c4 = round((ymax - ymin) / image_height, 6) if class_name in classes: bboxes.append([c1, c2, c3, c4]) class_names.append(class_name) with open(os.path.join(yolo_labels_dir, item + ".txt"), 'w') as file: for bbox, class_name in zip(bboxes, class_names): file.write...
python深色版本 import xml.etree.ElementTree as ET import os def convert_voc_to_yolo(voc_file, yolo_file, class_names): tree = ET.parse(voc_file) root = tree.getroot() width = int(root.find('size/width').text) height = int(root.find('size/height').text) with open(yolo_file, '...
# class namesnames:0:BrownSpot1:RiceBlast2:BacterialBlight 2.1数据集划分 通过split_train_val.py得到trainval.txt、val.txt、test.txt 代码语言:python 代码运行次数:2 复制 Cloud Studio代码运行 # coding:utf-8importosimportrandomimportargparse parser=argparse.ArgumentParser()#xml文件的地址,根据自己的...
yaml_path = str(Path(ultralytics.__file__).parent/'cfg/datasets/coco128-seg.yaml') class_names = utils.yaml_load(yaml_path)['names'] from torchkeras import plots boxes = result[0].boxes.data masks = result[0].masks.data plots.plot_instance_segmentation(img,boxes,masks,class_names) ...
# class names names: ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', ...
# numberofclassesnc:5#classnamesnames:0:echinus1:holothurian2:scallop3:starfish4:waterweeds 2.2 开启训练 代码语言:javascript 复制 importwarnings warnings.filterwarnings('ignore')from ultralyticsimportYOLOif__name__=='__main__':model=YOLO('ultralytics/cfg/models/v8/lyolo/yolov8n-lyolo.yaml'...
train: train/valid: valid/test: test/# number of classesnc: 12# class namesnames: ["Barn Swallow","Common Firecrest","Common Nightingale","Eurasian Chaffinch","Eurasian Crag Martin","European Goldfinch","European Greenfinch","European Serin","House Sparrow","Spanish Sparrow","Western House ...
img0 = cv2.putText(img0, str(idx) + ' ' + names[int(class_id)], (int(bbox[idx][0]), int(bbox[idx][1] + 16)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1) KeyError: 8220 打印了label_dict和pred_all,分别为{0: 'wu', 1: 'qiao_ji', 2: 'chong_wang', 3:...
在names部分,指定每个类别的名称。这些信息通常可以在任何YOLOv8数据集的data.yaml文件中找到。 如前所述,Python API或CLI(命令行方式)都可以用来进行本地训练。 Python API方式 创建另一个名为main.py的文件。这是实际训练开始的地方: 复制 from ultralytics import YOLO ...
import cv2 import time import random import numpy as np from numpy import ndarray from typing import List, Tuple from ais_bench.infer.interface import InferSession CLASS_COLORS = [[random.randint(0, 255) for _ in range(3)] for _ in range(80)] CLASS_NAMES = ('person', 'bicycle', '...