[{'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 process(img):\ncolor_space = \'YUV\' # Can be RGB, HSV, LUV, HLS, YUV, YCrCb\nhog_channel = \'ALL\' # Can be 0, 1, 2, or "ALL"\norient = 11\npix_per_cell = 16\ncell_per_block = 2\nrectangles = multi_windows(img)\nheatmap_img = np.zeros_like(img[:,:,0])\nheatmap_img = add_heat(heatmap_img, rectangles)\nheatmap_img = apply_threshold(heatmap_img, 1)\nlabels = label(heatmap_img)\ndraw_img, rects = draw_labeled_bboxes(np.copy(img), labels)\nreturn draw_img'}, {'role': 'assistant', 'content': "['modelling', 'result_visualization']"}]