登录
首页 » Python » 目标检测定位算法源码

目标检测定位算法源码

于 2020-10-08 发布
0 256
下载积分: 1 下载次数: 3
我要下载

代码说明：

说明：  这个一个在目标检测中起定位作用的神经网络代码，不过这次我没有写使用教程，东西应该不难。(This is a neural network code that plays a role in target detection, but this time I did not write a tutorial, things should not be difficult.)

文件列表：

目标检测定位算法源码, 0 , 2020-10-08
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master, 0 , 2020-05-31
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\.gitignore, 1292 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_iterator_base, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_iterator_base\data_batch.py, 596 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_iterator_base\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_provider_base, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_provider_base\base_data_adapter.py, 359 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_provider_base\base_provider.py, 748 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_provider_base\pickle_provider.py, 4102 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_provider_base\text_list_adapter.py, 1694 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\data_provider_base\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\image_augmentation, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\image_augmentation\augmentor.py, 10362 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\image_augmentation\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\inference_speed_eval, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\inference_speed_eval\inference_speed_eval_with_mxnet_cudnn.py, 4230 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\inference_speed_eval\inference_speed_eval_with_tensorrt_cudnn.py, 7265 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\inference_speed_eval\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\logging_GOCD.py, 1877 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\loss_layer_farm, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\loss_layer_farm\cross_entropy_with_focal_loss_for_one_class_detection.py, 2669 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\loss_layer_farm\cross_entropy_with_hnm_for_one_class_detection.py, 3278 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\loss_layer_farm\mean_squared_error_with_hnm_for_one_class_detection.py, 2946 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\loss_layer_farm\mean_squared_error_with_ohem_for_one_class_detection.py, 1847 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\loss_layer_farm\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\README.md, 950 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\solver_GOCD.py, 7990 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\train_GOCD.py, 2208 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\ChasingTrainFramework_GeneralOneClassDetection\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\accuracy_evaluation, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\accuracy_evaluation\evaluation_on_fddb.py, 2413 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\accuracy_evaluation\evaluation_on_widerface.py, 2793 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\accuracy_evaluation\predict.py, 11095 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\configuration_10_320_20L_5scales_v2, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\configuration_10_320_20L_5scales_v2\symbol_10_320_20L_5scales_v2_deploy.prototxt, 16689 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\configuration_10_320_20L_5scales_v2\train_10_320_20L_5scales_v2_iter_1000000.caffemodel, 6092129 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\configuration_10_560_25L_8scales_v1, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\configuration_10_560_25L_8scales_v1\symbol_10_560_25L_8scales_v1_deploy.prototxt, 24297 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\configuration_10_560_25L_8scales_v1\train_10_560_25L_8scales_v1_iter_1400000.caffemodel, 9177047 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\predict_caffemodel.py, 9915 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\predict_caffemodel_v2.py, 9753 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\caffemodel\README.md, 960 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\config_farm, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\config_farm\configuration_10_320_20L_5scales_v2.py, 11676 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\config_farm\configuration_10_560_25L_8scales_v1.py, 11516 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\config_farm\__init__.py, 98 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_iterator_farm, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_iterator_farm\multithread_dataiter_for_cross_entropy_v1.py, 26241 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_iterator_farm\multithread_dataiter_for_cross_entropy_v2.py, 26206 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_iterator_farm\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_provider_farm, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_provider_farm\pickle_provider.py, 4123 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_provider_farm\reformat_voc.py, 6033 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_provider_farm\reformat_WIDERFACE.py, 6128 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\data_provider_farm\text_list_adapter.py, 1711 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\demo, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\demo\demo.py, 6442 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt, 0 , 2020-05-22
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\debug_image, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\debug_image\test1.jpg, 51437 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\debug_image\test2.jpg, 47380 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\debug_image\test3.jpg, 48246 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\debug_image\test5.jpg, 53234 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\debug_image\test6.jpg, 37664 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\predict_tensorrt.py, 13785 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\README.md, 887 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\test.py, 322 , 2020-05-22
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\deploy_tensorrt\to_onnx.py, 1281 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\inference_speed_evaluation, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\inference_speed_evaluation\inference_speed_eval.py, 1209 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\inference_speed_evaluation\README.md, 919 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\metric_farm, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\metric_farm\metric_default.py, 1800 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\metric_farm\__init__.py, 0 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\qualitative_results, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\qualitative_results\v1_qualitative_1.jpg, 286723 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\qualitative_results\v1_qualitative_2.jpg, 265694 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\qualitative_results\v1_qualitative_3.jpg, 197624 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\qualitative_results\v1_qualitative_4.jpg, 257316 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\qualitative_results\v1_qualitative_5.jpg, 166773 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\README.md, 11058 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\saved_model, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\saved_model\configuration_10_320_20L_5scales_v2, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\saved_model\configuration_10_320_20L_5scales_v2\train_10_320_20L_5scales_v2_iter_1000000.params, 6088868 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\saved_model\configuration_10_560_25L_8scales_v1, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\saved_model\configuration_10_560_25L_8scales_v1\train_10_560_25L_8scales_v1_iter_1400000.params, 9171788 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\symbol_farm, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\symbol_farm\symbol_10_320_20L_5scales_v2.py, 20809 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\symbol_farm\symbol_10_320_20L_5scales_v2_deploy.json, 42802 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\symbol_farm\symbol_10_560_25L_8scales_v1.py, 25851 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\symbol_farm\symbol_10_560_25L_8scales_v1_deploy.json, 61934 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\symbol_farm\symbol_structures.xlsx, 17888 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\face_detection\symbol_farm\__init__.py, 97 , 2020-03-28
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\head_detection, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\head_detection\accuracy_evaluation, 0 , 2020-05-19
目标检测定位算法源码\A-Light-and-Fast-Face-Detector-for-Edge-Devices-master\head_detection\accuracy_evaluation\evaluation_on_brainwash.py, 4332 , 2020-03-28

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • Labeling
    对于二值图像进行labeling,求的对象个数，每个对象的像素数，中心点，长宽高矮值等(labeling for bianry image)
    2011-05-09 13:54:15下载
    积分：1
  • CV1
    属于图像分割的一种，利用matlab实现CV型,可以当function使用。其中包含图片，可以进行使用。(It belongs to one kind of image segmentation, and uses MATLAB to realize CV type, which can be used as function.It contains pictures, which can be used.)
    2019-04-16 21:59:34下载
    积分：1
  • LMI
    实现基于四叉树分解的局部化互信息。参考文献：Image fusion performance metric based on mutual information and entropy driven quadtree decomposition(Compute the Image fusion performance metric based on mutual information and entropy driven quadtree decomposition.)
    2013-02-27 08:46:16下载
    积分：1
  • GAMP
    基于GA和MP的信号稀疏分解,算法速度比元来的有很多改进。(Based on GA and MP sparse signal decomposition, the algorithm faster than the yuan to have many improvements.)
    2008-04-10 10:44:05下载
    积分：1
  • SAR_geo_correction
    距离模型、多普勒模拟、地球模型、的雷达图像几何校正 (Radar image geometric correction)
    2011-08-03 07:56:26下载
    积分：1
  • Zernike
    亚像素边缘检测的matlab代码，比一般的边缘检测代码精确(Sub-pixel edge detection matlab code)
    2020-12-18 09:59:11下载
    积分：1
  • image-processing
    1.设计一个程序，对一幅灰度图像的实现如下几何变换,1)放大为原图1.5倍 2)绕中心旋转30度(CW) 3)采用偏移量插值实现一个透视变换. 灰度差值用最近邻插值和双线性插值 2. 绘制一幅灰度图像的梯度幅度图像（三点法求梯度），针对梯度幅度图像合理的选择一个阈值（通过试验即可）将其二值化，以获得图像边缘检测图像。 ((1) design a program, a grayscale image as geometric transformation, zoom 1) for 1.5 times the original 2) around the center of rotation of 30 degrees (CW) 3) interpolation of the offset to achieve a perspective transformation.gray level difference between the nearest neighbor interpolation and bilinear interpolation (2) draw a grayscale image of the gradient magnitude image (three-point method seeking gradient), the gradient magnitude image is reasonable to select a threshold value (the test can be) the second value to the image edge detection image.)
    2012-03-13 23:16:59下载
    积分：1
  • snake
    在MATLAB编程环境下，使用一种活动轮廓的方法实现图像分割的程序。(In the MATLAB programming environment, the use of an active contour method to achieve image segmentation procedures.)
    2008-04-14 14:46:51下载
    积分：1
  • SURF-based-image-stitching
    SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )
    2014-08-30 15:12:42下载
    积分：1
  • unmixpro
    混合像元分解，是定量遥感中非常重要的组成部分之一，在反演地表参数时是必须要考虑的因素之一，文中罗列了分解的一些方法。(mixed pixel decomposition, is the quantification of remote sensing very important component of one of the the inversion of surface parameters is to be considered one of the factors, the paper listed some of the decomposition method.)
    2013-06-21 17:07:35下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！