refactor #26
12
Tractor.py
12
Tractor.py
@ -15,6 +15,7 @@ condition=Condition.Condition()
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drzewo=Drzewo.Drzewo()
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format_string = "{:<25}{:<25}{:<25}{:<10}{:<10}{:<10}{:<25}{:<15}{:<20}{:<10}{:<15}"
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format_string_nn="{:<10}{:<20}{:<20}{:<15}{:<20}"
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tab = [-1, 0, 0, 0, 0, 1, 1, 1, 1, 1,
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@ -193,6 +194,8 @@ class Tractor:
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print("podlanych slotów: ", str(counter))
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def snake_move_predict_plant(self, pole, model):
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headers=['Coords','Real plant','Predicted plant','Result','Fertilizer']
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print(format_string_nn.format(*headers))
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initPos = (self.slot.x_axis, self.slot.y_axis)
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count = 0
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for i in range(initPos[1], dCon.NUM_Y):
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@ -203,11 +206,8 @@ class Tractor:
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if self.slot.imagePath != None:
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predictedLabel = nn.predictLabel(self.slot.imagePath, model)
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# print(str("Coords: ({:02d}, {:02d})").format(self.slot.x_axis, self.slot.y_axis), "real:", self.slot.label, "predicted:", predictedLabel, "correct" if (self.slot.label == predictedLabel) else "incorrect", 'nawożę za pomocą:', nn.fertilizer[predictedLabel])
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if str(self.slot.label) != str(predictedLabel):
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print(str("Coords: ({:02d}, {:02d})").format(self.slot.x_axis, self.slot.y_axis))
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print("real: ", str(self.slot.label), "\tpredicted: ", str(predictedLabel), "\n")
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#print(str("Coords: ({:02d}, {:02d})").format(self.slot.x_axis, self.slot.y_axis), "real:", self.slot.label, "predicted:", predictedLabel, "correct" if (self.slot.label == predictedLabel) else "incorrect", 'nawożę za pomocą:', nn.fertilizer[predictedLabel])
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print(format_string_nn.format(f"{self.slot.x_axis,self.slot.y_axis}",self.slot.label,predictedLabel,"correct" if (self.slot.label == predictedLabel) else "incorrect",nn.fertilizer[predictedLabel]))
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if self.slot.label != predictedLabel:
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self.slot.mark_visited()
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count += 1
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@ -220,7 +220,7 @@ class Tractor:
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self.turn_left()
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self.move_forward(pole, False)
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self.turn_left()
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print(f"źle nawiezionych roślin: {count}")
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print(f"Dobrze nawiezionych roślin: {20*12-count}, źle nawiezionych roślin: {count}")
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def snake_move(self,pole,x,y):
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next_slot_coordinates=(x,y)
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@ -10,7 +10,7 @@ import random
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imageSize = (128, 128)
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labels = ['carrot','corn', 'potato', 'tomato'] # musi być w kolejności alfabetycznej
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fertilizer = {labels[0]: 'kompost', labels[1]: 'saletra amonowa', labels[2]: 'superfosfat'}
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fertilizer = {labels[0]: 'kompost', labels[1]: 'saletra amonowa', labels[2]: 'superfosfat', labels[3]:'obornik kurzy'}
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torch.manual_seed(42)
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@ -59,7 +59,7 @@ def accuracy(model, dataset):
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return correct.float() / len(dataset)
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def getModel():
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hidden_size = 300
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hidden_size = 500
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model = nn.Sequential(
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nn.Linear(imageSize[0] * imageSize[1] * 3, hidden_size),
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nn.ReLU(),
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