nabang1010
commented
3 months ago Look at scripts from line 92 to line 97 in yolov8_deepsort_trt.py
for (bbox, score, label) in zip(bboxes, scores, labels):
if label == 0 and score.item() > 0.3:
bbox = bbox.round().int().tolist()
cls_id = int(label)
cls = CLASSES[cls_id]
detections.append((bbox[0], bbox[1], bbox[2] , bbox[3], cls, score.item()))The pre-trained model has 80 classes but I only used class 0 (person) to do in the sample video. So I used if label == 0 to filter.
You can refer list classes:
0: person
1: bicycle
2: car
3: motorcycle
4: airplane
5: bus
6: train
7: truck
8: boat
9: traffic light
10: fire hydrant
11: stop sign
12: parking meter
13: bench
14: bird
15: cat
16: dog
17: horse
18: sheep
19: cow
20: elephant
21: bear
22: zebra
23: giraffe
24: backpack
25: umbrella
26: handbag
27: tie
28: suitcase
29: frisbee
30: skis
31: snowboard
32: sports ball
33: kite
34: baseball bat
35: baseball glove
36: skateboard
37: surfboard
38: tennis racket
39: bottle
40: wine glass
41: cup
42: fork
43: knife
44: spoon
45: bowl
46: banana
47: apple
48: sandwich
49: orange
50: broccoli
51: carrot
52: hot dog
53: pizza
54: donut
55: cake
56: chair
57: couch
58: potted plant
59: bed
60: dining table
61: toilet
62: tv
63: laptop
64: mouse
65: remote
66: keyboard
67: cell phone
68: microwave
69: oven
70: toaster
71: sink
72: refrigerator
73: book
74: clock
75: vase
76: scissors
77: teddy bear
78: hair drier
79: toothbrush
lovechang1986
I tested the sample video and had no problem recognizing and tracking it ok. But when I use my phone to record a video about traffic flow on an overpass, it seems that the recognition and tracking don't work, also I used YOLOv8 from the reference repository, and after compiling it, I found that the video is able to recognize some content, I don't know why this is the case?