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增加了单帧入侵判断及yoloV10

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18262620154
2025-04-11 17:02:39 +08:00
parent 798c596acc
commit e044c85a04
197 changed files with 1863 additions and 997 deletions
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tracking/tracking_pipeline.py
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@ -11,170 +11,222 @@ import pickle
import numpy as np
from pathlib import Path
from scipy.spatial.distance import cdist
import copy
from .dotrack.dotracks_back import doBackTracks
from .dotrack.dotracks_front import doFrontTracks
from .utils.drawtracks import plot_frameID_y2, draw_all_trajectories
from .utils.read_data import read_similar
from dotrack.dotracks_back import doBackTracks
from dotrack.dotracks_front import doFrontTracks
from utils.drawtracks import plot_frameID_y2, draw_all_trajectories
from utils.read_data import read_similar
def get_trail(ShoppingDict, ppath):
evtname = ShoppingDict["eventName"]
back_yrt = ShoppingDict["backCamera"]["yoloResnetTracker"]
front_yrt = ShoppingDict["frontCamera"]["yoloResnetTracker"]
back_vts = ShoppingDict["frontCamera"]["tracking"]
front_vts = ShoppingDict["backCamera"]["tracking"]
event_tracks = [("back", back_yrt, back_vts), ("front", front_yrt, front_vts)]
savepath = ppath / "alltrail"
if not savepath.exists():
savepath.mkdir()
savepath = str(savepath)
evtime = evtname[:15]
illus = [None, None]
for camera_type, yrtOut, vts in event_tracks:
if len(vts.Residual)==1: continue
if camera_type == 'front':
edgeline = cv2.imread("./shopcart/cart_tempt/board_ftmp_line.png")
img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
illus[0] = img_tracking
class CameraEvent_:
def __init__(self):
self.cameraType = '', # "front", "back"
self.videoPath = '',
self.imagePaths = [],
self.yoloResnetTracker =[],
self.tracking = None,
class ShoppingEvent_:
def __init__(self):
self.eventPath = ''
self.eventName = ''
self.barcode = ''
self.eventType = '', # "input", "output", "other"
self.frontCamera = None
self.backCamera = None
self.one2n = []
plt = plot_frameID_y2(vts)
plt.savefig(os.path.join(savepath, f"{evtime}_front.png"))
if camera_type == 'back':
edgeline = cv2.imread("./shopcart/cart_tempt/edgeline.png")
img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
illus[1] = img_tracking
illus = [im for im in illus if im is not None]
if len(illus):
img_cat = np.concatenate(illus, axis = 1)
if len(illus)==2:
H, W = img_cat.shape[:2]
cv2.line(img_cat, (int(W/2), 0), (int(W/2), int(H)), (128, 128, 255), 3)
trajpath = os.path.join(savepath, f"{evtime}.png")
cv2.imwrite(trajpath, img_cat)
return evtime
return None
def main():
def track_opt(ShoppingDict, ppath):
'''
将一个对象读取，修改其中一个属性
'''
evtname = ShoppingDict["eventName"]
shopping = copy.deepcopy(ShoppingDict)
evt_pkfile = 'path.pickle'
with open(evt_pkfile, 'rb') as f:
ShoppingDict = pickle.load(f)
savepath = ""
## only need to init item: tracking for each Camera
shopping["frontCamera"]["tracking"] = []
shopping["backCamera"]["tracking"] = []
back_camera = ShoppingDict["backCamera"]["cameraType"]
back_yrt = ShoppingDict["backCamera"]["yoloResnetTracker"]
front_camera = ShoppingDict["frontCamera"]["cameraType"]
front_yrt = ShoppingDict["frontCamera"]["yoloResnetTracker"]
yrts = [(back_camera, back_yrt), (front_camera, front_yrt)]
shopping_event = ShoppingEvent_()
shopping_event.eventPath = ShoppingDict["eventPath"]
shopping_event.eventName = ShoppingDict["eventName"]
shopping_event.barcode = ShoppingDict["barcode"]
yrtDict = {}
event_tracks = []
for camera_type, yrtOut in yrts:
'''
inputs:
yrtOut
camera_type
outputs:
CameraEvent
'''
camera_event = CameraEvent_()
'''================= 4. tracking ================='''
errtrail = ''
for camera_type, yrtOut in yrts:
'''================= 1. tracking ================='''
'''(1) 生成用于 tracking 模块的 boxes、feats'''
bboxes = np.empty((0, 6), dtype=np.float64)
# bboxes = np.empty((0, 6), dtype=np.float64)
trackerboxes = np.empty((0, 9), dtype=np.float64)
trackefeats = {}
for frameDict in yrtOut:
tboxes = frameDict["tboxes"]
ffeats = frameDict["feats"]
boxes = frameDict["bboxes"]
bboxes = np.concatenate((bboxes, np.array(boxes)), axis=0)
# boxes = frameDict["bboxes"]
# bboxes = np.concatenate((bboxes, np.array(boxes)), axis=0)
trackerboxes = np.concatenate((trackerboxes, np.array(tboxes)), axis=0)
for i in range(len(tboxes)):
fid, bid = int(tboxes[i, 7]), int(tboxes[i, 8])
trackefeats.update({f"{fid}_{bid}": ffeats[f"{fid}_{bid}"]})
'''(2) tracking, 后摄'''
if CameraEvent["cameraType"] == "back":
if camera_type == "back":
vts = doBackTracks(trackerboxes, trackefeats)
vts.classify()
event_tracks.append(("back", vts))
shopping["backCamera"]["tracking"] = vts
camera_event.camera_type = camera_type
camera_event.yoloResnetTracker = yrtOut
camera_event.tracking = vts
camera_event.videoPath = ShoppingDict["backCamera"]["videoPath"]
camera_event.imagePaths = ShoppingDict["backCamera"]["imagePaths"]
shopping_event.backCamera = camera_event
yrtDict["backyrt"] = yrtOut
'''(2) tracking, 前摄'''
if CameraEvent["cameraType"] == "front":
if len(vts.Residual)!=1:
errtrail = evtname
'''(3) tracking, 前摄'''
if camera_type == "front":
vts = doFrontTracks(trackerboxes, trackefeats)
vts.classify()
event_tracks.append(("front", vts))
shopping["frontCamera"]["tracking"] = vts
camera_event.camera_type = camera_type
camera_event.yoloResnetTracker = yrtOut
camera_event.tracking = vts
camera_event.videoPath = ShoppingDict["frontCamera"]["videoPath"]
camera_event.imagePaths = ShoppingDict["frontCamera"]["imagePaths"]
shopping_event.backCamera = camera_event
yrtDict["frontyrt"] = yrtOut
if len(vts.Residual)!=1:
errtrail = evtname
event_tracks.append((camera_type, yrtOut, vts))
pckpath = ppath / "track_optim"
if not pckpath.exists():
pckpath.mkdir()
fpath = pckpath / "{}_new.pickle".format(evtname)
with open(str(fpath), 'wb') as f:
pickle.dump(shopping, f)
name = Path(evt_pkfile).stem
pf_path = os.path.join(savepath, name+"_new.pickle")
with open(str(pf_path), 'wb') as f:
pickle.dump(shopping_event, f)
savepath = ppath / "yolos_tracking" / evtname
illus = [None, None]
for CamerType, vts in event_tracks:
for camera_type, yrtOut, vts in event_tracks:
if len(vts.tracks)==0: continue
if CamerType == 'front':
edgeline = cv2.imread("./tracking/shopcart/cart_tempt/board_ftmp_line.png")
if camera_type == 'front':
edgeline = cv2.imread("./shopcart/cart_tempt/board_ftmp_line.png")
h, w = edgeline.shape[:2]
# nh, nw = h//2, w//2
# edgeline = cv2.resize(edgeline, (nw, nh), interpolation=cv2.INTER_AREA)
img_tracking = draw_all_trajectories(vts, edgeline, savepath_pipeline, CamerType, draw5p=True)
img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
illus[0] = img_tracking
plt = plot_frameID_y2(vts)
plt.savefig(os.path.join(savepath_pipeline, "front_y2.png"))
plt.savefig(os.path.join(savepath, "front_y2_new.png"))
if CamerType == 'back':
edgeline = cv2.imread("./tracking/shopcart/cart_tempt/edgeline.png")
h, w = edgeline.shape[:2]
# nh, nw = h//2, w//2
# edgeline = cv2.resize(edgeline, (nw, nh), interpolation=cv2.INTER_AREA)
img_tracking = draw_all_trajectories(vts, edgeline, savepath_pipeline, CamerType, draw5p=True)
if camera_type == 'back':
edgeline = cv2.imread("./shopcart/cart_tempt/edgeline.png")
img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
illus[1] = img_tracking
illus = [im for im in illus if im is not None]
if len(illus):
img_cat = np.concatenate(illus, axis = 1)
if len(illus)==2:
H, W = img_cat.shape[:2]
cv2.line(img_cat, (int(W/2), 0), (int(W/2), int(H)), (128, 128, 255), 3)
trajpath = os.path.join(savepath, "trajectory_new.png")
cv2.imwrite(trajpath, img_cat)
return errtrail
def main():
# evttypes = ["single_event_V10", "single_event_V5", "performence_V10", "performence_V5"]
evttypes = ["single_event_V10"]
k = 0
error_trail = []
for evttype in evttypes:
ppath = Path("/home/wqg/dataset/pipeline/yrt/{}".format(evttype))
pkpath = ppath / "shopping_pkl"
for fp in pkpath.iterdir():
# fp = pkpath / "{}.pickle".format("20250305-152917-635_6970209860221_6970209860221")
print(fp)
if fp.suffix != '.pickle': continue
with open(str(fp), 'rb') as f:
ShoppingDict = pickle.load(f)
# errtrail = track_opt(ShoppingDict, ppath)
# error_trail.append(errtrail)
errtrail = get_trail(ShoppingDict, ppath)
if errtrail is not None:
error_trail.append(errtrail)
# k+=1
# if k==100:
# break
errfile = ppath / 'error_trail.txt'
with open(errfile, 'w', encoding='utf-8') as f:
for line in error_trail:
f.write(line + '\n')
if __name__ == "__main__":
main()
main()