import numpy as np import cv2 def tlwhs_to_tlbrs(tlwhs): tlbrs = np.copy(tlwhs) if len(tlbrs) == 0: return tlbrs tlbrs[:, 2] += tlwhs[:, 0] tlbrs[:, 3] += tlwhs[:, 1] return tlbrs def get_color(idx): idx = idx * 3 color = ((37 * idx) % 255, (17 * idx) % 255, (29 * idx) % 255) return color def resize_image(image, max_size=800): if max(image.shape[:2]) > max_size: scale = float(max_size) / max(image.shape[:2]) image = cv2.resize(image, None, fx=scale, fy=scale) return image def plot_tracking(image, tlwhs, obj_ids, scores=None, frame_id=0, fps=0., ids2=None): im = np.ascontiguousarray(np.copy(image)) im_h, im_w = im.shape[:2] top_view = np.zeros([im_w, im_w, 3], dtype=np.uint8) + 255 text_scale = max(1, image.shape[1] / 1600.) text_thickness = 1 if text_scale > 1.1 else 1 line_thickness = max(1, int(image.shape[1] / 600.)) radius = max(5, int(im_w/140.)) cv2.putText(im, 'frame: %d fps: %.2f num: %d' % (frame_id, fps, len(tlwhs)), (0, int(15 * text_scale)), cv2.FONT_HERSHEY_PLAIN, text_scale, (0, 0, 255), thickness=2) for i, tlwh in enumerate(tlwhs): x1, y1, w, h = tlwh intbox = tuple(map(int, (x1, y1, x1 + w, y1 + h))) obj_id = int(obj_ids[i]) id_text = '{}'.format(int(obj_id)) if ids2 is not None: id_text = id_text + ', {}'.format(int(ids2[i])) _line_thickness = 1 if obj_id <= 0 else line_thickness color = get_color(abs(obj_id)) cv2.rectangle(im, intbox[0:2], intbox[2:4], color=color, thickness=line_thickness) cv2.putText(im, id_text, (intbox[0], intbox[1] + 30), cv2.FONT_HERSHEY_PLAIN, text_scale, (0, 0, 255), thickness=text_thickness) return im def plot_trajectory(image, tlwhs, track_ids): image = image.copy() for one_tlwhs, track_id in zip(tlwhs, track_ids): color = get_color(int(track_id)) for tlwh in one_tlwhs: x1, y1, w, h = tuple(map(int, tlwh)) cv2.circle(image, (int(x1 + 0.5 * w), int(y1 + h)), 2, color, thickness=2) return image def plot_detections(image, tlbrs, scores=None, color=(255, 0, 0), ids=None): im = np.copy(image) text_scale = max(1, image.shape[1] / 800.) thickness = 2 if text_scale > 1.3 else 1 for i, det in enumerate(tlbrs): x1, y1, x2, y2 = np.asarray(det[:4], dtype=np.int) if len(det) >= 7: label = 'det' if det[5] > 0 else 'trk' if ids is not None: text = '{}# {:.2f}: {:d}'.format(label, det[6], ids[i]) cv2.putText(im, text, (x1, y1 + 30), cv2.FONT_HERSHEY_PLAIN, text_scale, (0, 255, 255), thickness=thickness) else: text = '{}# {:.2f}'.format(label, det[6]) if scores is not None: text = '{:.2f}'.format(scores[i]) cv2.putText(im, text, (x1, y1 + 30), cv2.FONT_HERSHEY_PLAIN, text_scale, (0, 255, 255), thickness=thickness) cv2.rectangle(im, (x1, y1), (x2, y2), color, 2) return im