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王庆刚
2024-11-04 18:06:52 +08:00
parent dfb2272a15
commit 5ecc1285d4
41 changed files with 2552 additions and 440 deletions
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pipeline.py
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@ -7,24 +7,20 @@ Created on Sun Sep 29 08:59:21 2024
import os
import cv2
import pickle
import numpy as np
from pathlib import Path
from track_reid import parse_opt, yolo_resnet_tracker
from tracking.dotrack.dotracks_back import doBackTracks
from tracking.dotrack.dotracks_front import doFrontTracks
from tracking.utils.drawtracks import plot_frameID_y2, draw_all_trajectories
from utils.getsource import get_image_pairs, get_video_pairs
IMGFORMATS = '.bmp', '.jpeg', '.jpg', 'png', 'tif', 'tiff', 'webp', 'pfm'
VIDFORMATS = '.avi', '.gif', '.m4v', '.mkv', '.mov', '.mp4', '.ts', '.wmv'
std_feature_path = r"\\192.168.1.28\share\测试_202406\contrast\std_features_2192_ft32vsft16"
opt = parse_opt()
optdict = vars(opt)
std_feature_path = r"\\192.168.1.28\share\测试_202406\contrast\std_features_2192_ft32vsft16"
def get_interbcd_inputenents():
bcdpath = r"\\192.168.1.28\share\测试_202406\contrast\std_barcodes_2192"
@ -44,108 +40,118 @@ def get_interbcd_inputenents():
return input_enents
def pipeline(eventpath, stdfeat_path=None, SourceType = "image"):
'''
inputs:
eventpath: 事件文件夹
stdfeat_path: 标准特征文件地址
outputs:
def get_video_pairs(vpath):
vdieopath = []
for filename in os.listdir(vpath):
file, ext = os.path.splitext(filename)
if ext in VIDFORMATS:
vdieopath.append(os.path.join(vpath, filename))
return vdieopath
def pipeline(eventpath, stdfeat_path):
'''
SourceType = "image" # image
# eventpath = r"\\192.168.1.28\share\测试_202406\0918\images1\20240918-110822-1bc3902e-5a8e-4e23-8eca-fb3f02738551_6938314601726"
savepath = r"D:\contrast\detect"
opt = parse_opt()
optdict = vars(opt)
optdict["project"] = savepath
eventname = os.path.basename(eventpath)
barcode = eventname.split('_')[-1]
# barcode = eventname.split('_')[-1]
if SourceType == "video":
vpaths = get_video_pairs(eventpath)
elif SourceType == "image":
vpaths = get_image_pairs(eventpath)
vpaths = get_video_pairs(eventpath)
event_tracks = []
for vpath in vpaths:
'''事件结果文件夹'''
save_dir_event = Path(savepath) / Path(eventname)
save_dir_img = save_dir_event / Path(str(Path(vpath).stem))
if not save_dir_img.exists():
save_dir_img.mkdir(parents=True, exist_ok=True)
if isinstance(vpath, list):
save_dir_video = save_dir_event / Path("images")
else:
save_dir_video = save_dir_event / Path(str(Path(vpath).stem))
if not save_dir_video.exists():
save_dir_video.mkdir(parents=True, exist_ok=True)
'''Yolo + Resnet + Tracker'''
optdict["source"] = vpath
optdict["save_dir"] = save_dir_img
optdict["nosave"] = False
optdict["save_dir"] = save_dir_video
optdict["is_save_img"] = True
optdict["is_save_video"] = True
tracksdict = yolo_resnet_tracker(**optdict)
bboxes = tracksdict['TrackBoxes']
bname = os.path.basename(vpath)
bname = os.path.basename(vpath[0]) if isinstance(vpath, list) else os.path.basename(vpath)
if bname.split('_')[0] == "0" or bname.find('back')>=0:
vts = doFrontTracks(bboxes, tracksdict)
vts = doBackTracks(bboxes, tracksdict)
vts.classify()
event_tracks.append(("back", vts))
if bname.split('_')[0] == "1" or bname.find('front')>=0:
vts = doBackTracks(bboxes, tracksdict)
vts = doFrontTracks(bboxes, tracksdict)
vts.classify()
event_tracks.append(("front", vts))
'''轨迹显示模块'''
illus = [None, None]
for CamerType, vts in event_tracks:
if CamerType == 'back':
pass
if CamerType == 'front':
pass
edgeline = cv2.imread("./tracking/shopcart/cart_tempt/board_ftmp_line.png")
img_tracking = draw_all_trajectories(vts, edgeline, save_dir_event, CamerType, draw5p=True)
illus[0] = img_tracking
plt = plot_frameID_y2(vts)
plt.savefig(os.path.join(save_dir_event, "front_y2.png"))
if CamerType == 'back':
edgeline = cv2.imread("./tracking/shopcart/cart_tempt/edgeline.png")
img_tracking = draw_all_trajectories(vts, edgeline, save_dir_event, CamerType, draw5p=True)
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(save_dir_event, "traj.png")
cv2.imwrite(trajpath, img_cat)
'''前后摄轨迹选择'''
if stdfeat_path is not None:
with open(stdfeat_path, 'rb') as f:
featDict = pickle.load(f)
def main():
def main_loop():
bcdpath = r"\\192.168.1.28\share\测试_202406\contrast\std_barcodes_2192"
eventpath = r"\\192.168.1.28\share\测试_202406\0918\images1"
SourceType = "image" # video, image
barcodes = []
input_enents = []
output_events = []
# input_enents = get_interbcd_inputenents()
# k = 0
# for event in input_enents:
# pipeline(event)
# k += 1
# if k ==1:
# break
'''1. 获得barcode标准特征集列表'''
for featname in os.listdir(bcdpath):
barcode, ext = os.path.splitext(featname)
@ -153,31 +159,30 @@ def main():
continue
barcodes.append(barcode)
'''2. 构造（放入事件，标准特征）对'''
for filename in os.listdir(eventpath):
'''barcode为时间文件夹的最后一个字段'''
bcd = filename.split('_')[-1]
event_path = os.path.join(eventpath, filename)
stdfeat_path = None
if bcd in barcodes:
stdfeat_path = os.path.join(bcdpath, f"{bcd}.pickle")
stdfeat_path = os.path.join(bcdpath, f"{bcd}.pickle")
input_enents.append((event_path, stdfeat_path))
for eventpath, stdfeat_path in input_enents:
pipeline(eventpath, stdfeat_path)
pipeline(eventpath, stdfeat_path, SourceType)
def main():
eventpath = r"D:\datasets\ym\exhibition\175836"
SourceType = 'image'
stdfeat_path = None
pipeline(eventpath, stdfeat_path, SourceType)
@ -187,4 +192,10 @@ def main():
if __name__ == "__main__":
main()
main()