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recognition file changes + link for neuron model

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Pavel 2023-06-04 19:02:37 +02:00
parent 20d32201ae
commit f3e6d04eb4
1 changed files with 24 additions and 0 deletions
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AI_brain/image_recognition.py
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@ -5,6 +5,7 @@ from tensorflow import keras
import cv2
import random
#YOU CAN DOWNLOAD MODEL FROM https://uam-my.sharepoint.com/:f:/g/personal/pavbia_st_amu_edu_pl/EmBHjnETuk5LiCZS6xk7AnIBNsnffR3Sygf8EX2bhR1w4A
class VacuumRecognizer:
model = keras.models.load_model('AI_brain\model.h5')
@ -18,6 +19,7 @@ class VacuumRecognizer:
predictions = self.model.predict(img)[0].tolist()
# More information about neuron decision
# print(img.shape)
# cv2.imshow("test_show", img)
# print(class_names)
@ -27,6 +29,28 @@ class VacuumRecognizer:
return class_names[predictions.index(max(predictions))]
def get_random_dir(self, type) -> str:
if type == 'Plant':
plant_image_paths = 'C:\\Users\\Pavel\\Desktop\\AI\\Machine_learning_2023\\AI_brain\\Image_datasetJPGnewBnW\\check\\Plant'
plant_dirs = os.listdir(plant_image_paths)
full_path = plant_image_paths + '\\' + plant_dirs[random.randint(0, len(plant_dirs)-1)]
print(full_path)
return full_path
elif type == 'Earings':
earnings_image_paths = 'C:\\Users\\Pavel\\Desktop\\AI\\Machine_learning_2023\\AI_brain\\Image_datasetJPGnewBnW\\check\\Earings'
earning_dirs = os.listdir(earnings_image_paths)
full_path = earnings_image_paths + '\\' + earning_dirs[random.randint(0, len(earning_dirs)-1)]
print(full_path)
return full_path
elif type == 'Banana':
banana_image_paths = 'C:\\Users\\Pavel\\Desktop\\AI\\Machine_learning_2023\\AI_brain\\Image_datasetJPGnewBnW\\check\\Banana'
banana_dirs = os.listdir(banana_image_paths)
full_path = banana_image_paths + '\\' + banana_dirs[random.randint(0, len(banana_dirs)-1)]
print(full_path)
return full_path
elif type == 'Cat':
cat_image_paths = 'C:\\Users\\Pavel\\Desktop\\AI\\Machine_learning_2023\\AI_brain\\Image_datasetJPGnewBnW\\check\\Cat'
cat_dir = os.listdir(cat_image_paths)
#For testing the neuron model