790 lines
32 KiB
Python
790 lines
32 KiB
Python
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"""小模型管理 Web 层
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页面：/smallmodel/index
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API：
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- /smallmodel/openIndex GET 列表
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- /smallmodel/openAdd POST 新增
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- /smallmodel/openEdit POST 编辑
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- /smallmodel/openDel POST 删除
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- /smallmodel/openUploadModel POST(multipart) 上传模型文件
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- /smallmodel/openProbe POST 探测模型 shape/labels
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- /smallmodel/openEngines GET 本机可用引擎列表
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- /smallmodel/openDetectors GET ReID 测试可选检测小模型列表
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- /smallmodel/openSetActive POST 设为默认算法
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- /smallmodel/openAssignStreams POST 把算法分配给多个摄像头
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"""
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import os
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import json
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import uuid
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from app.views.ViewsBase import *
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from app.utils.Utils import buildPageLabels
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from django.shortcuts import render
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from django.conf import settings
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from django.http import HttpResponse
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from app.models import StreamModel, AlgorithmModel
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def _algo_to_dict(a, include_streams=False):
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labels = a.labels or '[]'
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try:
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labels_list = json.loads(labels) if isinstance(labels, str) else labels
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except Exception:
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labels_list = []
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d = {
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"id": a.id,
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"name": a.name,
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"algorithm_type": a.algorithm_type,
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"task_type": a.task_type,
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"inference_engine": a.inference_engine,
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"device": a.device,
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"model_file": a.model_file,
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"model_file_size": a.model_file_size,
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"input_width": a.input_width,
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"input_height": a.input_height,
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"conf_threshold": a.conf_threshold,
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"iou_threshold": a.iou_threshold,
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"labels": labels_list,
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"is_default": a.is_default,
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"state": a.state,
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"create_time": str(a.create_time),
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"stream_count": a.streams.count() if include_streams else 0,
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}
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return d
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def _algo_parse_page_params(request, default_ps=10):
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page = request.GET.get('p', 1)
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page_size = request.GET.get('ps', default_ps)
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try:
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page = int(page)
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if page < 1:
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page = 1
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except Exception:
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page = 1
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try:
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page_size = int(page_size)
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if page_size < 1:
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page_size = default_ps
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elif page_size > 100:
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page_size = 100
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except Exception:
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page_size = default_ps
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return page, page_size
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def _algo_build_page_data(request, page, page_size, count):
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page_num = int(count / page_size)
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if count % page_size > 0:
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page_num += 1
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if page_num < 1:
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page_num = 1
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if page > page_num:
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page = page_num
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page_labels = buildPageLabels(page=page, page_num=page_num, lang=f_parseRequestLang(request))
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return {
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"page": page,
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"page_size": page_size,
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"page_num": page_num,
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"count": count,
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"pageLabels": page_labels,
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}
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def smallmodel_openIndex(request):
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ret = False
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msg = LANG_VIEWS_T(request, "msg_unknown_error")
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data = []
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page_data = {}
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if request.method == 'GET':
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__check_ret, __check_msg = f_checkRequestSafe(request)
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if __check_ret:
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params = f_parseGetParams(request)
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page, page_size = _algo_parse_page_params(request, default_ps=10)
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qs = AlgorithmModel.objects.all().order_by('-id')
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engine = params.get('engine', '').strip()
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if engine:
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qs = qs.filter(inference_engine=engine)
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state = params.get('state', '').strip()
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if state != '':
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qs = qs.filter(state=int(state))
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count = qs.count()
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skip = (page - 1) * page_size
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data = [_algo_to_dict(a, include_streams=True) for a in qs[skip:skip + page_size]]
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page_data = _algo_build_page_data(request, page, page_size, count)
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ret = True
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msg = LANG_VIEWS_T(request, "msg_success")
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else:
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msg = __check_msg
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else:
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msg = LANG_VIEWS_T(request, "msg_method_not_supported")
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return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data, "pageData": page_data})
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def _apply_algo_rules(fields):
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"""按任务类型规范化字段（ReID 仅 OnnxRuntime + OSNet）。"""
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task = (fields.get("task_type") or "detect").lower()
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if task == "reid":
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fields["inference_engine"] = "onnxruntime"
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fields["algorithm_type"] = "osnet"
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fields["labels"] = "[]"
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if not fields.get("input_width"):
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fields["input_width"] = 128
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if not fields.get("input_height"):
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fields["input_height"] = 256
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return fields
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def _validate_algo_fields(request, fields):
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task = (fields.get("task_type") or "detect").lower()
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if task == "reid":
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eng = (fields.get("inference_engine") or "").lower()
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if eng not in ("onnxruntime", "onnx"):
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return False, LANG_VIEWS_T(request, "alg_reid_onnx_only")
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if (fields.get("algorithm_type") or "").lower() != "osnet":
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return False, LANG_VIEWS_T(request, "alg_reid_osnet_only")
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return True, ""
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def _parse_algo_params(params):
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"""从 POST 参数构造 AlgorithmModel 字段 dict"""
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out = {}
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if "name" in params:
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out["name"] = (params.get("name") or "").strip()
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if "algorithm_type" in params:
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out["algorithm_type"] = (params.get("algorithm_type") or "yolo8").strip()
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if "task_type" in params:
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out["task_type"] = (params.get("task_type") or "detect").strip()
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if "inference_engine" in params:
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out["inference_engine"] = (params.get("inference_engine") or "yolo_pytorch").strip()
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if "device" in params:
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out["device"] = (params.get("device") or "cpu").strip()
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if "model_file" in params:
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out["model_file"] = (params.get("model_file") or "").strip()
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if "input_width" in params:
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try:
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out["input_width"] = int(params.get("input_width", 640))
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except Exception:
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pass
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if "input_height" in params:
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try:
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out["input_height"] = int(params.get("input_height", 640))
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except Exception:
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pass
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if "conf_threshold" in params:
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try:
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out["conf_threshold"] = float(params.get("conf_threshold", 0.4))
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except Exception:
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pass
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if "iou_threshold" in params:
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try:
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out["iou_threshold"] = float(params.get("iou_threshold", 0.5))
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except Exception:
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pass
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if "labels" in params:
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lb = params.get("labels")
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if isinstance(lb, list):
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out["labels"] = json.dumps([str(x).strip() for x in lb if str(x).strip()], ensure_ascii=False)
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elif isinstance(lb, str):
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# 英文逗号分隔：支持中文类别（只要用英文逗号隔开就是一个类别）
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try:
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arr = json.loads(lb)
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if isinstance(arr, list):
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out["labels"] = json.dumps([str(x).strip() for x in arr if str(x).strip()], ensure_ascii=False)
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else:
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out["labels"] = "[]"
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except Exception:
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items = [s.strip() for s in lb.split(",") if s.strip()]
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if items:
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out["labels"] = json.dumps(items, ensure_ascii=False)
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else:
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out["labels"] = "[]"
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if "state" in params:
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try:
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out["state"] = int(params.get("state", 1))
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except Exception:
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pass
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if "is_default" in params:
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try:
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out["is_default"] = int(params.get("is_default", 0))
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except Exception:
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pass
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if "model_file_size" in params:
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try:
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out["model_file_size"] = int(params.get("model_file_size", 0))
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except Exception:
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pass
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return out
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def smallmodel_index(request):
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return render(request, 'app/smallmodel/index.html', {})
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def smallmodel_test(request):
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return render(request, 'app/smallmodel/test.html', {})
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def smallmodel_openDetail(request):
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ret = False
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msg = LANG_VIEWS_T(request, "msg_unknown_error")
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data = {}
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if request.method == 'GET':
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__check_ret, __check_msg = f_checkRequestSafe(request)
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if __check_ret:
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params = f_parseGetParams(request)
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try:
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aid = int(params.get("id", 0))
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a = AlgorithmModel.objects.get(id=aid)
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data = _algo_to_dict(a, include_streams=True)
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ret = True
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msg = LANG_VIEWS_T(request, "msg_success")
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except Exception as e:
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msg = str(e)
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else:
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msg = __check_msg
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else:
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msg = LANG_VIEWS_T(request, "msg_method_not_supported")
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return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
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def _test_upload_dir():
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from app.services.algorithm_test_service import upload_dir
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return upload_dir()
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def smallmodel_openTestStart(request):
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ret = False
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msg = LANG_VIEWS_T(request, "msg_unknown_error")
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data = {}
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if request.method == 'POST':
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__check_ret, __check_msg = f_checkRequestSafe(request)
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if __check_ret:
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try:
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aid = int(request.POST.get("algorithm_id", 0) or 0)
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a = AlgorithmModel.objects.get(id=aid)
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f = request.FILES.get("file")
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if not f:
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msg = LANG_VIEWS_T(request, "alg_no_file")
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elif not a.model_file:
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msg = LANG_VIEWS_T(request, "alg_no_model_file")
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else:
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ext = os.path.splitext(f.name)[1].lower()
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allowed = (".jpg", ".jpeg", ".png", ".bmp", ".webp", ".mp4", ".avi", ".mov", ".mkv", ".webm", ".m4v")
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if ext not in allowed:
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msg = LANG_VIEWS_T(request, "alg_unsupported_ext") + ": " + ext
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else:
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detector_algo = None
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task_type = (a.task_type or "detect").lower()
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start_ok = True
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if task_type == "reid":
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detector_id = int(request.POST.get("detector_algorithm_id", 0) or 0)
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if not detector_id:
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start_ok = False
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msg = LANG_VIEWS_T(request, "alg_reid_need_detector")
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else:
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try:
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detector_algo = AlgorithmModel.objects.get(id=detector_id)
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except AlgorithmModel.DoesNotExist:
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start_ok = False
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msg = LANG_VIEWS_T(request, "alg_reid_need_detector")
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else:
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if (detector_algo.task_type or "detect").lower() != "detect":
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start_ok = False
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msg = LANG_VIEWS_T(request, "alg_reid_detector_must_detect")
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elif detector_algo.state != 1:
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start_ok = False
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msg = LANG_VIEWS_T(request, "alg_reid_detector_disabled")
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elif not detector_algo.model_file:
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start_ok = False
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msg = LANG_VIEWS_T(request, "alg_no_model_file")
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if start_ok:
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fname = "%s_%s%s" % (uuid.uuid4().hex[:12], aid, ext)
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dest = os.path.join(_test_upload_dir(), fname)
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with open(dest, "wb") as out:
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for chunk in f.chunks():
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out.write(chunk)
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from app.services.algorithm_test_service import start_test
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task_id = start_test(a, dest, f.name, detector_algo=detector_algo)
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data = {"task_id": task_id}
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ret = True
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msg = LANG_VIEWS_T(request, "msg_success")
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except Exception as e:
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msg = str(e)
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else:
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msg = __check_msg
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else:
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msg = LANG_VIEWS_T(request, "msg_method_not_supported")
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return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
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def smallmodel_openTestStatus(request):
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ret = False
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msg = LANG_VIEWS_T(request, "msg_unknown_error")
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data = {}
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if request.method == 'GET':
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__check_ret, __check_msg = f_checkRequestSafe(request)
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if __check_ret:
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params = f_parseGetParams(request)
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task_id = (params.get("task_id") or "").strip()
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if not task_id:
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msg = "missing task_id"
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|
|
else:
|
|||
|
|
from app.services.algorithm_test_service import get_task
|
|||
|
|
t = get_task(task_id)
|
|||
|
|
if not t:
|
|||
|
|
msg = "task not found"
|
|||
|
|
else:
|
|||
|
|
data = {
|
|||
|
|
"task_id": t.get("id"),
|
|||
|
|
"status": t.get("status"),
|
|||
|
|
"progress": t.get("progress", 0),
|
|||
|
|
"message": t.get("message", ""),
|
|||
|
|
"report": t.get("report"),
|
|||
|
|
"output_url": t.get("output_url", ""),
|
|||
|
|
"output_type": t.get("output_type", ""),
|
|||
|
|
"error": t.get("error", ""),
|
|||
|
|
}
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openTestOutput(request):
|
|||
|
|
"""返回算法测试渲染结果（图片/视频），避免运行时生成的 static 文件无法通过 /static/ 访问。"""
|
|||
|
|
if request.method != 'GET':
|
|||
|
|
return HttpResponse(b"method not allowed", status=405)
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if not __check_ret:
|
|||
|
|
return HttpResponse(__check_msg.encode("utf-8"), status=403)
|
|||
|
|
params = f_parseGetParams(request)
|
|||
|
|
task_id = (params.get("task_id") or "").strip()
|
|||
|
|
from app.services.algorithm_test_service import resolve_output_file
|
|||
|
|
fp, ctype = resolve_output_file(task_id)
|
|||
|
|
if not fp:
|
|||
|
|
return HttpResponse(b"not found", status=404)
|
|||
|
|
try:
|
|||
|
|
with open(fp, "rb") as f:
|
|||
|
|
data = f.read()
|
|||
|
|
except Exception:
|
|||
|
|
return HttpResponse(b"read error", status=500)
|
|||
|
|
resp = HttpResponse(data, content_type=ctype)
|
|||
|
|
resp["Cache-Control"] = "no-store, no-cache, must-revalidate"
|
|||
|
|
resp["Content-Disposition"] = 'inline; filename="%s"' % os.path.basename(fp)
|
|||
|
|
return resp
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openTestClearTemp(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
data = {}
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
try:
|
|||
|
|
from app.services.algorithm_test_service import clear_temp_files
|
|||
|
|
data = clear_temp_files()
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "alg_test_clear_ok")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openAdd(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
params = f_parsePostParams(request)
|
|||
|
|
try:
|
|||
|
|
fields = _parse_algo_params(params)
|
|||
|
|
fields = _apply_algo_rules(fields)
|
|||
|
|
ok, err = _validate_algo_fields(request, fields)
|
|||
|
|
if not ok:
|
|||
|
|
msg = err
|
|||
|
|
elif not fields.get("name"):
|
|||
|
|
msg = LANG_VIEWS_T(request, "alg_name_required")
|
|||
|
|
else:
|
|||
|
|
a = AlgorithmModel.objects.create(**fields)
|
|||
|
|
if fields.get("is_default") == 1:
|
|||
|
|
AlgorithmModel.objects.exclude(id=a.id).update(is_default=0)
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openEdit(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
params = f_parsePostParams(request)
|
|||
|
|
try:
|
|||
|
|
aid = int(params.get("id", 0))
|
|||
|
|
a = AlgorithmModel.objects.get(id=aid)
|
|||
|
|
fields = _parse_algo_params(params)
|
|||
|
|
fields = _apply_algo_rules(fields)
|
|||
|
|
ok, err = _validate_algo_fields(request, fields)
|
|||
|
|
if not ok:
|
|||
|
|
msg = err
|
|||
|
|
else:
|
|||
|
|
for k, v in fields.items():
|
|||
|
|
setattr(a, k, v)
|
|||
|
|
a.save()
|
|||
|
|
if a.is_default == 1:
|
|||
|
|
AlgorithmModel.objects.exclude(id=a.id).update(is_default=0)
|
|||
|
|
# 热更新：若该算法被某路正在跑的摄像头使用，重载其 pipeline
|
|||
|
|
try:
|
|||
|
|
from app.analysis.manager import AnalysisManager
|
|||
|
|
mgr = AnalysisManager()
|
|||
|
|
for s in a.streams.all():
|
|||
|
|
if mgr.is_running(s.id):
|
|||
|
|
mgr.stop(s.id)
|
|||
|
|
mgr.start(s)
|
|||
|
|
except Exception:
|
|||
|
|
pass
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openDel(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
params = f_parsePostParams(request)
|
|||
|
|
try:
|
|||
|
|
aid = int(params.get("id", 0))
|
|||
|
|
a = AlgorithmModel.objects.get(id=aid)
|
|||
|
|
# 先收集使用该算法的摄像头（解绑前查询，否则 update 后反向关系为空）
|
|||
|
|
affected_streams = list(a.streams.values_list('id', flat=True))
|
|||
|
|
# 检查是否有业务算法引用此小模型
|
|||
|
|
from app.models import BizAlgorithmModel
|
|||
|
|
from django.db.models import Q
|
|||
|
|
ref_count = BizAlgorithmModel.objects.filter(
|
|||
|
|
Q(small_model_id=aid) | Q(detector_model_id=aid)
|
|||
|
|
).count()
|
|||
|
|
if ref_count > 0:
|
|||
|
|
raise ValueError(LANG_VIEWS_T(request, "smallmodel_in_use_by_biz"))
|
|||
|
|
# 停止使用该算法的 pipeline（必须在解绑前完成）
|
|||
|
|
try:
|
|||
|
|
from app.analysis.manager import AnalysisManager
|
|||
|
|
mgr = AnalysisManager()
|
|||
|
|
for sid in affected_streams:
|
|||
|
|
if mgr.is_running(sid):
|
|||
|
|
mgr.stop(sid)
|
|||
|
|
except Exception:
|
|||
|
|
pass
|
|||
|
|
# 解绑摄像头
|
|||
|
|
StreamModel.objects.filter(algorithm_id=aid).update(algorithm=None)
|
|||
|
|
a.delete()
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def _models_dir():
|
|||
|
|
from app.analysis.worker_pool import get_weight_dir
|
|||
|
|
return get_weight_dir()
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openUploadModel(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
data = {}
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
try:
|
|||
|
|
f = request.FILES.get("file")
|
|||
|
|
if not f:
|
|||
|
|
msg = LANG_VIEWS_T(request, "alg_no_file")
|
|||
|
|
else:
|
|||
|
|
ext = os.path.splitext(f.name)[1].lower()
|
|||
|
|
allowed = (".onnx", ".pt", ".xml", ".bin", ".engine", ".model", ".yaml", ".labels", ".names")
|
|||
|
|
if ext and ext not in allowed:
|
|||
|
|
msg = LANG_VIEWS_T(request, "alg_unsupported_ext") + ": " + ext
|
|||
|
|
else:
|
|||
|
|
# 文件名：年月日时分秒_原文件名（保留原名称，前面拼时间戳避免冲突）
|
|||
|
|
from datetime import datetime
|
|||
|
|
ts = datetime.now().strftime("%Y%m%d%H%M%S")
|
|||
|
|
# 安全处理原文件名：去掉路径分隔符，保留扩展名
|
|||
|
|
raw_name = os.path.basename(f.name)
|
|||
|
|
# 限制总长度，避免文件名过长
|
|||
|
|
name_part = os.path.splitext(raw_name)[0]
|
|||
|
|
if len(name_part) > 60:
|
|||
|
|
name_part = name_part[:60]
|
|||
|
|
fname = "%s_%s%s" % (ts, name_part, ext)
|
|||
|
|
dest = os.path.join(_models_dir(), fname)
|
|||
|
|
with open(dest, "wb") as out:
|
|||
|
|
for chunk in f.chunks():
|
|||
|
|
out.write(chunk)
|
|||
|
|
if ext == ".pt":
|
|||
|
|
try:
|
|||
|
|
from app.utils.ModelTrust import require_trusted_model
|
|||
|
|
require_trusted_model(dest)
|
|||
|
|
except Exception:
|
|||
|
|
os.unlink(dest)
|
|||
|
|
raise
|
|||
|
|
size = os.path.getsize(dest)
|
|||
|
|
# 清理旧模型文件：未被任何启用算法引用的文件
|
|||
|
|
try:
|
|||
|
|
_cleanup_unused_model_files(exclude=fname)
|
|||
|
|
except Exception as e:
|
|||
|
|
import logging
|
|||
|
|
logging.getLogger("app").warning("清理旧模型文件失败: %s" % str(e))
|
|||
|
|
# 相对路径
|
|||
|
|
data = {
|
|||
|
|
"model_file": fname,
|
|||
|
|
"model_file_size": size,
|
|||
|
|
"filename": f.name,
|
|||
|
|
}
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def _cleanup_unused_model_files(exclude=None):
|
|||
|
|
"""清理未被任何启用算法引用的模型文件（保留 exclude 指定的刚上传文件）。"""
|
|||
|
|
models_dir = _models_dir()
|
|||
|
|
if not os.path.isdir(models_dir):
|
|||
|
|
return 0
|
|||
|
|
# 收集所有算法（含禁用）引用的模型文件名，避免删除被禁用算法的模型文件
|
|||
|
|
used_files = set()
|
|||
|
|
for a in AlgorithmModel.objects.all():
|
|||
|
|
if a.model_file:
|
|||
|
|
used_files.add(os.path.basename(a.model_file))
|
|||
|
|
removed = 0
|
|||
|
|
allowed_ext = (".onnx", ".pt", ".xml", ".bin", ".engine", ".model", ".yaml", ".labels", ".names")
|
|||
|
|
for fn in os.listdir(models_dir):
|
|||
|
|
fp = os.path.join(models_dir, fn)
|
|||
|
|
if not os.path.isfile(fp):
|
|||
|
|
continue
|
|||
|
|
ext = os.path.splitext(fn)[1].lower()
|
|||
|
|
if ext not in allowed_ext:
|
|||
|
|
continue
|
|||
|
|
if exclude and fn == exclude:
|
|||
|
|
continue
|
|||
|
|
if fn in used_files:
|
|||
|
|
continue
|
|||
|
|
try:
|
|||
|
|
os.remove(fp)
|
|||
|
|
removed += 1
|
|||
|
|
except Exception:
|
|||
|
|
pass
|
|||
|
|
return removed
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openProbe(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
data = {}
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
params = f_parsePostParams(request)
|
|||
|
|
try:
|
|||
|
|
engine_name = (params.get("engine") or "onnxruntime").strip()
|
|||
|
|
model_file = (params.get("model_file") or "").strip()
|
|||
|
|
if not model_file:
|
|||
|
|
msg = LANG_VIEWS_T(request, "alg_no_model_file")
|
|||
|
|
else:
|
|||
|
|
from app.analysis.worker_pool import resolve_model_path
|
|||
|
|
abs_path = resolve_model_path(model_file)
|
|||
|
|
if not abs_path:
|
|||
|
|
msg = LANG_VIEWS_T(request, "alg_no_model_file")
|
|||
|
|
else:
|
|||
|
|
from app.analysis.engines.factory import EngineFactory, list_engines
|
|||
|
|
from app.analysis.engines.base import EngineNotAvailableError
|
|||
|
|
try:
|
|||
|
|
task_type = (params.get("task_type") or "detect").strip().lower()
|
|||
|
|
algorithm_type = (params.get("algorithm_type") or "yolo8").strip()
|
|||
|
|
if task_type == "reid":
|
|||
|
|
engine_name = "onnxruntime"
|
|||
|
|
eng = EngineFactory.create(
|
|||
|
|
engine_name,
|
|||
|
|
model_file=abs_path,
|
|||
|
|
task_type=task_type,
|
|||
|
|
algorithm_type=algorithm_type,
|
|||
|
|
)
|
|||
|
|
data = eng.probe()
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except EngineNotAvailableError as e:
|
|||
|
|
msg = LANG_VIEWS_T(request, "engine_not_installed") + ": " + str(e)
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openEngines(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
data = []
|
|||
|
|
if request.method == 'GET':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
try:
|
|||
|
|
from app.analysis.engines.factory import list_engines, device_options
|
|||
|
|
data = list_engines()
|
|||
|
|
# 附带 device_options 便于前端直接渲染
|
|||
|
|
for item in data:
|
|||
|
|
item["device_options"] = device_options(item["name"])
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openDetectors(request):
|
|||
|
|
"""列出可用于 ReID 测试的检测小模型（task_type=detect 且启用）。"""
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
data = []
|
|||
|
|
if request.method == 'GET':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
try:
|
|||
|
|
qs = AlgorithmModel.objects.filter(state=1, task_type="detect").order_by("-is_default", "-id")
|
|||
|
|
data = [{
|
|||
|
|
"id": a.id,
|
|||
|
|
"name": a.name,
|
|||
|
|
"model_file": a.model_file,
|
|||
|
|
"inference_engine": a.inference_engine,
|
|||
|
|
"algorithm_type": a.algorithm_type,
|
|||
|
|
"is_default": a.is_default,
|
|||
|
|
} for a in qs]
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg, "data": data})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openSetActive(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
params = f_parsePostParams(request)
|
|||
|
|
try:
|
|||
|
|
aid = int(params.get("id", 0))
|
|||
|
|
a = AlgorithmModel.objects.get(id=aid)
|
|||
|
|
AlgorithmModel.objects.exclude(id=aid).update(is_default=0)
|
|||
|
|
a.is_default = 1
|
|||
|
|
a.save()
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg})
|
|||
|
|
|
|||
|
|
|
|||
|
|
def smallmodel_openAssignStreams(request):
|
|||
|
|
ret = False
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_unknown_error")
|
|||
|
|
if request.method == 'POST':
|
|||
|
|
__check_ret, __check_msg = f_checkRequestSafe(request)
|
|||
|
|
if __check_ret:
|
|||
|
|
params = f_parsePostParams(request)
|
|||
|
|
try:
|
|||
|
|
aid = int(params.get("algorithm_id", 0))
|
|||
|
|
a = AlgorithmModel.objects.get(id=aid)
|
|||
|
|
stream_ids = params.get("stream_ids") or []
|
|||
|
|
if isinstance(stream_ids, str):
|
|||
|
|
try:
|
|||
|
|
stream_ids = json.loads(stream_ids)
|
|||
|
|
except Exception:
|
|||
|
|
stream_ids = [s for s in stream_ids.split(",") if s]
|
|||
|
|
# 先解绑所有当前使用该算法的摄像头
|
|||
|
|
StreamModel.objects.filter(algorithm_id=aid).update(algorithm=None)
|
|||
|
|
# 再绑新选的
|
|||
|
|
restarted = []
|
|||
|
|
for sid in stream_ids:
|
|||
|
|
try:
|
|||
|
|
s = StreamModel.objects.get(id=int(sid))
|
|||
|
|
# 若该路正在跑，需重启以应用新算法
|
|||
|
|
try:
|
|||
|
|
from app.analysis.manager import AnalysisManager
|
|||
|
|
if AnalysisManager().is_running(s.id):
|
|||
|
|
AnalysisManager().stop(s.id)
|
|||
|
|
restarted.append(s.id)
|
|||
|
|
except Exception:
|
|||
|
|
pass
|
|||
|
|
s.algorithm = a
|
|||
|
|
s.save()
|
|||
|
|
except Exception:
|
|||
|
|
pass
|
|||
|
|
# 重启刚才停掉的
|
|||
|
|
for sid in restarted:
|
|||
|
|
try:
|
|||
|
|
s = StreamModel.objects.get(id=sid)
|
|||
|
|
AnalysisManager().start(s)
|
|||
|
|
except Exception:
|
|||
|
|
pass
|
|||
|
|
ret = True
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_success")
|
|||
|
|
except Exception as e:
|
|||
|
|
msg = str(e)
|
|||
|
|
else:
|
|||
|
|
msg = __check_msg
|
|||
|
|
else:
|
|||
|
|
msg = LANG_VIEWS_T(request, "msg_method_not_supported")
|
|||
|
|
return f_responseJson({"code": 1000 if ret else 0, "msg": msg})
|