在步骤3.5执行完以后,我们cd到builders目录下,然后执行python model_builder_test.py 如果出现下面的结果,则表示安装成功。 然后我们退回object_detection目录下,然后输入jupyter notebook 在出现的网页界面中,点击object_detection_tutorial.ipynb,然后该代码会从object_detection目录下的test文件夹下读取官方图片进行测试,最...
from object_detection.utils import visualization_utils as vis_util config = tf.compat.v1.ConfigProto(gpu_options=tf.compat.v1.GPUOptions(allow_growth=True)) sess = tf.compat.v1.Session(config=config) model_c=tf.saved_model.load('saved_model') #加载模型 for i in range(1,8): #导入并...
from object_detection.utils import label_map_util, config_util from object_detection.utils import visualization_utils as viz_utils from object_detection.builders import model_builder PATH_TO_CFG = PATH_TO_MODEL_DIR + '/pipeline.config' PATH_TO_CKPT = PATH_TO_MODEL_DIR + '/checkpoint' print(...
(10)以上安装完了就大功告成了,可通过执行测试指令: python object_detection/builders/model_builder_tf2_test.py 测试。显示如下结果,说明安装成功。 二、使用 TensorFlow Object Detection API 进行图像目标检测。 代码思路: 代码: 1#载入套件2importos3importpathlib4importtensorflow as tf5importcv26fromosimport...
打开object_detection\g3doc\tf2_classification_zoo.md,里面是用相应数据集训练好的模型(有附下载链接),可直接在上面做迁移训练。 如果已经下载或有训练好的模型,直接使用model=tf.saved_model.load加载即可(这个函数在tf1中就比较麻烦了) ②模型的输入输出(可略过) ...
在网上找了相关教程,设置好了数据集,下载好了训练模型,数据也都存放好了,config文件中的路径和num_classes参数也改好了,但是一运行model_main.py就出现了下面的警告:WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.WARNING:tensorflow:Expected number of evaluation epochs is 1, bu...
拷贝models/research/object_detection/model_main_tf2.py到training_demo目录 root@cc58e655b170:/home/zhou/tensorflow/workspace/training_demo# cp ../../models/research/object_detection/model_main_tf2.py . root@cc58e655b170:/home/zhou/tensorflow/workspace/training_demo# ls README.md annotations expor...
打开object detection api 地址:https://github.com/tensorflow/models/tree/master/research/object_detection,在reademe中找到Tensorflow detection model zoo,进去之后可以看到有基于COCO数据集、Kitti数据集、Open Images数据集等训练出来的预训练模型,我们选择faster_rcnn_inception_resnet_v2_atrous_coco,然后下载到本...
Tensorflow Object Detection API框架 基于tensorflow框架构建的快速对象检测模型构建、训练、部署框架,是针对计算机视觉领域对象检测任务的深度学习框架。之前tensorflow2.x一直不支持该框架,最近Tensorflow Object Detection API框架最近更新了,同时支持tensorflow1.x与tensorflow2.x。其中model zoo方面,tensorflow1.x基于COCO数...
1.1."train.py"文件在/object_detection/legacy当中,把它放入到/object_detection中, 在路径\object_detection下输入指令: (object_dection) E:\4work\8python\1study\object_detection\object-detection-model\research\object_detection>python train.py --logtostderr --train_dir=training/ --pipeline_config_...