[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:def draw_boxes(img, bboxes, color=(0, 0, 255), thick=4):\nimcopy = np.copy(img)\nfor bbox in bboxes:\ncv2.rectangle(imcopy, bbox[0], bbox[1], color, thick)\nreturn imcopy\nrectangles = find_cars(test_image, ystart=ystart, ystop=ystop, scale=scale, cspace=color_space,\nhog_channel=hog_channel, svc=svc, orient=orient,\npix_per_cell=pix_per_cell, cell_per_block=cell_per_block, show_all_rectangles=False)\nwindow_img = draw_boxes(test_image, rectangles, color=(0, 0, 255), thick=3)\nplt.imshow(window_img)'}, {'role': 'assistant', 'content': "['data_exploration', 'modelling', 'result_visualization']"}]