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conda ready

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This commit is contained in:
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">
<option name="languageLevel" value="ES6" />
</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>

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://$MODULE_DIR$">
<excludeFolder url="file://$MODULE_DIR$/venv" />
</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" />
</component>
<component name="TestRunnerService">
<option name="PROJECT_TEST_RUNNER" value="Unittests" />
</component>
</module>

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

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