diff --git a/__pycache__/track_reid.cpython-39.pyc b/__pycache__/track_reid.cpython-39.pyc index c859070..2532102 100644 Binary files a/__pycache__/track_reid.cpython-39.pyc and b/__pycache__/track_reid.cpython-39.pyc differ diff --git a/contrast/__pycache__/feat_inference.cpython-39.pyc b/contrast/__pycache__/feat_inference.cpython-39.pyc new file mode 100644 index 0000000..725550e Binary files /dev/null and b/contrast/__pycache__/feat_inference.cpython-39.pyc differ diff --git a/contrast/one2one_contrast.py b/contrast/one2one_contrast.py index f4b8b03..8730da9 100644 --- a/contrast/one2one_contrast.py +++ b/contrast/one2one_contrast.py @@ -404,8 +404,8 @@ def stdfeat_infer(imgPath, featPath, bcdSet=None): feature_ft16 /= np.linalg.norm(feature_ft16, axis=1)[:, None] # uint8, 两种策略，1) 精度损失小, 2) 计算复杂度小 - # stdfeat_uint8, _ = ft16_to_uint8(feature_ft16) - stdfeat_uint8 = (feature_ft16*128).astype(np.int8) + # feature_uint8, _ = ft16_to_uint8(feature_ft16) + feature_uint8 = (feature_ft16*128).astype(np.int8) except Exception as e: print(f"Error accured at: {filename}, with Exception is: {e}") @@ -414,32 +414,15 @@ def stdfeat_infer(imgPath, featPath, bcdSet=None): ##================== float32 stdbDict["barcode"] = barcode stdbDict["imgpaths"] = imgpaths - stdbDict["feats"] = feature + stdbDict["feats_ft32"] = feature + stdbDict["feats_ft16"] = feature_ft16 + stdbDict["feats_uint8"] = feature_uint8 - # pkpath = os.path.join(featPath, f"{barcode}.pickle") with open(pkpath, 'wb') as f: pickle.dump(stdbDict, f) + stdBarcodeDict[barcode] = feature - - - ##================== float16 - # stdbDict_ft16["barcode"] = barcode - # stdbDict_ft16["imgpaths"] = imgpaths - # stdbDict_ft16["feats"] = feature_ft16 - # pkpath_ft16 = os.path.join(featPath, f"{barcode}_ft16.pickle") - # with open(pkpath_ft16, 'wb') as f: - # pickle.dump(stdbDict_ft16, f) - # stdBarcodeDict_ft16[barcode] = pkpath_ft16 - - - - ##================== uint8 - # stdbDict_uint8["barcode"] = barcode - # stdbDict_uint8["imgpaths"] = imgpaths - # stdbDict_uint8["feats"] = stdfeat_uint8 - # pkpath_uint8 = os.path.join(featPath, f"{barcode}_uint8.pickle") - # with open(pkpath_uint8, 'wb') as f: - # pickle.dump(stdbDict_uint8, f) + stdBarcodeDict_ft16[barcode] = feature_ft16 t2 = time.time() print(f"Barcode: {barcode}, need time: {t2-t1:.1f} secs") @@ -813,7 +796,7 @@ def main_std(): get_std_barcodeDict(std_sample_path, std_barcode_path) - # stdfeat_infer(std_barcode_path, std_feature_path, bcdSet=None) + stdfeat_infer(std_barcode_path, std_feature_path, bcdSet=None) # fileList = [] # for filename in os.listdir(std_barcode_path): @@ -829,7 +812,7 @@ if __name__ == '__main__': # main() - # main_std() + main_std() diff --git a/pipeline.py b/pipeline.py index eb346e2..1d1c0df 100644 --- a/pipeline.py +++ b/pipeline.py @@ -6,6 +6,7 @@ Created on Sun Sep 29 08:59:21 2024 """ import os import cv2 +import pickle from pathlib import Path from track_reid import parse_opt, yolo_resnet_tracker @@ -21,21 +22,49 @@ std_feature_path = r"\\192.168.1.28\share\测试_202406\contrast\std_features_21 opt = parse_opt() optdict = vars(opt) + + + + +def get_interbcd_inputenents(): + 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" + + barcodes = [] + eventpaths = [] + for featname in os.listdir(bcdpath): + barcode, ext = os.path.splitext(featname) + barcodes.append(barcode) + + input_enents = [] + for root, dirs, files in os.walk(eventpath): + input_enent = [os.path.join(root, d) for d in dirs if d.split('_')[-1] in barcodes] + + input_enents.extend(input_enent) + + + return input_enents + + + 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 - + return vdieopath -def pipeline(): - eventpath = r"\\192.168.1.28\share\测试_202406\0918\images1\20240918-110913-c3a7e4d9-23d4-4a6f-a23f-a2eeee510536_6939947701616" +def pipeline(eventpath, stdfeat_path): + # 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" optdict["project"] = savepath + eventname = os.path.basename(eventpath) + barcode = eventname.split('_')[-1] + vpaths = get_video_pairs(eventpath) event_tracks = [] @@ -75,9 +104,19 @@ def pipeline(): if CamerType == 'front': pass + '''前后摄轨迹选择''' + + + if stdfeat_path is not None: + with open(stdfeat_path, 'rb') as f: + featDict = pickle.load(f) + + + + + + - for featname in os.listdir(std_feature_path): - pass @@ -88,7 +127,63 @@ def pipeline(): def main(): - pipeline() + 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" + + + 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) + if not barcode.isdigit() or len(barcode)<=8 or ext != ".pickle" : + continue + barcodes.append(barcode) + + + + + + + + + for filename in os.listdir(eventpath): + 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") + + input_enents.append((event_path, stdfeat_path)) + + + + + for eventpath, stdfeat_path in input_enents: + pipeline(eventpath, stdfeat_path) + + + + + + + + + if __name__ == "__main__": diff --git a/pipeline_extract_subimg.py b/pipeline_extract_subimg.py new file mode 100644 index 0000000..1e3a960 --- /dev/null +++ b/pipeline_extract_subimg.py @@ -0,0 +1,125 @@ +# -*- coding: utf-8 -*- +""" +Created on Sun Sep 29 08:59:21 2024 + +@author: ym +""" +import os +import cv2 +import pickle +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 + +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) + + +def pipeline(eventpath, savepath): + # eventpath = r"\\192.168.1.28\share\测试_202406\0918\images1\20240918-110822-1bc3902e-5a8e-4e23-8eca-fb3f02738551_6938314601726" + optdict["project"] = savepath + + '''Yolo + Resnet + Tracker''' + optdict["source"] = eventpath + optdict["save_dir"] = savepath + optdict["nosave"] = False + + tracksdict = yolo_resnet_tracker(**optdict) + + bboxes = tracksdict['TrackBoxes'] + + basename = os.path.basename(eventpath) + base, ext = os.path.splitext(basename) + + if base.find('front')>=0: + vts = doFrontTracks(bboxes, tracksdict) + vts.classify() + + if base.find('back')>=0: + vts = doBackTracks(bboxes, tracksdict) + vts.classify() + + tracks = [t for t in vts.tracks if t.cls>0 and not t.is_static()] + # tracks = [t for t in vts.tracks if t.cls>0] + + for track in tracks: + # for track in vts.Residual: + for *xyxy, tid, conf, cls, fid, bid in track.boxes: + img = tracksdict[f'frame_{int(fid)}']["imgs"][int(bid)] + + imgpth = savepath / Path(f'{base}_tid-{int(tid)}_fid-{int(fid)}_bid-{int(bid)}.jpg') + + cv2.imwrite(imgpth, img) + + return len(vts.Residual) + + + + +def main(): + + videopath = r"\\192.168.1.28\share\上海中环店采集视频\21-25\videos\1\back" + savepath = r"D:\contrast\barcodes" + + vpaths = [] + for root, dirs, files in os.walk(videopath): + vpth = [os.path.join(root, f) for f in files if os.path.splitext(f)[-1] in VIDFORMATS] + vpaths.extend(vpth) + + manual_txt = os.path.join(savepath, 'manual_videos.txt') + file = open(manual_txt, 'a', encoding='utf-8') + + + + manual = [] + k = 0 + for vpath in vpaths: + videoname = os.path.basename(vpath) + + vname, ext = os.path.splitext(videoname) + barcode = videoname.split('_')[0] + + subpath = os.path.join(savepath, barcode, vname) + subpath = Path(subpath) + if not subpath.exists(): + subpath.mkdir(parents=True, exist_ok=True) + + ntract = pipeline(vpath, subpath) + + if ntract==0: + manual.append(vpath) + file.write(vpath) + file.write("\n") + + print(f"{videoname} done!!!") + k += 1 + if k==10: + break + + file.close() + + + + + + +if __name__ == "__main__": + main() + + + + + + + + + + \ No newline at end of file diff --git a/track_reid.py b/track_reid.py index 8822f53..e927a77 100644 --- a/track_reid.py +++ b/track_reid.py @@ -264,12 +264,11 @@ def yolo_resnet_tracker( im0 = annotator.result() save_path_img, ext = os.path.splitext(save_path) if save_img: - if dataset.mode == 'image': - imgpath = save_path_img + f"_{dataset}.png" - else: - imgpath = save_path_img + f"_{dataset.frame}.png" - - cv2.imwrite(Path(imgpath), im0) + # if dataset.mode == 'image': + # imgpath = save_path_img + f"_{dataset}.png" + # else: + # imgpath = save_path_img + f"_{dataset.frame}.png" + # cv2.imwrite(Path(imgpath), im0) if vid_path[i] != save_path: # new video vid_path[i] = save_path