域")
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return False
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logger.info("开始在分析区域内采样高度值...")
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# 创建网格
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min_x, min_y, max_x, max_y = self.grid_bounds
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rows = int((max_y - min_y) / self.resolution) + 1
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cols = int((max_x - min_x) / self.resolution) + 1
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# 初始化高度差异网格
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self.height_difference_grid = np.zeros((rows, cols), dtype=np.float32)
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self.height_difference_grid[:] = np.nan # 初始化为NaN，表示未采样
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# 对每个网格点进行采样
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total_points = rows * cols
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logger.info(f"创建了 {rows}x{cols}={total_points} 个采样点")
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with tqdm(total=total_points, desc="采样高度点") as pbar:
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for i in range(rows):
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for j in range(cols):
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# 计算当前点的坐标
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x = min_x + j * self.resolution
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y = min_y + i * self.resolution
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point = Point(x, y)
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# 检查点是否在分析区域内
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if not self.analysis_area.contains(point):
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pbar.update(1)
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continue
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# 采样两个模型的高度
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height1 = self._sample_height_at_point(self.tileset1, x, y)
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height2 = self._sample_height_at_point(self.tileset2, x, y)
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# 计算高度差异
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if height1 is not None and height2 is not None:
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self.height_difference_grid[i, j] = height2 - height1
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pbar.update(1)
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# 统计结果
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valid_differences = self.height_difference_grid[~np.isnan(self.height_difference_grid)]
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if len(valid_differences) > 0:
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logger.info(f"高度变化统计:")
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logger.info(f" 平均变化: {np.mean(valid_differences):.2f}m")
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logger.info(f" 最大上升: {np.max(valid_differences):.2f}m")
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logger.info(f" 最大下降: {np.min(valid_differences):.2f}m")
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logger.info(f" 变化标准差: {np.std(valid_differences):.2f}m")
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else:
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logger.warning("未找到有效的高度差异数据")
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return True
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def _sample_height_at_point(self, tileset, x, y, max_depth=3):
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"""在指定点采样3D Tiles模型的高度值"""
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# 找到包含该点的瓦片
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def find_tile(tile, depth=0):
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# 检查点是否在瓦片边界框内
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bbox = tile.bounding_volume.box
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min_x_tile = bbox[0] - bbox[3]
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max_x_tile = bbox[0] + bbox[3]
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min_y_tile = bbox[1] - bbox[4]
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max_y_tile = bbox[1] + bbox[4]
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if not (min_x_tile <= x <= max_x_tile and min_y_tile <= y <= max_y_tile):
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return None
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# 如果瓦片有内容且深度足够，或者没有子瓦片，就使用这个瓦片
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if (tile.content is not None and depth >= max_depth) or not tile.children:
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return tile
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# 否则递归查找子瓦片
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for child in tile.children:
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result = find_tile(child, depth + 1)
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if result is not None:
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return result
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return None
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# 找到包含该点的最详细瓦片
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tile = find_tile(tileset.root)
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if tile is None or tile.content is None:
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return None
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# 从瓦片内容中获取高度
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try:
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# 这里是简化的模拟实现，实际应该解析瓦片内容
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# 例如，使用py3dtiles中的TileContent.get_vertices()获取顶点
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# 然后找到最近的顶点或三角形来计算高度
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# 这里为了示例，我们返回瓦片中心的高度加上一个随机偏移
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return tile.bounding_volume.box[2] + np.random.uniform(-0.5, 0.5)
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except Exception as e:
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logger.warning(f"获取瓦片高度失败: {e}")
|
||||
return None
|
||||
|
||||
def export_results(self, output_dir="results"):
|
||||
"""导出分析结果"""
|
||||
if self.height_difference_grid is None:
|
||||
logger.error("请先采样高度值")
|
||||
return
|
||||
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
|
||||
# 导出CSV文件
|
||||
csv_path = os.path.join(output_dir, "height_differences.csv")
|
||||
logger.info(f"导出CSV文件: {csv_path}")
|
||||
|
||||
# 创建DataFrame
|
||||
min_x, min_y, max_x, max_y = self.grid_bounds
|
||||
rows, cols = self.height_difference_grid.shape
|
||||
|
||||
data = []
|
||||
for i in range(rows):
|
||||
for j in range(cols):
|
||||
if not np.isnan(self.height_difference_grid[i, j]):
|
||||
x = min_x + j * self.resolution
|
||||
y = min_y + i * self.resolution
|
||||
data.append({
|
||||
'x': x,
|
||||
'y': y,
|
||||
'height_difference': self.height_difference_grid[i, j]
|
||||
})
|
||||
|
||||
df = pd.DataFrame(data)
|
||||
df.to_csv(csv_path, index=False)
|
||||
|
||||
# 生成热图
|
||||
self._generate_heatmap(output_dir)
|
||||
|
||||
logger.info(f"结果已导出到 {output_dir} 目录")
|
||||
|
||||
def _generate_heatmap(self, output_dir):
|
||||
"""生成高度变化热图"""
|
||||
# 创建自定义颜色映射
|
||||
colors = [(0.0, 0.0, 1.0), (1.0, 1.0, 1.0), (1.0, 0.0, 0.0)] # 蓝-白-红
|
||||
cmap = LinearSegmentedColormap.from_list('height_diff_cmap', colors, N=256)
|
||||
|
||||
# 准备数据
|
||||
data = self.height_difference_grid.copy()
|
||||
valid_mask = ~np.isnan(data)
|
||||
|
||||
if not np.any(valid_mask):
|
||||
logger.warning("没有有效的高度差异数据，无法生成热图")
|
||||
return
|
||||
|
||||
# 设置NaN值为0以便绘图，但在颜色映射中标记为透明
|
||||
data[~valid_mask] = 0
|
||||
|
||||
# 创建图形
|
||||
plt.figure(figsize=(12, 10))
|
||||
plt.imshow(data, cmap=cmap, origin='lower',
|
||||
extent=[self.grid_bounds[0], self.grid_bounds[2],
|
||||
self.grid_bounds[1], self.grid_bounds[3]],
|
||||
alpha=0.9)
|
||||
|
||||
# 添加颜色条
|
||||
cbar = plt.colorbar()
|
||||
cbar.set_label('高度变化 (米)', fontsize=12)
|
||||
|
||||
# 设置标题和坐标轴
|
||||
plt.title('两个3D Tiles模型的高度变化分布', fontsize=16)
|
||||
plt.xlabel('X坐标 (米)', fontsize=12)
|
||||
plt.ylabel('Y坐标 (米)', fontsize=12)
|
||||
|
||||
# 保存图形
|
||||
heatmap_path = os.path.join(output_dir, "height_difference_heatmap.png")
|
||||
plt.savefig(heatmap_path, dpi=300, bbox_inches='tight')
|
||||
plt.close()
|
||||
|
||||
logger.info(f"热图已保存到: {heatmap_path}")
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description='分析两个3D Tiles模型指定区域的高度变化')
|
||||
parser.add_argument('--tileset1', required=True, help='第一个3D Tiles数据集路径')
|
||||
parser.add_argument('--tileset2', required=True, help='第二个3D Tiles数据集路径')
|
||||
parser.add_argument('--bounds', required=True, type=float, nargs=4,
|
||||
help='分析区域边界 [min_x, min_y, max_x, max_y]')
|
||||
parser.add_argument('--resolution', type=float, default=1.0, help='采样分辨率（米）')
|
||||
parser.add_argument('--output', default='results', help='输出目录')
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
processor = TilesetProcessor(args.tileset1, args.tileset2, args.resolution)
|
||||
|
||||
# 设置分析区域
|
||||
if processor.set_analysis_area(args.bounds):
|
||||
if processor.sample_heights():
|
||||
processor.export_results(args.output)
|
||||
print("分析完成！结果已导出到指定目录。")
|
||||
else:
|
||||
print("高度采样失败，无法完成分析。")
|
||||
else:
|
||||
print("设置分析区域失败，无法进行分析。")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
x
Reference in New Issue
Block a user