sys.path.append("../..")print(sys.path)#from utils import label_map_util#from utils import visualization_utils as vis_utilfromresearch.object_detection.utilsimportlabel_map_utilfromresearch.object_detection.utilsimportvisualization_utils as vis_util#What model to download.MODEL_NAME ='ssd_mobilene...
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(...
2.pretrained_model中存放的是从GitHub上下载解压的ssd_mobilenet_v1_coco_2018_01_28文件中的内容,下载网址: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md 3.train与test分别存放训练与检测的图片与XML文件; 4.training中存放从object_detection文件夹...
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_...
(还是写一下吧,找到对应python环境。例如前面创建的python是tensorflowAPI ,那就找到anaconda的安装路径,envs文件夹,进入tensorflowAPI\Lib\site-packages,将前面的object_detection文件夹复制进去) 测试环境 python object_detection/builders/model_builder_test.py ...
Step 5 : I trained Single Shot Detector — MobileNet — v1 COCO model with my products dataset. Step6: use tf_od.py and tf_oc.py for detection and counting 0 实验结果: 项目二:Use Tensorflow Object Detection API in google colab 项目思想: 如何配置基于google colab环境下的对象检测模型,同时...
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.python.framework.errors_impl.NotFoundError: Unsuccessful TensorSliceReader constructor: Failed to find any matching files for ???/model.ckpt model.ckpt这个文件似乎只在.config文件中见到: 如在object_detection/samples/configs/ssd_mobilenet_v2_coco.config中有: ...
python object_detection/builders/model_builder_tf2_test.py ``` ## 4. 其他常用命令 ```python # 删除虚拟环境: conda remove --name tensorflow --all # 创建虚拟环境: conda create -n tensorflow pip python=3.9 # 清理缓存文件: conda clean --all ...
可以开始训练啦。用object_detection目录下的model_main.py文件进行训练,option写上各种自己的地址就可以啦! python model_main.py --pipeline_config_path=data\ssd_mobilenet_v1_coco.config --model_dir=data\training --num_train_steps=30000 大概就是这样,回车!