Model generated + tests screenshots #31
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assets/neural_network_tests_screenshots/1-3.png
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assets/neural_network_tests_screenshots/19-21.png
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assets/neural_network_tests_screenshots/29-31.png
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12
main.py
@ -135,15 +135,15 @@ def recognize_plants(plants_array, fields_for_astar, fields_for_movement, agent)
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if b == 0:
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for j in range(11):
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if plants_array[j][i] == 'carrot':
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img = 'assets/learning/test/carrot/' + str(random.randint(1, 25)) + '.jpg'
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img = 'assets/learning/test/carrot/' + str(random.randint(1, 200)) + '.jpg'
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pred = neural_network.prediction(img, model)
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show_plant_img(img)
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elif plants_array[j][i] == 'potato':
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img = 'assets/learning/test/potato/' + str(random.randint(1, 25)) + '.jpg'
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img = 'assets/learning/test/potato/' + str(random.randint(1, 200)) + '.jpg'
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pred = neural_network.prediction(img, model)
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show_plant_img(img)
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elif plants_array[j][i] == 'wheat':
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img = 'assets/learning/test/wheat/' + str(random.randint(1, 25)) + '.jpg'
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img = 'assets/learning/test/wheat/' + str(random.randint(1, 200)) + '.jpg'
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pred = neural_network.prediction(img, model)
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show_plant_img(img)
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else:
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@ -156,15 +156,15 @@ def recognize_plants(plants_array, fields_for_astar, fields_for_movement, agent)
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else:
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for j in range(10,-1,-1):
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if plants_array[j][i] == 'carrot':
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img = 'assets/learning/test/carrot/' + str(random.randint(1, 25)) + '.jpg'
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img = 'assets/learning/test/carrot/' + str(random.randint(1, 200)) + '.jpg'
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pred = neural_network.prediction(img, model)
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show_plant_img(img)
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elif plants_array[j][i] == 'potato':
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img = 'assets/learning/test/potato/' + str(random.randint(1, 25)) + '.jpg'
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img = 'assets/learning/test/potato/' + str(random.randint(1, 200)) + '.jpg'
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pred = neural_network.prediction(img, model)
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show_plant_img(img)
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elif plants_array[j][i] == 'wheat':
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img = 'assets/learning/test/wheat/' + str(random.randint(1, 25)) + '.jpg'
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img = 'assets/learning/test/wheat/' + str(random.randint(1, 200)) + '.jpg'
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pred = neural_network.prediction(img, model)
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show_plant_img(img)
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else:
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