An example of image recognition(kaggle competition:dogs vs cats)

Pytorch implementation

Preprocess

• 每张图片压缩到[0,1]（toTensor）
• 减去mean=[0.485, 0.456, 0.406]，再除以std = [0.229, 0.224, 0.225]（归一化），这是ImageNet上常用的，如果pretrain为False，可使用[0.5,0.5,0.5]

Data

• download: https://www.kaggle.com/c/dogs-vs-cats/data?select=train.zip

Result

	epochs	running time(GPU:2080Ti)	pretrain	accruay（train: 25000，test: 12500）
VGG16	20	1:17:57	True	train: 98.98% ；test(logloss): 0.12360
VGG19	20	1:26:05	True	train: 98.84% ；test(logloss): 0.11135
GoogleNet	20	3:14:35	True	train: 98.68% ；test(logloss): 0.12219
ResNet152	20	3:56:54	True	train: 99.89% ；test(logloss): 0.09463
Inception-v3	20	2:34:41	True	train: 99.92% ；test(logloss): 0.08733

• 训练评价指标使用LogLoss

Run

    cd 当前目录
    python googlenet.py