# 导入库importosimportcv2importrandomimportnumpyasnpimporttensorflowastffromsklearn.model_selectionimporttrain_test_splitfromtensorflow.kerasimportlayers,models,utils,applicationsimportnumpyasnpfromsklearn.metricsimportclassification_report,confusion_matrix,roc_curve,roc_auc_scoreimportmatplotlib.pyplotaspltfromtenso...
import os import matplotlib.pyplotaspltfromkeras.preprocessing.image importImageDataGeneratorfromkeras.models importSequentialfromkeras.layers import Conv2D,MaxPool2D,Flatten,Dense,Dropouttrain_set_base_dir='G:/dataset/kaggle_dogs_and_cats/subset/train_set/'validation_set_base_dir='G:/dataset/kaggle_d...
Kaggle: Dogs vs Cats Kernel Redux Edition This repository consists a solution for theCats vs Dogs classification challengeon Kaggle. This solution scored a logloss of0.04973(#60/ 1314 teams). Top score was0.03303 (#1). This repository also contains links to my best and second best CNN models...
Dogs vs. Cats is a competition on Kaggle, which needs to write an algorithm to classify whether images contain either a dog or a cat. The training archive contains 25,000 images of dogs and cats. The Asirra data set Web services are often protected with a challenge that's supposed to ...
如果想用最新的FastAI v1.0来跑可以参看 Image classification with FastAI1.0.x, Colab and Python3(Dogs&Cats) 参考: https://forums.fast.ai/t/google-colab-fastai-setup/27167 扫码后在手机中选择通过第三方浏览器下载
Datasets and Inputs此数据集可以从 kaggle 上下载。Dogs vs. Cats Redux: Kernels Edition下载kaggle 猫狗数据集解压后分为 3 个文件 train.zip、 test.zip 和 sample_submission.csv。train 训练集包含了 25000 张猫狗的图片,猫狗各一半,每张图片包含图片本身和图片名。命名规则根据 “type.num.jpg” 方式...
microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_5340....
microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_5340....
使用深度学习方法识别一张图片是猫还是狗。. Contribute to rongmax-gufei/udacity-mlnd-dogs-vs-cats development by creating an account on GitHub.
dataset_name = 'cats_vs_dogs' dataset, info = tfds.load(name=dataset_name, split=tfds.Split.TRAIN, with_info=True) for i in dataset: print(i) Expected behavior I except to be able to iterate over all the images without getting errors and without it taking forever to complete a single...