From 410e463235e24542e8388c3f3ea0e98245b24a57 Mon Sep 17 00:00:00 2001
From: piowyg <piowyg@st.amu.edu.pl>
Date: Sun, 30 May 2021 17:10:39 +0200
Subject: [PATCH] roman pls help us

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diff --git a/images/learning/bomb163.jpg b/images/learning/bomb163.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..f13afa2ead0dcbdb9fc41440110fadbb69bb9c6c
GIT binary patch
literal 2006
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literal 0
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diff --git a/images/learning/bomb164.jpg b/images/learning/bomb164.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..a06917f9be70c8506edef48c93b449ece77a203c
GIT binary patch
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literal 0
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diff --git a/images/learning/bomb165.jpg b/images/learning/bomb165.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..5de583b145226047896cb77a21400f3a04b37f4e
GIT binary patch
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literal 0
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diff --git a/images/learning/bomb166.jpg b/images/learning/bomb166.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..59def2d20ede279dc3e819377ce8eb0df74e436b
GIT binary patch
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diff --git a/images/learning/bomb228.jpg b/images/learning/bomb228.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..6fb0b5367e1a87b6656806b5867e41088a2e283b
GIT binary patch
literal 1927
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diff --git a/images/learning/bomb229.jpg b/images/learning/bomb229.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..ed0643163a310b9ee877e72a6ea569e7a3cd590c
GIT binary patch
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diff --git a/images/learning/bomb23.jpg b/images/learning/bomb23.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..5486ec5495c07707d838c3f7fa4e482b224a3044
GIT binary patch
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diff --git a/images/learning/bomb230.jpg b/images/learning/bomb230.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..ad0e0392a495dbe9ae5d19f3dd0f3df0e4815e96
GIT binary patch
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diff --git a/images/learning/bomb763.jpg b/images/learning/bomb763.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..b4e20597b93283461878e500d5f26e7983143a0f
GIT binary patch
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diff --git a/images/learning/bomb764.jpg b/images/learning/bomb764.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..6578bbf14b6fb0d1d65fe231b3fa414a1c3c864a
GIT binary patch
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diff --git a/images/learning/bomb765.jpg b/images/learning/bomb765.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..0ec158584893f37777ac06893912b3f96d6a06e1
GIT binary patch
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diff --git a/images/learning/bomb766.jpg b/images/learning/bomb766.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..ccf5bc0a60ad8e9ba3b1c2594f919dcbafc830d8
GIT binary patch
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diff --git a/images/learning/other125.jpg b/images/learning/other125.jpg
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diff --git a/images/learning/other126.jpg b/images/learning/other126.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..a8674cf1e9292977027d6334f07fc9cfa3176d4e
GIT binary patch
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diff --git a/images/learning/other127.jpg b/images/learning/other127.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..b51da527d6d63714a624d3a4043437abf82c92a4
GIT binary patch
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diff --git a/images/learning/other128.jpg b/images/learning/other128.jpg
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index 0000000000000000000000000000000000000000..134720c4cd09dc1d49728bc9efb99623bf6168b9
GIT binary patch
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diff --git a/images/learning/other129.jpg b/images/learning/other129.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..0781a02095bfe27e574fb18adbcf84ae57cd34fb
GIT binary patch
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diff --git a/images/learning/other139.jpg b/images/learning/other139.jpg
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GIT binary patch
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diff --git a/images/learning/other14.jpg b/images/learning/other14.jpg
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index 0000000000000000000000000000000000000000..fcbaed54dc49d0ce6fd413c155d0a9c9ed07e640
GIT binary patch
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diff --git a/images/learning/other140.jpg b/images/learning/other140.jpg
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GIT binary patch
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diff --git a/images/learning/other141.jpg b/images/learning/other141.jpg
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GIT binary patch
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diff --git a/images/learning/other142.jpg b/images/learning/other142.jpg
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GIT binary patch
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GIT binary patch
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GIT binary patch
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GIT binary patch
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diff --git a/src/machine_learning/neural_network/changingNameOfFiles.py b/src/machine_learning/neural_network/changingNameOfFiles.py
new file mode 100644
index 0000000..bc861ab
--- /dev/null
+++ b/src/machine_learning/neural_network/changingNameOfFiles.py
@@ -0,0 +1,68 @@
+import os
+import csv
+from PIL import Image
+import cv2
+
+IMG_SIZE = 28
+CATEGORIES = ["bomby", "other"]
+
+temp_path = os.path.abspath('../../..')
+DIR = 'images\learning'
+DIR = os.path.join(temp_path, DIR)
+
+name_bomb = 'bomb'
+name_other = 'other'
+
+def create_training_labels():
+    with open('annotations.csv', 'a', newline='') as fd:
+        for category in CATEGORIES:
+            path = os.path.join(DIR, category)
+            category_index = CATEGORIES.index(category)
+            for img in os.listdir(path):
+                try:
+                    if category_index == 0:
+                        writer = csv.writer(fd)
+                        writer.writerow([img,0])
+                    else:
+                        writer = csv.writer(fd)
+                        writer.writerow([img, 1])
+                except Exception as e:
+                    print(e)
+
+
+def change_training_data():
+    with open ('annotations.csv', 'a', newline='') as fd:
+        for category in CATEGORIES:
+            path = os.path.join(DIR, category)
+            category_index = CATEGORIES.index(category)
+            i = 0
+            for img in os.listdir(path):
+                try:
+                    if category_index == 0:
+                        name_bomb2 = name_bomb + str(i) + '.jpg'
+                        os.rename(os.path.join(path, img),os.path.join(path, name_bomb2))
+                    else:
+                        name_other2 = name_other + str(i) + '.jpg'
+                        os.rename(os.path.join(path, img), os.path.join(path, name_other2))
+                except Exception as e:
+                    print(e)
+def resize_images():
+    for item in os.listdir(DIR):
+        print(item)
+        im = Image.open(f'{DIR}/{item}')
+        if im.mode != 'RGB':
+            im = im.convert ('RGB')
+        #f, e = os.path.splitext (item)
+        imResize = im.resize((28, 28), Image.ANTIALIAS)
+        imResize.save(f'{DIR}/{item}', quality=100)
+
+if __name__ == '__main__':
+    #change_training_data()
+    #create_training_labels()
+    # temp_path = os.path.abspath('annotations.csv')
+    # #DIR = 'annotations.csv'
+    # #DIR = os.path.join(temp_path, DIR)
+    # print(temp_path)
+    #print(DIR)
+    resize_images()
+    
\ No newline at end of file
diff --git a/src/machine_learning/neural_network/learning.py b/src/machine_learning/neural_network/learning.py
index 9b4fdf4..4e21d0c 100644
--- a/src/machine_learning/neural_network/learning.py
+++ b/src/machine_learning/neural_network/learning.py
@@ -1,26 +1,36 @@
 import torch
 import torch.nn as nn
-from torch.utils.data import DataLoader
+from torch.utils.data import DataLoader, random_split
 
 from net import NeuralNetwork
 from database import create_training_data
 from Dataset import ImageDataset
+import os
+
+temp_path = os.path.abspath('../../..')
+DIR = 'images\learning'
+
+img_dir = os.path.join(temp_path, DIR)
+annonation_file = os.path.abspath('annotations.csv')
 
 
-training_data = create_training_data()
-# dataset = ImageDataset(annonation_file, img_dir)
-# trainset, valset = random_split(dataset, [15593, 3898])
+# training_data = create_training_data()
+
+dataset = ImageDataset(annonation_file, img_dir)
+
+print(len(dataset))
+trainset, testset = random_split(dataset, [1031, 200])
 
 batch_size = 64
 
 # Create data loaders.
-train_dataloader = DataLoader(training_data, batch_size=batch_size, shuffle=True)
-# test_dataloader = DataLoader(test_data, batch_size=batch_size)
+train_dataloader = DataLoader(trainset, batch_size=batch_size, shuffle=True)
+test_dataloader = DataLoader(testset, batch_size=batch_size, shuffle=True)
 
-# for X, y in test_dataloader:
-#     print("Shape of X [N, C, H, W]: ", X.shape)
-#     print("Shape of y: ", y.shape, y.dtype)
-#     break
+for X, y in test_dataloader:
+    print("Shape of X [N, C, H, W]: ", X.shape)
+    print("Shape of y: ", y.shape, y.dtype)
+    break
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 print("Using {} device".format(device))