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conda ready

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shaaqu 2020-06-08 14:30:10 +02:00
parent 9b083201e8
commit d8b857bb0c
6 changed files with 30 additions and 31 deletions
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2
.idea/misc.xml
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@ -3,5 +3,5 @@
<component name="JavaScriptSettings"> <component name="JavaScriptSettings">
<option name="languageLevel" value="ES6" /> <option name="languageLevel" value="ES6" />
</component> </component>
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.7 (AL-2020)" project-jdk-type="Python SDK" /> <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (AL-2020)" project-jdk-type="Python SDK" />
</project> </project>

24
.idea/shelf/Uncommitted_changes_before_Update_at_6_8_2020_1_30_PM_[Default_Changelist]/shelved.patch Normal file
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File diff suppressed because one or more lines are too long

5
.idea/wozek.iml
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@ -4,10 +4,7 @@
<content url="file://$MODULE_DIR$"> <content url="file://$MODULE_DIR$">
<excludeFolder url="file://$MODULE_DIR$/venv" /> <excludeFolder url="file://$MODULE_DIR$/venv" />
</content> </content>
<orderEntry type="jdk" jdkName="Python 3.7 (AL-2020)" jdkType="Python SDK" /> <orderEntry type="jdk" jdkName="Python 3.8 (AL-2020)" jdkType="Python SDK" />
<orderEntry type="sourceFolder" forTests="false" /> <orderEntry type="sourceFolder" forTests="false" />
</component> </component>
<component name="TestRunnerService">
<option name="PROJECT_TEST_RUNNER" value="Unittests" />
</component>
</module> </module>

16
coder/model.py
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@ -1,21 +1,9 @@
import numpy as np
import torch import torch
import torchvision
import matplotlib.pyplot as plt
from time import time
from torchvision import datasets, transforms
from torch import nn, optim
import torch.nn.functional as F import torch.nn.functional as F
import cv2
from nn_model import Net from nn_model import Net
from torch import nn, optim
from torchvision import datasets, transforms
'''
Q:
what is batch?
'''
n_epochs = 3 n_epochs = 3
batch_size_train = 64 batch_size_train = 64
batch_size_test = 1000 batch_size_test = 1000

1
coder/nn_model.py
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@ -1,6 +1,5 @@
import torch.nn as nn import torch.nn as nn
import torch.nn.functional as F import torch.nn.functional as F
import torch.optim as optim
class Net(nn.Module): class Net(nn.Module):

13
coder/rocognizer.py
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@ -1,13 +1,7 @@
import cv2 import cv2
import matplotlib.pyplot as plt
import torch import torch
from PIL.Image import Image
from torch import nn
from torchvision.transforms import transforms
from torch.autograd import Variable
import numpy as np
from nn_model import Net from nn_model import Net
from torchvision.transforms import transforms
def recognizer(a_path): def recognizer(a_path):
@ -30,9 +24,6 @@ def recognizer(a_path):
rects = [cv2.boundingRect(ctr) for ctr in ctrs] rects = [cv2.boundingRect(ctr) for ctr in ctrs]
# load nn model # load nn model
input_size = 784 # = 28*28
hidden_sizes = [128, 128, 64]
output_size = 10
model = Net() model = Net()
model.load_state_dict(torch.load('model.pt')) model.load_state_dict(torch.load('model.pt'))
model.eval() model.eval()
@ -60,4 +51,4 @@ def recognizer(a_path):
recognizer("55555.jpg") recognizer("55555.jpg")
# print(recognizer("55555.jpg"))