mirror of
https://github.com/SilverComet7/yolov5-DNF.git
synced 2026-05-07 06:15:43 +08:00
44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
import cv2 as cv
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import os
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import shutil
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# 将标注好的图像和标签转移到新路径下
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root_path = "datasets/guiqi/patch1"
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yolo5_data_dir = "datasets/guiqi/patch1_yolo5"
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json_list = []
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imgs_list = []
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dir = os.listdir(root_path)
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for d in dir:
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if d.endswith(".json"):
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imgs_list.append(d.strip().split(".")[0] + ".jpg")
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json_list.append(d)
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print(imgs_list)
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print(json_list)
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for img_name, json in zip(imgs_list, json_list):
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shutil.copy(os.path.join(root_path + "/" + img_name), os.path.join(yolo5_data_dir + '/imgs'))
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shutil.copy(os.path.join(root_path + "/" + json), os.path.join(yolo5_data_dir + '/labels_json'))
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# # 选一部分数据作为验证集
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# img_train_path = r"F:\Computer_vision\yolov5\YOLO5\DNF\train\images"
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# img_valid_path = r"F:\Computer_vision\yolov5\YOLO5\DNF\valid\images"
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# label_train_path = r"F:\Computer_vision\yolov5\YOLO5\DNF\train\labels"
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# label_valid_path = r"F:\Computer_vision\yolov5\YOLO5\DNF\valid\labels"
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# eval_ratio = 0.1
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# dir = os.listdir(img_train_path)
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# eval_nums = int(eval_ratio * len(dir))
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# import random
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# random.shuffle(dir)
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# for d in dir[:eval_nums]:
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# shutil.move(os.path.join(img_train_path + "\\" + d), os.path.join(img_valid_path + "\\" + d))
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# shutil.move(os.path.join(label_train_path + "\\" + d.strip().split(".")[0] + ".txt"),
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# os.path.join(label_valid_path + "\\" + d.strip().split(".")[0] + ".txt"))
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# undict生成
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#
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# name2id = {'hero': 0, 'small_map': 1, "monster": 2, 'money': 3, 'material': 4, 'door': 5, 'BOSS': 6, 'box': 7, 'options': 8}
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# id2name = {}
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# for key, val in name2id.items():
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# id2name[val] = key
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# print(id2name) |