I want to load my custom model weight directly in code how can I do that? And while loading custom weight in prompt it is showing error " YOLOv9-DeepSORT-Object-Tracking\detect_dual_tracking.py", line 191, in run pred = pred[0][1] ~~~~~~~^^^ IndexError: index 1 is out of bounds for dimension 0 with size 1.
Sir, I have a problem. I want to save the output in a text file format with vehicle ids, vehicle classes, confidence lvl, bounding boxes coordinates for each frame with my trained model weight. but I face error. Is it possible to contact u.
we are using pretrained model, which is YOLO V9 , you can train your CNN or other model for object detection along with the bounding box and replace it inplace of YOLO V9 model
In the object tracking model, I need to find the distance of the vehicle from the camera which is recorded, how can I achieve it can you please help me to sort out this problem, this could be very helpful for my research paper
hello sir i have followed all your steps, but it is showing this error -> File "C:\Users\sharm\OneDrive\Desktop\YOLOv9-DeepSORT-Object-Tracking-main\yolov9\detect_dual_tracking.py", line 9, in from deep_sort_pytorch.utils.parser import get_config ModuleNotFoundError: No module named 'deep_sort_pytorch.utils' Pls guide sir 🙏🙏🙏🙏🙏🙏🙏🙏
first import like this import deep_sort_pytorch then from deep_sort_pytorch.utils.parser import get_config if any method did not work then import deep_sort_pytorch from deep_sort_pytorch.deep_sort import DeepSort import yaml # Load DeepSORT configuration from YAML file with open("deep_sort_pytorch/configs/deep_sort.yaml", 'r') as config_file: cfg_deep = yaml.safe_load(config_file) # Initialize DeepSORT tracker with loaded configuration deepsort = DeepSort(cfg_deep['DEEPSORT']['REID_CKPT'], max_dist=cfg_deep['DEEPSORT']['MAX_DIST'], min_confidence=cfg_deep['DEEPSORT']['MIN_CONFIDENCE'], nms_max_overlap=cfg_deep['DEEPSORT']['NMS_MAX_OVERLAP'], max_iou_distance=cfg_deep['DEEPSORT']['MAX_IOU_DISTANCE'], max_age=cfg_deep['DEEPSORT']['MAX_AGE'], n_init=cfg_deep['DEEPSORT']['N_INIT'], nn_budget=cfg_deep['DEEPSORT']['NN_BUDGET'], use_cuda=True) use this to initialize deepsort
