Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/dltrack.py @ 1229:759d76d6d20c

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minor variable name update
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 13 Jul 2023 17:40:37 -0400
parents 5a207c838323
children c582b272108f
comparison
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1228:5654c9173548 1229:759d76d6d20c
1 #! /usr/bin/env python3 1 #! /usr/bin/env python3
2 # from https://docs.ultralytics.com/modes/track/ 2 # from https://docs.ultralytics.com/modes/track/
3 import sys, argparse 3 import sys, argparse
4 4
5 from trafficintelligence.moving import cocoUserTypeNames 5 from trafficintelligence.moving import cocoTypeNames
6 from ultralytics import YOLO 6 from ultralytics import YOLO
7 7
8 parser = argparse.ArgumentParser(description='The program tracks objects following the ultralytics yolo executable.')#, epilog = 'Either the configuration filename or the other parameters (at least video and database filenames) need to be provided.') 8 parser = argparse.ArgumentParser(description='The program tracks objects following the ultralytics yolo executable.')#, epilog = 'Either the configuration filename or the other parameters (at least video and database filenames) need to be provided.')
9 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (overrides the configuration file)') 9 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (overrides the configuration file)')
10 # detect model 10 # detect model
17 # seg could be used on cropped image... if can be loaded and kept in memory 17 # seg could be used on cropped image... if can be loaded and kept in memory
18 # model = YOLO('/home/nicolas/Research/Data/classification-models/yolo_nas_l.pt ') # AttributeError: 'YoloNAS_L' object has no attribute 'get' 18 # model = YOLO('/home/nicolas/Research/Data/classification-models/yolo_nas_l.pt ') # AttributeError: 'YoloNAS_L' object has no attribute 'get'
19 19
20 # Track with the model 20 # Track with the model
21 if args.display: 21 if args.display:
22 results = model.track(source=args.videoFilename, tracker="/home/nicolas/Research/Data/classification-models/bytetrack.yaml", classes=list(cocoUserTypeNames.keys()), show=True) # , save_txt=True 22 results = model.track(source=args.videoFilename, tracker="/home/nicolas/Research/Data/classification-models/bytetrack.yaml", classes=list(cocoTypeNames.keys()), show=True) # , save_txt=True
23 else: 23 else:
24 results = model.track(source=args.videoFilename, tracker="/home/nicolas/Research/Data/classification-models/bytetrack.yaml", classes=list(cocoUserTypeNames.keys()), stream=True) 24 results = model.track(source=args.videoFilename, tracker="/home/nicolas/Research/Data/classification-models/bytetrack.yaml", classes=list(cocoTypeNames.keys()), stream=True)
25 for result in results: 25 for result in results:
26 for box in result.boxes: 26 for box in result.boxes:
27 print(box.xyxy) 27 print(box.xyxy)