najbliższe pole

.idea/workspace.xml

@@ -20,7 +20,6 @@
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_04.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_04.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_05.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_05.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_06.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_06.png" afterDir="false" />
-      <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_07.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_03_07.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_04_01.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_04_01.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_04_02.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_04_02.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_04_03.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_04_03.png" afterDir="false" />
@@ -37,7 +36,6 @@
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_07.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_07.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_08.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_08.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_09.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_09.png" afterDir="false" />
-      <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_10.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_05_10.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_06_01.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_06_01.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_06_02.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_06_02.png" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/resources/neural_network/sliced/screen_06_03.png" beforeDir="false" afterPath="$PROJECT_DIR$/resources/neural_network/sliced/screen_06_03.png" afterDir="false" />
@@ -233,6 +231,8 @@
       <workItem from="1622535418118" duration="3519000" />
       <workItem from="1622539085394" duration="24000" />
       <workItem from="1622539306453" duration="4588000" />
+      <workItem from="1622544012547" duration="1597000" />
+      <workItem from="1622545712675" duration="82000" />
     </task>
     <servers />
   </component>
@@ -254,25 +254,25 @@
     </state>
     <state x="690" y="287" key="#com.intellij.refactoring.safeDelete.UnsafeUsagesDialog/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622536049152" />
     <state x="690" y="287" key="#com.intellij.refactoring.safeDelete.UnsafeUsagesDialog/0.0.1920.1080@0.0.1920.1080" timestamp="1621429221570" />
-    <state width="1879" height="295" key="GridCell.Tab.0.bottom" timestamp="1622543931828">
+    <state width="1879" height="295" key="GridCell.Tab.0.bottom" timestamp="1622545794822">
       <screen x="0" y="0" width="1920" height="1080" />
     </state>
-    <state width="1879" height="295" key="GridCell.Tab.0.bottom/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622543931828" />
+    <state width="1879" height="295" key="GridCell.Tab.0.bottom/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622545794822" />
     <state width="1879" height="295" key="GridCell.Tab.0.bottom/0.0.1920.1080@0.0.1920.1080" timestamp="1621429389327" />
-    <state width="1879" height="295" key="GridCell.Tab.0.center" timestamp="1622543931827">
+    <state width="1879" height="295" key="GridCell.Tab.0.center" timestamp="1622545794822">
       <screen x="0" y="0" width="1920" height="1080" />
     </state>
-    <state width="1879" height="295" key="GridCell.Tab.0.center/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622543931827" />
+    <state width="1879" height="295" key="GridCell.Tab.0.center/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622545794822" />
     <state width="1879" height="295" key="GridCell.Tab.0.center/0.0.1920.1080@0.0.1920.1080" timestamp="1621429389327" />
-    <state width="1879" height="295" key="GridCell.Tab.0.left" timestamp="1622543931827">
+    <state width="1879" height="295" key="GridCell.Tab.0.left" timestamp="1622545794822">
       <screen x="0" y="0" width="1920" height="1080" />
     </state>
-    <state width="1879" height="295" key="GridCell.Tab.0.left/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622543931827" />
+    <state width="1879" height="295" key="GridCell.Tab.0.left/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622545794822" />
     <state width="1879" height="295" key="GridCell.Tab.0.left/0.0.1920.1080@0.0.1920.1080" timestamp="1621429389326" />
-    <state width="1879" height="295" key="GridCell.Tab.0.right" timestamp="1622543931827">
+    <state width="1879" height="295" key="GridCell.Tab.0.right" timestamp="1622545794822">
       <screen x="0" y="0" width="1920" height="1080" />
     </state>
-    <state width="1879" height="295" key="GridCell.Tab.0.right/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622543931827" />
+    <state width="1879" height="295" key="GridCell.Tab.0.right/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622545794822" />
     <state width="1879" height="295" key="GridCell.Tab.0.right/0.0.1920.1080@0.0.1920.1080" timestamp="1621429389327" />
     <state width="1879" height="364" key="GridCell.Tab.1.bottom" timestamp="1622538962724">
       <screen x="0" y="0" width="1920" height="1080" />
@@ -294,10 +294,10 @@
     </state>
     <state width="1879" height="364" key="GridCell.Tab.1.right/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622538962724" />
     <state width="1879" height="364" key="GridCell.Tab.1.right/0.0.1920.1080@0.0.1920.1080" timestamp="1619289752045" />
-    <state x="0" y="0" key="com.intellij.ide.util.TipDialog" timestamp="1622539085140">
+    <state x="0" y="0" key="com.intellij.ide.util.TipDialog" timestamp="1622545712780">
       <screen x="0" y="0" width="1920" height="1080" />
     </state>
-    <state x="0" y="0" key="com.intellij.ide.util.TipDialog/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622539085140" />
+    <state x="0" y="0" key="com.intellij.ide.util.TipDialog/0.0.1920.1080/-1920.0.1920.1080@0.0.1920.1080" timestamp="1622545712780" />
     <state x="0" y="0" key="com.intellij.ide.util.TipDialog/0.0.1920.1080@0.0.1920.1080" timestamp="1621439087317" />
     <state x="623" y="235" width="672" height="678" key="search.everywhere.popup" timestamp="1622494466933">
       <screen x="0" y="0" width="1920" height="1080" />
@@ -319,6 +319,6 @@
     <SUITE FILE_PATH="coverage/SmartCart$copy.coverage" NAME="copy Coverage Results" MODIFIED="1622503170538" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$" />
     <SUITE FILE_PATH="coverage/SmartCart$glue.coverage" NAME="glue Coverage Results" MODIFIED="1622501306368" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$" />
     <SUITE FILE_PATH="coverage/SmartTractor$py.coverage" NAME="py Coverage Results" MODIFIED="1622469837941" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$" />
-    <SUITE FILE_PATH="coverage/SmartCart$py.coverage" NAME="py Coverage Results" MODIFIED="1622543817734" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$" />
+    <SUITE FILE_PATH="coverage/SmartCart$py.coverage" NAME="py Coverage Results" MODIFIED="1622545719029" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$" />
   </component>
 </project>

definitions.py

@@ -54,7 +54,7 @@ FARMLAND_DRY_COST = 3
 FARMLAND_WET = pygame.image.load(os.path.join('resources/images', 'farmland_wet.png'))
 FARMLAND_WET = pygame.transform.scale(FARMLAND_WET, (BLOCK_SIZE, BLOCK_SIZE))
 FARMLAND_WET_COST = 1
-FPS = 10
+FPS = 1
 POTATOES_ADULT_COST = 4
 POTATOES_GROW_COST = 10
 POTATOES_GROW_TIME = 5

neuralnetwork.py

@@ -4,6 +4,7 @@ from torch.optim import Adam
 from torch.utils.data import DataLoader
 from torchvision.transforms import transforms
 import glob
+import graph
 import os
 import pathlib
 import torch
@@ -95,13 +96,10 @@ def create_neural_network(): #tworzenie sieci neuronowej
         model.load_state_dict(checkpoint)
         model.eval()
     return classes, model
-def predfield(cart_direction, cart_x, cart_y, classes, model): #zwraca najbliższe miejsce pola z wyrośniętą rośliną na podstawie wykrywania obrazu
+def predfield(classes, istate, model): #zwraca najbliższe miejsce pola z wyrośniętą rośliną na podstawie wykrywania obrazu
     pred_path = os.path.join('resources/neural_network/sliced/') #ścieżka do obrazków do sprawdzenia
     pred_dict = {}
     images_path = glob.glob(pred_path + '/*.png')
-    cart_x = int(cart_x) #x'owa wózka
-    cart_y = int(cart_y) #y'owa wózka
-    additional_rotate_moves = 0
     x = None #x'owa pola
     y = None #y'kowa  pola
     min = None
@@ -122,7 +120,8 @@ def predfield(cart_direction, cart_x, cart_y, classes, model): #zwraca najbliżs
                     y = 9
                 else:
                     y = y - 1
-                min = abs(cart_x - x) + abs(cart_y - y) + additional_rotate_moves
+                min = len((graph.graphsearch([], [], (x, y), istate, graph.succ)))
+                print(min)
             else:
                 temp_x = img_name[18]
                 temp_y = img_name[15]
@@ -136,15 +135,13 @@ def predfield(cart_direction, cart_x, cart_y, classes, model): #zwraca najbliżs
                     temp_y = 9
                 else:
                     temp_y = temp_y - 1
-                if abs(cart_x - temp_x) + abs(cart_y - temp_y) + additional_rotate_moves < min:
+                if len((graph.graphsearch([], [], (temp_x, temp_y), istate, graph.succ))) < min:
+                    min = len((graph.graphsearch([], [], (temp_x, temp_y), istate, graph.succ)))
                     x = temp_x
                     y = temp_y
-                    min = abs(cart_x - x) + abs(cart_y - y) + additional_rotate_moves
-    if x == None and y == None: #jeżeli nie ma wyrośniętej rośliny to zwróć False
+    if x == None and y == None: #jeżeli nie ma wyrośniętej rośliny to zwróć fałsz
         return False
     else:
-        print(x, y)
-        print(min)
         return x, y
 def prediction1(classes, img_path, model, transformer): #zwraca predykcję dla danego obrazka
     image = Image.open(img_path).convert('RGB')

py.py

@@ -38,11 +38,11 @@ def main():
             pygame.image.save(pygame.display.get_surface(), os.path.join('resources/neural_network/sliced/', 'screen.jpg')) #zrzut obecnego ekranu
             image_slicer.slice(os.path.join('resources/neural_network/sliced/', 'screen.jpg'), 100) #pocięcie ekranu na sto części
             os.remove('resources/neural_network/sliced/screen.jpg')
-            if neuralnetwork.predfield(cart1.get_direction(), cart1.get_x() / definitions.BLOCK_SIZE, cart1.get_y() / definitions.BLOCK_SIZE, classes, model) is not False: #jeżeli istnieje jakaś dojrzała roślina
-                random_movement = False
             istate = graph.Istate(cart1.get_direction(), cart1.get_x() / definitions.BLOCK_SIZE, cart1.get_y() / definitions.BLOCK_SIZE) #stan początkowy wózka (jego orientacja oraz jego aktualne miejsce)
+            if neuralnetwork.predfield(classes, istate, model) is not False: #jeżeli istnieje jakaś dojrzała roślina
+                random_movement = False
                 if decision == [0]: #jeżeli decyzja jest 0 (brak powrotu do stacji) to uprawiaj pole
-                    move_list = (astar.graphsearch([], astar.f, [], neuralnetwork.predfield(cart1.get_direction(), cart1.get_x() / definitions.BLOCK_SIZE, cart1.get_y() / definitions.BLOCK_SIZE, classes, model), istate, map1, graph.succ))  #lista z ruchami, które należy po kolei wykonać, astar
+                    move_list = (astar.graphsearch([], astar.f, [], neuralnetwork.predfield(classes, istate, model), istate, map1, graph.succ))  #lista z ruchami, które należy po kolei wykonać, astar
                 else:  #jeżeli decyzja jest 1 (powrót do stacji) to wróć do stacji uzupełnić zapasy
                     move_list = (graph.graphsearch([], [], (0, 0), istate, graph.succ)) #lista z ruchami, które należy po kolei wykonać, graphsearch
             else: