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| import os | |
| from typing import Dict | |
| import numpy as np | |
| def write_results(filename, results_dict: Dict, data_type: str): | |
| if not filename: | |
| return | |
| path = os.path.dirname(filename) | |
| if not os.path.exists(path): | |
| os.makedirs(path) | |
| if data_type in ('mot', 'mcmot', 'lab'): | |
| save_format = '{frame},{id},{x1},{y1},{w},{h},1,-1,-1,-1\n' | |
| elif data_type == 'kitti': | |
| save_format = '{frame} {id} pedestrian -1 -1 -10 {x1} {y1} {x2} {y2} -1 -1 -1 -1000 -1000 -1000 -10 {score}\n' | |
| else: | |
| raise ValueError(data_type) | |
| with open(filename, 'w') as f: | |
| for frame_id, frame_data in results_dict.items(): | |
| if data_type == 'kitti': | |
| frame_id -= 1 | |
| for tlwh, track_id in frame_data: | |
| if track_id < 0: | |
| continue | |
| x1, y1, w, h = tlwh | |
| x2, y2 = x1 + w, y1 + h | |
| line = save_format.format(frame=frame_id, id=track_id, x1=x1, y1=y1, x2=x2, y2=y2, w=w, h=h, score=1.0) | |
| f.write(line) | |
| def read_results(filename, data_type: str, is_gt=False, is_ignore=False): | |
| if data_type in ('mot', 'lab'): | |
| read_fun = read_mot_results | |
| else: | |
| raise ValueError('Unknown data type: {}'.format(data_type)) | |
| return read_fun(filename, is_gt, is_ignore) | |
| """ | |
| labels={'ped', ... % 1 | |
| 'person_on_vhcl', ... % 2 | |
| 'car', ... % 3 | |
| 'bicycle', ... % 4 | |
| 'mbike', ... % 5 | |
| 'non_mot_vhcl', ... % 6 | |
| 'static_person', ... % 7 | |
| 'distractor', ... % 8 | |
| 'occluder', ... % 9 | |
| 'occluder_on_grnd', ... %10 | |
| 'occluder_full', ... % 11 | |
| 'reflection', ... % 12 | |
| 'crowd' ... % 13 | |
| }; | |
| """ | |
| def read_mot_results(filename, is_gt, is_ignore): | |
| valid_labels = {1} | |
| ignore_labels = {2, 7, 8, 12} | |
| results_dict = dict() | |
| if os.path.isfile(filename): | |
| with open(filename, 'r') as f: | |
| for line in f.readlines(): | |
| linelist = line.split(',') | |
| if len(linelist) < 7: | |
| continue | |
| fid = int(linelist[0]) | |
| if fid < 1: | |
| continue | |
| results_dict.setdefault(fid, list()) | |
| box_size = float(linelist[4]) * float(linelist[5]) | |
| if is_gt: | |
| if 'MOT16-' in filename or 'MOT17-' in filename: | |
| label = int(float(linelist[7])) | |
| mark = int(float(linelist[6])) | |
| if mark == 0 or label not in valid_labels: | |
| continue | |
| score = 1 | |
| elif is_ignore: | |
| if 'MOT16-' in filename or 'MOT17-' in filename: | |
| label = int(float(linelist[7])) | |
| vis_ratio = float(linelist[8]) | |
| if label not in ignore_labels and vis_ratio >= 0: | |
| continue | |
| else: | |
| continue | |
| score = 1 | |
| else: | |
| score = float(linelist[6]) | |
| #if box_size > 7000: | |
| #if box_size <= 7000 or box_size >= 15000: | |
| #if box_size < 15000: | |
| #continue | |
| tlwh = tuple(map(float, linelist[2:6])) | |
| target_id = int(linelist[1]) | |
| results_dict[fid].append((tlwh, target_id, score)) | |
| return results_dict | |
| def unzip_objs(objs): | |
| if len(objs) > 0: | |
| tlwhs, ids, scores = zip(*objs) | |
| else: | |
| tlwhs, ids, scores = [], [], [] | |
| tlwhs = np.asarray(tlwhs, dtype=float).reshape(-1, 4) | |
| return tlwhs, ids, scores |