self.model = model self.model = revert_sync_batchnorm(self.model) self.model.to('cpu') self.model.eval()# 切换为 eval 模式,不计算梯度 self.detect_layer = self.model.model[-1]# 得到最后的检测层 self.model.traced =True# False 修改为 True # 随机制造一个 bs=1 输入 tensor rand_exampl...
traced_script_module saved! model is traced! 暂时不太清楚啥意思。 回到顶部 3. onnx导出 python export.py --weights yolov7.pt --grid --end2end --simplify \ --topk-all 100 --iou-thres 0.65 --conf-thres 0.35 --img-size 640 640 --max-wh 640 这里我们主要关注得到的 yolov7.onnx...
map_location=device)# load FP32 modelstride=int(model.stride.max())# model strideimgsz=check_img_size(imgsz,s=stride)# check img_sizeifFalse:model=TracedModel(model,device,self.img_size)ifhalf:model.half()# to FP16# Second-stage classifierclassify=Falseifclassify:modelc=load_classifier(na...
='cpu'# half precision only supported on CUDA# Load modelmodel = attempt_load(weights, map_location=device)# load FP32 modelstride = int(model.stride.max())# model strideimgsz = check_img_size(imgsz, s=stride)# check img_sizeifFalse: model = TracedModel(model, device, self.img_size...
strip_optimizer, set_logging, increment_path from utils.plots import plot_one_box from utils.torch_utils import select_device, load_classifier, time_synchronized, TracedModel import pycuda.autoinit import pycuda.driver as cuda import tensorrt as trt # Allocates all buffers required for an engine...
Yolo X, v7, v8 and several Multi-Object Tracker(SORT, DeepSORT, ByteTrack, BoT-SORT, etc.) in MOT17 and VisDrone2019 Dataset. It uses a unified style and integrated tracker for easy embedding in your own projects. - Yolov7-tracker/test.py at v2 · JackWo
model is traced! video 1/1 (1/402) /Users/macbookpro/jup/yolov7/inference-data/busy_street.mp4: 24 persons, 1 bicycle, 8 cars, 3 traffic lights, 2 backpacks, 2 handbags, Done. (1071.6ms) Inference, (2.4ms) NMS video 1/1 (2/402) /Users/macbookpro/jup/yolov7/inference-data/...
model is traced! /yolov7/venv3/lib/python3.8/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.) ...
from utils.torch_utils import select_device, time_synchronized, TracedModel def test(data, weights=None, batch_size=32, imgsz=640, conf_thres=0.001, iou_thres=0.6, # for NMS save_json=False, single_cls=False, augment=False, verbose=False, model=None, dataloader=None, ...
y, dt = [], []# outputsforminself.model:#按配置文件的每一层网络进行叠加ifm.f != -1:# if not from previous layerx = y[m.f]ifisinstance(m.f,int)else[xifj == -1elsey[j]forjinm.f]# from earlier layersifnothasattr(self,'traced'): ...