import glob import xml.etree.ElementTree as ET import numpy as np from kmeans import kmeans, avg_iou ANNOTATIONS_PATH = "Annotations" CLUSTERS = 5 def load_dataset(path): dataset = [] for xml_file in glob.glob("{}/*xml".format(path)): tree = ET.parse(xml_file) height = int(tree.findtext("./size/height")) width = int(tree.findtext("./size/width")) for obj in tree.iter("object"): xmin = int(obj.findtext("bndbox/xmin")) / width ymin = int(obj.findtext("bndbox/ymin")) / height xmax = int(obj.findtext("bndbox/xmax")) / width ymax = int(obj.findtext("bndbox/ymax")) / height dataset.append([xmax - xmin, ymax - ymin]) return np.array(dataset) data = load_dataset(ANNOTATIONS_PATH) out = kmeans(data, k=CLUSTERS) print("Accuracy: {:.2f}%".format(avg_iou(data, out) * 100)) print("Boxes:\n {}".format(out)) ratios = np.around(out[:, 0] / out[:, 1], decimals=2).tolist() print("Ratios:\n {}".format(sorted(ratios)))