new dataset

.idea/workspace.xml

@@ -19,7 +19,9 @@
     <select />
   </component>
   <component name="ChangeListManager">
-    <list default="true" id="828778c9-9d97-422f-a727-18ddbd059b85" name="Default Changelist" comment="finding barcode">
+    <list default="true" id="828778c9-9d97-422f-a727-18ddbd059b85" name="Default Changelist" comment="po">
+      <change afterPath="$PROJECT_DIR$/coder/dataset/test.csv" afterDir="false" />
+      <change afterPath="$PROJECT_DIR$/coder/dataset/train.csv" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/coder/image.py" beforeDir="false" afterPath="$PROJECT_DIR$/coder/image.py" afterDir="false" />
     </list>
@@ -70,16 +72,17 @@
     <property name="RunOnceActivity.ShowReadmeOnStart" value="true" />
     <property name="SHARE_PROJECT_CONFIGURATION_FILES" value="true" />
     <property name="WebServerToolWindowFactoryState" value="false" />
-    <property name="last_opened_file_path" value="$PROJECT_DIR$/coder" />
+    <property name="last_opened_file_path" value="$PROJECT_DIR$/coder/dataset" />
     <property name="restartRequiresConfirmation" value="false" />
     <property name="settings.editor.selected.configurable" value="com.jetbrains.python.configuration.PyActiveSdkModuleConfigurable" />
   </component>
   <component name="RecentsManager">
     <key name="CopyFile.RECENT_KEYS">
+      <recent name="C:\Users\Pawel Lukaszewicz\PycharmProjects\AL-2020\coder\dataset" />
       <recent name="C:\Users\Pawel Lukaszewicz\PycharmProjects\AL-2020\coder" />
     </key>
   </component>
-  <component name="RunManager" selected="Python.rocognizer">
+  <component name="RunManager" selected="Python.image">
     <configuration default="true" type="PythonConfigurationType" factoryName="Python">
       <module name="wozek" />
       <option name="INTERPRETER_OPTIONS" value="" />
@@ -169,6 +172,9 @@
       <module name="wozek" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
+      <envs>
+        <env name="PYTHONUNBUFFERED" value="1" />
+      </envs>
       <option name="SDK_HOME" value="" />
       <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/coder" />
       <option name="IS_MODULE_SDK" value="true" />
@@ -188,6 +194,9 @@
       <module name="wozek" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
+      <envs>
+        <env name="PYTHONUNBUFFERED" value="1" />
+      </envs>
       <option name="SDK_HOME" value="" />
       <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/coder" />
       <option name="IS_MODULE_SDK" value="true" />
@@ -204,16 +213,16 @@
       <method v="2" />
     </configuration>
     <list>
+      <item itemvalue="Python.image" />
       <item itemvalue="Python.main" />
       <item itemvalue="Python.feature_hashing" />
       <item itemvalue="Python.train_nn" />
-      <item itemvalue="Python.load_image" />
       <item itemvalue="Python.rocognizer" />
     </list>
     <recent_temporary>
       <list>
+        <item itemvalue="Python.image" />
         <item itemvalue="Python.rocognizer" />
-        <item itemvalue="Python.load_image" />
         <item itemvalue="Python.train_nn" />
         <item itemvalue="Python.main" />
         <item itemvalue="Python.feature_hashing" />
@@ -242,7 +251,12 @@
       <workItem from="1589814601057" duration="4208000" />
       <workItem from="1589844260514" duration="777000" />
       <workItem from="1589845066174" duration="177000" />
-      <workItem from="1589888090669" duration="27074000" />
+      <workItem from="1589888090669" duration="27128000" />
+      <workItem from="1590140903263" duration="211000" />
+      <workItem from="1590179245978" duration="6655000" />
+      <workItem from="1590230578314" duration="1895000" />
+      <workItem from="1590235510565" duration="925000" />
+      <workItem from="1590340739871" duration="8052000" />
     </task>
     <task id="LOCAL-00001" summary="create Shelf">
       <created>1589815443652</created>
@@ -307,7 +321,14 @@
       <option name="project" value="LOCAL" />
       <updated>1589967955430</updated>
     </task>
-    <option name="localTasksCounter" value="10" />
+    <task id="LOCAL-00010" summary="po">
+      <created>1589972251988</created>
+      <option name="number" value="00010" />
+      <option name="presentableId" value="LOCAL-00010" />
+      <option name="project" value="LOCAL" />
+      <updated>1589972251988</updated>
+    </task>
+    <option name="localTasksCounter" value="11" />
     <servers />
   </component>
   <component name="TypeScriptGeneratedFilesManager">
@@ -336,7 +357,8 @@
     <MESSAGE value="recognizing but training must be improved" />
     <MESSAGE value="zwiekszenie dokladnosci" />
     <MESSAGE value="finding barcode" />
-    <option name="LAST_COMMIT_MESSAGE" value="finding barcode" />
+    <MESSAGE value="po" />
+    <option name="LAST_COMMIT_MESSAGE" value="po" />
   </component>
   <component name="WindowStateProjectService">
     <state x="115" y="162" key="#com.intellij.refactoring.safeDelete.UnsafeUsagesDialog" timestamp="1589923610328">
@@ -363,10 +385,10 @@
       <screen x="0" y="0" width="1536" height="824" />
     </state>
     <state x="277" y="57" key="SettingsEditor/0.0.1536.824@0.0.1536.824" timestamp="1589845139218" />
-    <state x="361" y="145" key="Vcs.Push.Dialog.v2" timestamp="1589955889829">
+    <state x="361" y="145" key="Vcs.Push.Dialog.v2" timestamp="1589972275899">
       <screen x="0" y="0" width="1536" height="824" />
     </state>
-    <state x="361" y="145" key="Vcs.Push.Dialog.v2/0.0.1536.824@0.0.1536.824" timestamp="1589955889829" />
+    <state x="361" y="145" key="Vcs.Push.Dialog.v2/0.0.1536.824@0.0.1536.824" timestamp="1589972275899" />
     <state x="54" y="145" width="672" height="678" key="search.everywhere.popup" timestamp="1589918982407">
       <screen x="0" y="0" width="1536" height="824" />
     </state>

coder/image.py

@@ -4,37 +4,55 @@ import matplotlib.pyplot as plt
 from sklearn import datasets
 from sklearn.metrics import accuracy_score
 from sklearn.neural_network import MLPClassifier
+import pandas as pd
 import cv2
 
+#28x28
+train_data = np.genfromtxt('dataset/train.csv', delimiter=',', skip_header=1 ,max_rows=20000, encoding='utf-8')
+test_data = np.genfromtxt('dataset/test.csv', delimiter=',' , skip_header=1, max_rows=20000, encoding='utf-8')
+
+
 
 # training
 # recznie napisane cyfry
-digits = datasets.load_digits()
 
+digits = datasets.load_digits()
 y = digits.target
 x = digits.images.reshape((len(digits.images), -1))
+
+
 #ogarnac zbior, zwiekszyc warstwy
 
-x_train = x[:1000000]
+x_train = train_data[0:20000, 1:]
-y_train = y[:1000000]
+y_train = train_data[0:20000, 0]
-x_test = x[1000000:]
+x_test = test_data[0:20000]
-y_test = y[1000000:]
+y_test = test_data[0:20000, 0]
 
-mlp = MLPClassifier(hidden_layer_sizes=(15,), activation='logistic', alpha=1e-4,
+# x_train = x[:900]
-                    solver='sgd', tol=1e-4, random_state=1,
+# y_train = y[:900]
-                    learning_rate_init=.1, verbose=True)
+# x_test = x[900:]
+# y_test = y[900:]
+
+print(x_test[0].shape, y_test[9].shape)
+
+mlp = MLPClassifier(hidden_layer_sizes=(100, 100, 100, 100), activation='logistic', alpha=1e-4,
+                    solver='sgd', tol=0.000000000001, random_state=1,
+                    learning_rate_init=.1, verbose=True, max_iter=1000)
 
 mlp.fit(x_train, y_train)
-
+print(123456789)
 predictions = mlp.predict(x_test)
-print(accuracy_score(y_test, predictions))
+print(123456789)
+
+print("Accuracy: ", accuracy_score(y_test, predictions))
 
 
 # image
 
-img = cv2.cvtColor(cv2.imread('test3.png'), cv2.COLOR_BGR2GRAY)
+img = cv2.cvtColor(cv2.imread('test5.jpg'), cv2.COLOR_BGR2GRAY)
 img = cv2.blur(img, (9, 9)) # poprawia jakosc
-img = cv2.resize(img, (8, 8), interpolation=cv2.INTER_AREA)
+img = cv2.resize(img, (28, 28), interpolation=cv2.INTER_AREA)
+img = img.reshape((len(img), -1))
 
 print(type(img))
 print(img.shape)
@@ -61,4 +79,3 @@ print(data)
 predictions = mlp.predict([data])
 
 print("Liczba to:", predictions[0])
-