def evaluation_all(path, target_key):
records = misc_utils.load_json_lines(path)
for i in range(10):
score_thr = 1e-1 * i
total = len(records)
stride = math.ceil(total / nr_procs)
result_queue = Queue(10000)
results, procs = [], []
for i in range(nr_procs):
start = i * stride
end = np.min([start + stride, total])
sample_data = records[start:end]
p = Process(target=compute_JI_with_ignore,
args=(result_queue, sample_data, score_thr,
target_key))
p.start()
procs.append(p)
tqdm.monitor_interval = 0
pbar = tqdm(total=total, leave=False, ascii=True)
for i in range(total):
t = result_queue.get()
results.append(t)
pbar.update(1)
for p in procs:
p.join()
pbar.close()
line, mean_ratio = gather(results)
line = 'score_thr:{:.1f}, {}'.format(score_thr, line)
print(line)
def __init__(self, config, if_train):
if if_train:
self.training = True
source = config.train_source
self.short_size = config.train_image_short_size
self.max_size = config.train_image_max_size
else:
self.training = False
source = config.eval_source
self.short_size = config.eval_image_short_size
self.max_size = config.eval_image_max_size
self.records = misc_utils.load_json_lines(source)
self.config = config
def eval_all(args):
# json file
assert os.path.exists(args.json_file), "Wrong json path!"
misc_utils.ensure_dir('outputs')
records = misc_utils.load_json_lines(args.json_file)[:args.number]
for record in records:
dtboxes = misc_utils.load_bboxes(
record, key_name='dtboxes', key_box='box', key_score='score', key_tag='tag')
gtboxes = misc_utils.load_bboxes(record, 'gtboxes', 'box')
dtboxes = misc_utils.xywh_to_xyxy(dtboxes)
gtboxes = misc_utils.xywh_to_xyxy(gtboxes)
keep = dtboxes[:, -2] > args.visual_thresh
dtboxes = dtboxes[keep]
len_dt = len(dtboxes)
len_gt = len(gtboxes)
line = "{}: dt:{}, gt:{}.".format(record['ID'], len_dt, len_gt)
print(line)
img_path = img_root + record['ID'] + '.png'
img = misc_utils.load_img(img_path)
visual_utils.draw_boxes(img, dtboxes, line_thick=1, line_color='blue')
visual_utils.draw_boxes(img, gtboxes, line_thick=1, line_color='white')
fpath = 'outputs/{}.png'.format(record['ID'])
cv2.imwrite(fpath, img)