yolo中断训练

app/controller/AlgorithmController.py

@@ -31,6 +31,7 @@ from pathlib import Path
 
 bp = Blueprint('AlgorithmController', __name__)
 
+ifKillDict = {}
 
 def start_train_algorithm():
     """
@@ -147,6 +148,42 @@ def algorithm_process_value_websocket():
 
     return wrapTheFunction
 
+def algorithm_kill_value_websocket():
+    """
+    获取kill值, websocket发布
+    """
+
+    def wrapTheFunction(func):
+        @wraps(func)
+        def wrapped_function(*args, **kwargs):
+            data = func(*args, **kwargs)
+            id = data["id"]
+            data_res = {'code': 1, "type": 'kill', 'msg': 'success', 'data': data}
+            manager.send_message_proj_json(message=data_res, id=id)
+            return data
+
+        return wrapped_function
+
+    return wrapTheFunction
+
+
+def algorithm_error_value_websocket():
+    """
+    获取error值, websocket发布
+    """
+
+    def wrapTheFunction(func):
+        @wraps(func)
+        def wrapped_function(*args, **kwargs):
+            data = func(*args, **kwargs)
+            id = data["id"]
+            data_res = {'code': 2, "type": 'error', 'msg': 'fail', 'data': data}
+            manager.send_message_proj_json(message=data_res, id=id)
+            return data
+
+        return wrapped_function
+
+    return wrapTheFunction
 
 def obtain_train_param():
     """
@@ -164,7 +201,6 @@ def obtain_train_param():
 
     return wrapTheFunction
 
-
 def obtain_test_param():
     """
        获取验证参数
@@ -215,6 +251,16 @@ def obtain_download_pt_param():
 
     return wrapTheFunction
 
+@bp.route('/change_ifKillDIct', methods=['get'])
+def change_ifKillDIct():
+    """
+    修改全局变量
+    """
+    id = request.args.get('id')
+    type = request.args.get('type')
+    global ifKillDict
+    ifKillDict[id] = False
+    return output_wrapped(0, 'success')
 
 # @start_train_algorithm()
 # def start(param: str):
@@ -241,6 +287,13 @@ from app.schemas.TrainResult import DetectProcessValueDice, DetectReport
 from app import file_tool
 
 
+def error_return(id: str):
+    """
+    算法出错，返回
+    """
+    data_res = {'code': 2, "type": 'error', 'msg': 'fail', 'data': None}
+    manager.send_message_proj_json(message=data_res, id=id)
+
 # 启动训练
 @start_train_algorithm()
 def train_R0DY(params_str, id):
@@ -255,8 +308,10 @@ def train_R0DY(params_str, id):
     epoches = params.get('epochnum').value
     batch_size = params.get('batch_size').value
     device = params.get('device').value
-
-    train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id)
+    try:
+        train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id)
+    except:
+        error_return(id=id)
 
 
 # 启动验证程序

app/yolov5/train_server.py

@@ -61,6 +61,8 @@ from app.yolov5.utils.torch_utils import (EarlyStopping, ModelEMA, de_parallel,
                                smart_resume, torch_distributed_zero_first)
 from app.schemas.TrainResult import Report, ProcessValueList
 from app.controller.AlgorithmController import algorithm_process_value_websocket
+from app.controller.AlgorithmController import ifKillDict
+from app.utils.websocket_tool import manager
 LOCAL_RANK = int(os.getenv('LOCAL_RANK', -1))  # https://pytorch.org/docs/stable/elastic/run.html
 RANK = int(os.getenv('RANK', -1))
 WORLD_SIZE = int(os.getenv('WORLD_SIZE', 1))
@@ -304,6 +306,15 @@ def train(hyp, opt, device, data_list,id,callbacks):  # hyp is path/to/hyp.yaml
                     num_train_img=train_num,
                     train_mod_savepath=best)
 
+    def kill_return():
+        """
+        算法中断，返回
+        """
+        id = report.id
+        data = report.dict()
+        data_res = {'code': 1, "type": 'kill', 'msg': 'fail', 'data': data}
+        manager.send_message_proj_json(message=data_res, id=id)    
+
     @algorithm_process_value_websocket()
     def report_cellback(i, num_epochs, reportAccu):
         report.rate_of_progess = ((i + 1) / num_epochs) * 100
@@ -314,6 +325,11 @@ def train(hyp, opt, device, data_list,id,callbacks):  # hyp is path/to/hyp.yaml
     ###################结束#######################
     for epoch in range(start_epoch, epochs):  # epoch ------------------------------------------------------------------
         #callbacks.run('on_train_epoch_start')
+        global ifKillDict
+        ifkill = ifKillDict['id']
+        if ifkill:
+            kill_return()
+            break
         model.train()
 
         # Update image weights (optional, single-GPU only)