你可以在TensorFlow 2 对象检测model zoo中(https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf2_detection_zoo.md)找到 Tensorflow 2 的所有可用模型的列表。 模型的基础(https://github.com/tensorflow/mod
一、在Model Zoo下载需要测试的模型,这里选择的SSD MobileNet V2 FPNLite 320x320 https:///tensorflow/models/blob/master/research/object_detection/g3doc/tf2_detection_zoo.md 下载后解压,可以看到有如些这些文件(这里后放到D:\TensorFlow\Test\model文件夹下) 二、在Object Detection API安装目录找到pbtxt配置文...
# Models can bee found here: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md MODEL_NAME = 'ssd_inception_v2_coco_2017_11_17' MODEL_FILE = MODEL_NAME + '.tar.gz' DOWNLOAD_BASE = 'http://download.tensorflow.org/models/object_detectio...
research In TensorFlow Object Detection, fixed the order of the arguments when… Mar 6, 2025 tensorflow_models No public description May 29, 2025 .gitignore Update .gitignore Apr 27, 2020 AUTHORS Spatial Transformer model Apr 2, 2016
tar zxf ssd_mobilenet_v1_coco_11_06_2017.tar.gz 1. 2. 3. 4. 5. 另外可到https:///tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md下载预训练模型,将上边命令中的模型名更换一下即可
由于object_detection需要的输入格式是TFRecord, 所以我们必须把原图.jpg 和 LabelImg生成的.xml 先转换成 .csv 最后再转成 .record。 具体需要通过两个脚本: #xml2csv.pyimportosimportglobimportpandas as pdimportxml.etree.ElementTree as ET os.chdir('/home/zzf/tensorflow/models/research/object_detection/im...
3.2.2 预训练模型的文件构成 TensorFlow detection model zoo中预训练模型的文件组成基本一致,以ssd_inception_v2_coco为例,请下载ssd_inception_v2_coco,解压后请把文件夹名也改为ssd_inception_v2_coco,可以得到如图3-4所示的多个文件。 图3-4 预训练模型文件 ...
[detection model zoo](https://github.com/tensorflow/models/blob/master/object_detection/g3doc/detection_model_zoo.md) for a list of other models that can be run out-of-the-box with varying speeds and accuracies.# In[4]:# What model to download.#此处修改模型路径#模型地址:https://...
（想要了解更多跟模型有关的知识https://github.com/tensorflow/models/blob/477ed41e7e4e8a8443bc633846eb01e2182dc68a/object_detection/g3doc/detection_model_zoo.md）实测时间 我决定使用最轻量级的模型（ssd_mobilenet）。主要步骤如下：1. 下载一个打包模型(.pb-protobuf)并把它载入缓存 2. 使用内置的辅助...
classModel:"""Class that contains the model and all its functions """def__init__(self, model_path):""" Initialization function @ model_path : path to the model """# Declare detection graph self.detection_graph = tf.Graph() # Load the model into the tensorflow graph...