# -*- coding: utf-8 -*- """ Created on Sun Sep 29 08:59:21 2024 @author: ym """ import os # import sys import cv2 import pickle import numpy as np from pathlib import Path from track_reid import 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 from tracking.utils.read_data import read_similar def save_subimgs(imgdict, boxes, spath, ctype): for i in range(len(boxes)): fid, bid = int(boxes[i, 7]), int(boxes[i, 8]) if f"{fid}_{bid}" in imgdict.keys(): img = imgdict[f"{fid}_{bid}"] imgpath = spath / f"{ctype}_{fid}_{bid}.png" cv2.imwrite(imgpath, img) def pipeline( eventpath, savepath, SourceType, weights ): ''' eventpath: 单个事件的存储路径 ''' if SourceType == "video": vpaths = get_video_pairs(eventpath) elif SourceType == "image": vpaths = get_image_pairs(eventpath) optdict = {} optdict["weights"] = weights event_tracks = [] ## 构造购物事件字典 evtname = Path(eventpath).stem barcode = evtname.split('_')[-1] if len(evtname.split('_'))>=2 \ and len(evtname.split('_')[-1])>=8 \ and evtname.split('_')[-1].isdigit() else '' '''事件结果存储文件夹''' if not savepath: savepath = Path(__file__).resolve().parents[0] / "events_result" savepath_pipeline = Path(savepath) / Path("Yolos_Tracking") / evtname """ShoppingDict pickle 文件保存地址 """ savepath_spdict = Path(savepath) / "ShoppingDict_pkfile" if not savepath_spdict.exists(): savepath_spdict.mkdir(parents=True, exist_ok=True) pf_path = Path(savepath_spdict) / Path(str(evtname)+".pickle") # if pf_path.exists(): # return ShoppingDict = {"eventPath": eventpath, "eventName": evtname, "barcode": barcode, "eventType": '', # "input", "output", "other" "frontCamera": {}, "backCamera": {}, "one2n": [] } procpath = Path(eventpath).joinpath('process.data') if procpath.is_file(): SimiDict = read_similar(procpath) ShoppingDict["one2n"] = SimiDict['one2n'] for vpath in vpaths: '''相机事件字典构造''' CameraEvent = {"cameraType": '', # "front", "back" "videoPath": '', "imagePaths": [], "yoloResnetTracker": [], "tracking": [], } if isinstance(vpath, list): CameraEvent["imagePaths"] = vpath bname = os.path.basename(vpath[0]) if not isinstance(vpath, list): CameraEvent["videoPath"] = vpath bname = os.path.basename(vpath) if bname.split('_')[0] == "0" or bname.find('back')>=0: CameraEvent["cameraType"] = "back" if bname.split('_')[0] == "1" or bname.find('front')>=0: CameraEvent["cameraType"] = "front" '''事件结果存储文件夹''' if isinstance(vpath, list): savepath_pipeline_imgs = savepath_pipeline / Path("images") else: savepath_pipeline_imgs = savepath_pipeline / Path(str(Path(vpath).stem)) if not savepath_pipeline_imgs.exists(): savepath_pipeline_imgs.mkdir(parents=True, exist_ok=True) savepath_pipeline_subimgs = savepath_pipeline / Path("subimgs") if not savepath_pipeline_subimgs.exists(): savepath_pipeline_subimgs.mkdir(parents=True, exist_ok=True) '''Yolo + Resnet + Tracker''' optdict["source"] = vpath optdict["save_dir"] = savepath_pipeline_imgs yrtOut = yolo_resnet_tracker(**optdict) CameraEvent["yoloResnetTracker"] = yrtOut # bboxes = np.empty((0, 9), dtype = np.float32) # for frameDict in yrtOut: # bboxes = np.concatenate([bboxes, frameDict["tboxes"]], axis=0) trackerboxes = np.empty((0, 9), dtype=np.float64) trackefeats = {} for frameDict in yrtOut: tboxes = frameDict["tboxes"] ffeats = frameDict["feats"] 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}"]}) '''tracking''' if CameraEvent["cameraType"] == "back": vts = doBackTracks(trackerboxes, trackefeats) vts.classify() event_tracks.append(("back", vts)) CameraEvent["tracking"] = vts ShoppingDict["backCamera"] = CameraEvent if CameraEvent["cameraType"] == "front": vts = doFrontTracks(trackerboxes, trackefeats) vts.classify() event_tracks.append(("front", vts)) CameraEvent["tracking"] = vts ShoppingDict["frontCamera"] = CameraEvent with open(str(pf_path), 'wb') as f: pickle.dump(ShoppingDict, f) for CamerType, vts in event_tracks: if len(vts.tracks)==0: continue if CamerType == 'front': yolos = ShoppingDict["frontCamera"]["yoloResnetTracker"] ctype = 1 if CamerType == 'back': yolos = ShoppingDict["backCamera"]["yoloResnetTracker"] ctype = 0 imgdict = {} for y in yolos: imgdict.update(y["imgs"]) for track in vts.Residual: if isinstance(track, np.ndarray): save_subimgs(imgdict, track, savepath_pipeline_subimgs, ctype) else: save_subimgs(imgdict, track.boxes, savepath_pipeline_subimgs, ctype) '''轨迹显示模块''' illus = [None, None] for CamerType, vts in event_tracks: if len(vts.tracks)==0: continue if CamerType == 'front': edgeline = cv2.imread("./tracking/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) illus[0] = img_tracking plt = plot_frameID_y2(vts) plt.savefig(os.path.join(savepath_pipeline, "front_y2.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) 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_pipeline, "trajectory.png") cv2.imwrite(trajpath, img_cat) def main(): ''' 函数：pipeline()，遍历事件文件夹，选择类型 image 或 video, ''' parmDict = {} evtdir = r"\\192.168.1.28\share\测试视频数据以及日志\算法全流程测试\202412\images" parmDict["SourceType"] = "video" # video, image parmDict["savepath"] = r"\\192.168.1.28\share\测试视频数据以及日志\算法全流程测试\202412\result" parmDict["weights"] = r'D:\DetectTracking\ckpts\best_cls10_0906.pt' evtdir = Path(evtdir) k, errEvents = 0, [] for item in evtdir.iterdir(): if item.is_dir(): # item = evtdir/Path("20241209-160201-b97f7a0e-7322-4375-9f17-c475500097e9_6926265317292") parmDict["eventpath"] = item # pipeline(**parmDict) try: pipeline(**parmDict) except Exception as e: errEvents.append(str(item)) k+=1 if k==1: break errfile = os.path.join(parmDict["savepath"], f'error_events.txt') with open(errfile, 'w', encoding='utf-8') as f: for line in errEvents: f.write(line + '\n') if __name__ == "__main__": main()