LocalizeSORT/run.py at localizesortplus · shinobi-wolf/LocalizeSORT · GitHub

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import cv2
import numpy as np
from pathlib import Path
import yaml
from types import SimpleNamespace

from boxmot import DeepOCSORT, StrongSORT
from boxmot import create_tracker, get_tracker_config

import os
import glob
import time

tracker = StrongSORT(
            Path('osnet_x0_25_msmt17.pt'),
            "cpu",
            False,
            max_age=800,
        )

video_path = "/home/srihari/tcs/data/mango_videos/GOPR1731_reconstruction/images"
num_images = 844
detections_path = "/home/srihari/tcs/data/mango_videos/GOPR1731_reconstruction/detections.txt"
save_results_file = "/home/srihari/tcs/data/mango_videos/GOPR1731_reconstruction/localizesort_plus.txt"
wcs_path = "/home/srihari/tcs/data/mango_videos/GOPR1731_reconstruction/wcs.txt"

color = (255, 255, 255)  # BGR
thickness = 2
fontscale = 0.5

mango_detections = []
with open(detections_path, 'r') as f:
    for i in f.readlines():
        if i.strip() == '':
            mango_detections.append([])
            continue
        bboxes = i.strip().split(';')
        bboxes = [[float(x) for x in y.split(',')] for y in bboxes]
        mango_detections.append(bboxes)

wcs = []
with open(wcs_path, 'r') as f:
    for i in f.readlines():
        if i.strip() == '':
            wcs.append([])
            continue
        bboxes = i.strip().split(';')
        bboxes = [[float(x) for x in y.split(',')] for y in bboxes]
        wcs.append(bboxes)

def file_sorter(x):
    x = x.strip().split('/')[-1]
    return float(x[5:-4])
# def file_sorter(x):
#     x = x.strip().split('/')[-1]
#     x = x[:-4].split('_')
#     x = float(x[1])+0.1*float(x[2])
#     return x
files = sorted(glob.glob(os.path.join(video_path, '*.*')), key=file_sorter)

gidx = []
result_file = open(save_results_file, 'w')

start = time.time()

req_frames = [y for y in range(25)] + [y for y in range(740,760)]

# for _, img_file in enumerate(files[:]):
for frame_counter in req_frames:
    img_file = files[frame_counter]
    print("Frame:", frame_counter+1)
    im = cv2.imread(img_file)

    bboxes_ = mango_detections[frame_counter]
    wc = wcs[frame_counter]
    # good_idxs = []
    # for idx, tmp in enumerate(wc):
    #     if tmp[0] != -1:
    #         good_idxs.append(idx)
    # bboxes_ = [bboxes_[x] for x in good_idxs]
    # wcs = [wcs[x] for x in good_idxs]

    # bboxes_.sort(key=lambda x:x[0])
    for i in bboxes_:
        i.append(1)
        i.append(0)
    dets = np.array(bboxes_)

    if len(bboxes_) == 0:
        dets = np.array([[0.,0.,1.,1.,0.,0]])
        wc = np.array([[0,0,0]])

    tracks = tracker.update(dets, im, wc)
    if len(tracks) != 0:
        tracks, last_wcs = tracks
        xyxys = tracks[:, 0:4].astype('int') # float64 to int
        ids = tracks[:, 4].astype('int') # float64 to int
        confs = tracks[:, 5]
        clss = tracks[:, 6].astype('int') # float64 to int
        inds = tracks[:, 7].astype('int') # float64 to int

        if tracks.shape[0] != 0:
            for xyxy, id, conf, cls, last_wc in zip(xyxys, ids, confs, clss, last_wcs):
                if conf >= 0.9:
                    result_file.write(f"{frame_counter+1},{id},{xyxy[0]},{xyxy[1]},{xyxy[2]-xyxy[0]},{xyxy[3]-xyxy[1]},{last_wc[0]},{last_wc[1]},{last_wc[2]},-1\n")
                    if not id in gidx:
                        gidx.append(id)
                    im = cv2.rectangle(
                        im,
                        (xyxy[0], xyxy[1]),
                        (xyxy[2], xyxy[3]),
                        color,
                        thickness
                    )
                    cv2.putText(
                        im,
                        f'id: {id}, conf: {conf}, c: {cls}',
                        (xyxy[0], xyxy[1]-10),
                        cv2.FONT_HERSHEY_SIMPLEX,
                        fontscale,
                        color,
                        thickness
                    )

    # show image with bboxes, ids, classes and confidences
    im = cv2.resize(im, (1920,1080))
    cv2.imshow('frame', im)

    # break on pressing q
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

    # frame_counter += 1

    print('---------------------------------------------------')

end = time.time()
result_file.close()
print(num_images/(end-start))

cv2.destroyAllWindows()

print(len(gidx))