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Previous episode: Color planet image generation 2: using both traditional Gan discriminator and Markov discriminator (pytorch version) Based on the previous set of code, some detailed modifications are made to improve the generation effect. 1. Modification 1.1 preprocessing scaling The code for preprocessing training set pictures is mod ...

Time: 2021 / 08 / 29 / 05:45:28 It's been a night. I can't believe I'm not sleepy and have the impulse to organize my blog. Just this week, the ability to stay up late suddenly broke through in the absence of a home for several nights. After one night, there is a world of difference. I can stay up night by night. Before, I was worried about my ...

brief introduction   with the gradual deepening of research, I learned that loading the pytorch training model with libtorch is actually a very tortuous method. It can indeed meet our needs, but it may not be the best method. Now the more common model format is ONNX model, so I wonder if I can use this general model to solve the problem? ...

The three neural networks described above are "series", just the continuous stacking of convolution layers, and the structure is relatively simple. The next two blogs will introduce the "parallel" structure in GoogLeNet and ResNet, which are also the last two neural networks to be introduced before officially entering the ta ...

1, Installing Anaconda3 1.Anaconda3 Download Download link on the official website: https://www.anaconda.com/products/individual If the download speed of the official website is too slow, you can download the baidu cloud Anaconda file I uploaded Baidu cloud link: https://pan.baidu.com/s/1SK_Hc9tZ5iIXgq_tshbu_Q Extraction code: 8856 ...

PyTorch learning -- handwritten numeral recognition    MNIST dataset, which contains 70000 28 × 28 handwritten numeral data set, which is divided into 60000 training samples and 10000 test samples. Ⅰ. data reader import torch from torch import nn from torch import optim from torch.nn.parameter import Parameter import ...

1, Image augmentation Definition & Interpretation: By making a series of random changes to the training image, similar but different training samples are generated, so as to expand the scale of the training data set.Randomly changing the training samples can reduce the dependence of the model on some attributes, so as to improve the g ...

In view of the failure of many tutorials on training my data sets with yolov3 algorithm on the network, I decided to write one myself. Train in the latest version of pytorch. First, we should prepare our own data sets (that is, pictures), and then use our annotation tools to annotate them 1. Labeling tool (labelimg) Labelimg is an open sourc ...

Learning video source: link. Course summary Question: how to find the optimal value of weight As shown in the following figure, assuming that the initial value of W is the position of the red dot, how can we update w to approach the minimum value of the loss function The update algorithm is: Algorithm explanation: when the partial derivativ ...

Deep learning Basic knowledge and various network structures preface It is very important to learn a good framework for in-depth learning. Now the mainstream is pytoch and tf. Let's learn pytoch together today ! [insert picture description here]( https://img-blog.csdnimg.cn/25238d12cb8641b8bc38171559ab41e9.jpg#pic_center) 1, Basi ...