基于卷积神经网络的食物图像识别

[{"title":"（ 32 个子文件 17.28MB ） 基于卷积神经网络的食物图像识别","children":[{"title":"Dish_CNN","children":[{"title":"test_two","children":[{"title":"input_data.py <span style='color:#111;'> 5.57KB </span>","children":null,"spread":false},{"title":"dog_train.tfrecords <span style='color:#111;'> 8.26MB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"input_data.cpython-36.pyc <span style='color:#111;'> 2.82KB </span>","children":null,"spread":false},{"title":"__init__.cpython-36.pyc <span style='color:#111;'> 128B </span>","children":null,"spread":false},{"title":"model.cpython-36.pyc <span style='color:#111;'> 2.80KB </span>","children":null,"spread":false}],"spread":true},{"title":"result.py <span style='color:#111;'> 5.46KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":".pytest_cache","children":[{"title":"CACHEDIR.TAG <span style='color:#111;'> 194B </span>","children":null,"spread":false},{"title":"v","children":[{"title":"cache","children":[{"title":"lastfailed <span style='color:#111;'> 2B </span>","children":null,"spread":false},{"title":"nodeids <span style='color:#111;'> 2B </span>","children":null,"spread":false},{"title":"stepwise <span style='color:#111;'> 2B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":".gitignore <span style='color:#111;'> 37B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 303B </span>","children":null,"spread":false}],"spread":true},{"title":"model.py <span style='color:#111;'> 6.64KB </span>","children":null,"spread":false},{"title":"image_transf.py <span style='color:#111;'> 3.42KB </span>","children":null,"spread":false},{"title":"test_result.py <span style='color:#111;'> 2.98KB </span>","children":null,"spread":false},{"title":"train_model.py <span style='color:#111;'> 3.16KB </span>","children":null,"spread":false}],"spread":true},{"title":".idea","children":[{"title":"misc.xml <span style='color:#111;'> 298B </span>","children":null,"spread":false},{"title":"modules.xml <span style='color:#111;'> 275B </span>","children":null,"spread":false},{"title":"workspace.xml <span style='color:#111;'> 27.81KB </span>","children":null,"spread":false},{"title":"Dish_CNN.iml <span style='color:#111;'> 464B </span>","children":null,"spread":false}],"spread":true},{"title":"test_mnist","children":[{"title":"test1.py <span style='color:#111;'> 4.11KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 12.41KB </span>","children":null,"spread":false},{"title":".pytest_cache","children":[{"title":"CACHEDIR.TAG <span style='color:#111;'> 194B </span>","children":null,"spread":false},{"title":"v","children":[{"title":"cache","children":[{"title":"nodeids <span style='color:#111;'> 2B </span>","children":null,"spread":false},{"title":"stepwise <span style='color:#111;'> 2B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":".gitignore <span style='color:#111;'> 37B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 303B </span>","children":null,"spread":false}],"spread":true},{"title":"MNIST_data","children":[{"title":"input_data.py <span style='color:#111;'> 335B </span>","children":null,"spread":false},{"title":"convolutional.py <span style='color:#111;'> 1.55KB </span>","children":null,"spread":false},{"title":"train-images-idx3-ubyte.gz <span style='color:#111;'> 9.45MB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 1.59KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}],"spread":true}]