from yolov7 import val # 初始化YOLOv7模型 model_path = 'runs/train/ir_security/weights/best.pt' # 评估模型 results = val.run( data='data.yaml', weights=model_path, imgsz=640, task='val' ) # 打印评估结果 print(results) infer.py import sys import cv2 import numpy as np import ra...
logger.info('Overriding model.yaml nc=%g with nc=%g' % (self.yaml['nc'], nc)) self.yaml['nc'] = nc # override yaml value self.model, self.save = parse_model(deepcopy(self.yaml), ch=[ch]) # model, savelist self.names = [str(i) for i in range(self.yaml['nc'])] # de...
opt = parser.parse_args() # Load pytorch model model = torch.load(opt.weights, map_location=torch.device('cpu')) print(model) #print(type(model)) model = model['model'] print(model.state_dict()) print(type(model)) for name, parameters in model.named_parameters(): # print(name,':...
defparse_model(d, ch):# model_dict, input_channels(3)logger.info('\n%3s%18s%3s%10s %-40s%-30s'% ('','from','n','params','module','arguments')) anchors, nc, gd, gw = d['anchors'], d['nc'], d['depth_multiple'], d['width_multiple'] na = (len(anchors[0]) //2)...
std::cout<<"successfully parse the onnx model"<< std::endl; 方法二(修改时间:2022-0905): 可用github yolov7的转换代码https://github.com/WongKinYiu/yolov7/tree/u5,已测试可行。同时也测试了yolov7转换,任然可运行。 二.基于C++ 使用onnx转engine且推理 ...
将上面的模块封装好后,就可以在yolo.py的parse_model函数中增加模块的参数配置逻辑了,代码如下: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 if m in [nn.Conv2d, Conv, RobustConv, RobustConv2, E_ELAN, E_ELAN_H, DWConv, GhostConv, RepConv, RepConv_OREPA, DownC, SPP, SPPF, SPPCSPC...
file=int8_calib_cache.bin tensor-file=data/dummy_input_tensor.bin int8-force-fallback=true gie-unique-id=1 operate-on-gpu=1 cluster-mode=4 output-blob-names=BLOB/BiasAdd_output_0:BBOX/BiasAdd_output_0 parse-bbox-func-name=NvDsInferParseCustomFuncDefault custom-lib-path= migraphx=0 ...
opt = parser.parse_args() 四、训练模型 上面操作全部做好之后,直接运行train.py就可以开始训练,显卡估计就开始爆炸了,程序出现下面这样子,就是在炼丹状态了,等着就ok了。 autoanchor: Analyzing anchors... anchors/target = 4.13, Best Possible Recall (BPR) = 1.0000 ...
(3)修改parse_model函数 可以直接把下面的代码粘贴到对应的位置中,后续的改进中,对应的模块就不需要做出改变,有改变处,后续会另有说明 代码语言:javascript 代码运行次数:0 运行 AI代码解释 def parse_model(d, ch, verbose=True, warehouse_manager=None): # model_dict, input_channels(3) """Parse a Y...
ERROR: ModelImporter.cpp:124 In function parseGraph: [5] Assertion failed: ctx->tensors().count(inputName) [11/02/2022-10:53:05] [E] Failed to parse onnx file [11/02/2022-10:53:05] [E] Parsing model failed [11/02/2022-10:53:05] [E] Engine creation failed ...