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王庆刚
2025-03-13 15:36:29 +08:00
parent 0efe8892f3
commit 9b5b135fa3
21 changed files with 837 additions and 258 deletions
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86
realtime/draw_traj.py
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# -*- coding: utf-8 -*-
"""
Created on Fri Feb 21 14:28:59 2025
@author: ym
"""
import os
import numpy as np
from pathlib import Path
import sys
sys.path.append(r"D:\DetectTracking")
from contrast.utils.event import ShoppingEvent
from tracking.utils.read_data import read_weight_sensor, extract_data_realtime, read_tracking_output_realtime
from tracking.utils.read_data import read_process
def read_tracker_data(filepath):
pass
def read_tracking_output_data(filepath):
pass
def read_process_data(filepath):
path
def main():
evtPaths = r"\\192.168.1.28\share\测试视频数据以及日志\全实时测试\V12\2025-2-21\persist"
evtPaths = Path(evtPaths)
for evtpath in evtPaths.iterdir():
## 1. 读取重力数据
if evtpath.name.find("Weight")>=0 and evtpath.name.find(".txt")>0:
weight_data = read_weight_sensor(evtpath)
if not evtpath.is_dir():
continue
## 2. 读取事件data数据
for fpath in evtpath.iterdir():
fname = fpath.name
if fname.find("tracker.data"):
pass
if fname.find("tracking_output.data"):
pass
if fname.find("process.data") >=0:
pass
fpath = str(fpath)
pass
if __name__ == "__main__":
main()

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realtime/tracker_test.py Normal file
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# -*- coding: utf-8 -*-
"""
Created on Sun Mar 2 14:15:57 2025
@author: ym
"""
import numpy as np
import cv2
import os
from pathlib import Path
import sys
sys.path.append(r"D:\DetectTracking")
# from tracking.utils.read_data import extract_data_realtime, read_tracking_output_realtime
from tracking.utils.plotting import Annotator, colors
from tracking.utils import Boxes, IterableSimpleNamespace, yaml_load, boxes_add_fid
from tracking.trackers import BOTSORT, BYTETracker
from tracking.utils.showtrack import drawtracks
from hands.hand_inference import hand_pose
from tracking.utils.read_data import read_weight_sensor, extract_data_realtime, read_tracking_output_realtime
from contrast.feat_extract.config import config as conf
from contrast.feat_extract.inference import FeatsInterface
from tracking.utils.drawtracks import drawTrack
ReIDEncoder = FeatsInterface(conf)
W, H = 1024, 1280
Mode = 'front' #'back'
ImgFormat = ['.jpg', '.jpeg', '.png', '.bmp']
'''调用tracking()函数，利用本地跟踪算法获取各目标轨迹，可以比较本地跟踪算法与现场跟踪算法的区别。'''
def init_tracker(tracker_yaml = None, bs=1):
"""
Initialize tracker for object tracking during prediction.
"""
TRACKER_MAP = {'bytetrack': BYTETracker, 'botsort': BOTSORT}
cfg = IterableSimpleNamespace(**yaml_load(tracker_yaml))
tracker = TRACKER_MAP[cfg.tracker_type](args=cfg, frame_rate=30)
return tracker
def init_trackers(tracker_yaml = None, bs=1):
"""
Initialize trackers for object tracking during prediction.
"""
# tracker_yaml = r"./tracking/trackers/cfg/botsort.yaml"
TRACKER_MAP = {'bytetrack': BYTETracker, 'botsort': BOTSORT}
cfg = IterableSimpleNamespace(**yaml_load(tracker_yaml))
trackers = []
for _ in range(bs):
tracker = TRACKER_MAP[cfg.tracker_type](args=cfg, frame_rate=30)
trackers.append(tracker)
return trackers
def draw_box(img, tracks):
annotator = Annotator(img.copy(), line_width=2)
# for *xyxy, conf, cls in reversed(tracks):
# name = f'{int(cls)} {conf:.2f}'
# color = colors(int(cls), True)
# annotator.box_label(xyxy, name, color=color)
for *xyxy, id, conf, cls, fid, bid in reversed(tracks):
name = f'ID:{int(id)} {int(cls)} {conf:.2f}'
color = colors(int(cls), True)
annotator.box_label(xyxy, name, color=color)
im0 = annotator.result()
return im0
def tracking(bboxes, ffeats):
tracker_yaml = "./tracking/trackers/cfg/botsort.yaml"
tracker = init_tracker(tracker_yaml)
TrackBoxes = np.empty((0, 9), dtype = np.float32)
TracksDict = {}
frmIds = []
'''========================== 执行跟踪处理 ============================='''
# dets 与 feats 应保持严格对应
k=0
for dets, feats in zip(bboxes, ffeats):
frmIds.append(np.unique(dets[:, 6]).astype(np.int64)[0])
boxes = dets[:, :6]
det_tracking = Boxes(boxes).cpu().numpy()
tracks, outfeats = tracker.update(det_tracking, features=feats)
'''tracks: [x1, y1, x2, y2, track_id, score, cls, frame_index, box_index]
0 1 2 3 4 5 6 7 8
这里，frame_index 也可以用视频的 帧ID 代替, box_index 保持不变
'''
k += 1
imgpath = r"D:\全实时\202502\tracker\Yolos_Tracking\tracker\1_1740891284792\1_1740891284792_{}.png".format(int(k))
img = cv2.imread(imgpath)
im0 = draw_box(img, tracks)
savepath = r"D:\全实时\202502\tracker\Yolos_Tracking\tracker\1_1740891284792\b\1_1740891284792_{}_b.png".format(k)
cv2.imwrite(savepath, im0)
if len(tracks):
TrackBoxes = np.concatenate([TrackBoxes, tracks], axis=0)
# =============================================================================
# FeatDict = {}
# for track in tracks:
# tid = int(track[8])
# FeatDict.update({tid: feats[tid, :]})
#
# frameID = tracks[0, 7]
#
# # print(f"frameID: {int(frameID)}")
# assert len(tracks) == len(FeatDict), f"Please check the func: tracker.update() at frameID({int(frameID)})"
#
# TracksDict[f"frame_{int(frameID)}"] = {"feats":FeatDict}
# =============================================================================
return TrackBoxes, TracksDict
def dotrack():
datapath = r"D:\全实时\202502\tracker\1_tracker_in.data"
bboxes, ffeats = extract_data_realtime(datapath)
trackerboxes, tracker_feat_dict = tracking(bboxes, ffeats)
print("done!")
# def plotbox():
# fpath = r"\\192.168.1.28\share\测试视频数据以及日志\全实时测试\V12\2025-3-3\20250303-103833-338_6928804010091_6928804010091\1_tracking_output.data"
# imgpath = r"D:\全实时\202502\result\Yolos_Tracking\20250303-103833-338_6928804010091_6928804010091\1_1740969517953"
# trackingboxes, trackingfeats, tracking_outboxes, tracking_outfeats = read_tracking_output_realtime(fpath)
# for *xyxy, id, conf, cls, fid, bid in tracking_outboxes[0]:
# imgname = f"1_1740969517953_{int(fid)}.png"
# img_path = os.path.join(imgpath, imgname)
# img = cv2.imread(img_path)
# annotator = Annotator(img.copy(), line_width=2)
# name = f'ID:{int(id)} {int(cls)} {conf:.2f}'
# color = colors(int(cls), True)
# annotator.box_label(xyxy, name, color=color)
# im0 = annotator.result()
# cv2.imwrite(os.path.join(imgpath, f"1_1740969517953_{int(fid)}_.png"), im0)
# print(f"1_1740969676295_{int(fid)}_.png")
# print("done")
def video2imgs(videopath):
cap = cv2.VideoCapture(str(videopath))
k = 0
while True:
ret, frame = cap.read()
if frame is None:
break
k += 1
imgpath = videopath.parent / f"{videopath.stem}_{k}.png"
cv2.imwrite(str(imgpath), frame)
def extract_evtimgs(evtpath):
vidpaths = [v for v in evtpath.iterdir() if v.suffix == '.mp4']
for vidpath in vidpaths:
video2imgs(vidpath)
stamps = [name.stem.split('_')[1] for name in vidpaths]
if len(set(stamps)==1):
return stamps[0]
return None
def draw_tracking_boxes(evtpath, stamp):
for datapath in evtpath.iterdir():
if datapath.name.find('_tracking_output.data')<=0:
continue
camera = datapath.stem.split('_')[0]
trackingboxes, trackingfeats, tracking_outboxes, tracking_outfeats = read_tracking_output_realtime(str(datapath))
## 该模块先读取轨迹数据，再根据帧ID读取相应图像
for *xyxy, id, conf, cls, fid, bid in tracking_outboxes[0]:
imgpath = evtpath / f"{camera}_{stamp}_{int(fid)}.png"
img = cv2.imread(str(imgpath))
annotator = Annotator(img.copy(), line_width=2)
name = f'ID:{int(id)} {int(cls)} {conf:.2f}'
color = colors(int(cls), True)
annotator.box_label(xyxy, name, color=color)
im0 = annotator.result()
cv2.imwrite(imgpath, im0)
print(datapath.name)
def draw_traj(evtpath):
for datapath in evtpath.iterdir():
if datapath.name.find('_tracking_output.data')<=0:
continue
fname = datapath.name
trackingboxes, trackingfeats, tracking_outboxes, tracking_outfeats = read_tracking_output_realtime(datapath)
CamerType = fname.split('_')[0]
if CamerType == '1':
edgeline = cv2.imread("./CartTemp/board_ftmp_line.png")
if CamerType == '0':
edgeline = cv2.imread("./CartTemp/edgeline.png")
edgeline = drawTrack(tracking_outboxes, edgeline)
imgpath = datapath.parent / f"{datapath.stem}.png"
cv2.imwrite(str(imgpath), edgeline)
def main():
path = r"\\192.168.1.28\share\测试视频数据以及日志\全实时测试\V12\2025-3-3\20250303-104225-381_6920459958674"
evtpaths = [p for p in Path(path).iterdir() if p.is_dir()]
for evtpath in evtpaths:
#1. 从事件的前后摄视频提取图像
stamp = extract_evtimgs(evtpath)
#2. 根据 0/1_tracking_output.data 中提取的轨迹在img中绘制box
draw_tracking_boxes(evtpath, stamp)
#3. 根据 0/1_tracking_output.data 中提取的轨迹在edgeline中绘制box
draw_traj(evtpath)
if __name__ == '__main__':
# dotrack()
# plotbox()
vpath = r"D:\datasets\ym\VID_20250307_105606"
extract_evtimgs(Path(vpath))