קורס יסודות בינה מלאוכתית – RB23-09
אימון רשת 
זיהוי טנק
https://colab.research.google.com/drive/1Kgx0Ac8A74csaqob9B9tY2mo6Ctkmqqx?usp=sharing
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%pip install ultralytics import ultralytics ultralytics.checks() !pip install opencv-python-headless print (" **** done **** ") |
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import os # Print the current working directory current_directory = os.getcwd() print("Current Directory:", current_directory) # Define the main directories to create main_directories = ['test', 'train', 'val'] subdirectories = ['images', 'labels'] # Create the main directories and their subdirectories for main_dir in main_directories: main_dir_path = os.path.join(current_directory, main_dir) if not os.path.exists(main_dir_path): os.makedirs(main_dir_path) print(f"Created directory: {main_dir_path}") for sub_dir in subdirectories: sub_dir_path = os.path.join(main_dir_path, sub_dir) if not os.path.exists(sub_dir_path): os.makedirs(sub_dir_path) print(f"Created directory: {sub_dir_path}") |
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from ultralytics import YOLO model=YOLO("yolov8m.pt") !touch data.yaml |
data.yaml
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train: /content/train val: /content/val nc: 4 names: ["c1","c2","c3","c4"] |
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model.train(data="/content/data.yaml",batch=16, epochs=5) |
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pre=YOLO("/content/runs/detect/train3/weights/best.pt") |
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pre.predict("/content/val/images/tanks-dessert-86.jpg",save=True, conf=0.50) |
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pre.predict("/content/val/images/tanks-dessert-75.jpg",save=True, conf=0.350) |
