Comments (14)
yolo is used for detection, which can detect 80 classes with coco dataset.
deep_sort can only calculate person appearance features with default model. even though you detect multi targets such as cars, truck, bird etc with yolo, the deep_sort tracking performace would not be well.
you need train your own model for tracking.
from deep_sort_yolov3.
Change the part in the yolo detector code where we filter 'person' from detected boxes.
In yolo.py
for i, c in reversed(list(enumerate(out_classes))):
predicted_class = self.class_names[c]
if predicted_class != 'person' :
continue
box = out_boxes[i]
Change 'person' to 'car'.
from deep_sort_yolov3.
Excellent! Missed that, thank you for the pointer! @anshu1106
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Maybe not , the deep_sort model was just trained for person
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I can confirm that it tracks cars, birds and trucks too and performs well.
from deep_sort_yolov3.
Maybe deep_sort more like a feature coding and similarity comparator , no matter what object it is .
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hi!, there's a way to track multiple objects?, like cars and trucks at the same time?
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you can have a try . they all belong to "car" , just like @anshu1106 say to have a try .
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Thanks a lot ,btw it can be easily used to track cars. It's favoured if the relevant paper can be provide : )
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I want to track other things, not people, cars, birds, etc. However, the tracking effect is not good. How should I train again?
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@Goldwh You can reference to https://github.com/nwojke/deep_sort
from deep_sort_yolov3.
hi!, there's a way to track multiple objects?, like cars and trucks at the same time?
yes.
Change the part in the yolo detector code where we filter 'person' from detected boxes.
In yolo.py
for i, c in reversed(list(enumerate(out_classes))):
predicted_class = self.class_names[c]
if predicted_class != 'car' and predicted_class!='truck' :
continue
box = out_boxes[i]
Change 'person' to 'car'.
from deep_sort_yolov3.
hi! I ran demp.py. than this error occur
VIDEOIO ERROR: V4L2: Pixel format of incoming image is unsupported by OpenCV
can anyone help me figure out some way to overcome this error?
from deep_sort_yolov3.
yolo is used for detection, which can detect 80 classes with coco dataset.
deep_sort can only calculate person appearance features with default model. even though you detect multi targets such as cars, truck, bird etc with yolo, the deep_sort tracking performace would not be well.you need train your own model for tracking.
I agree. DeepSort is trained for Person Re-Identification. I wanted to track people and cars together, I observed a lot of ID switches for vehicles. so, If you want to use the same model to track multiple objects then it would need to be trained again.
from deep_sort_yolov3.
Related Issues (20)
- demo.py 异常 HOT 2
- yolo3模型是tensorflow生成的ckpt文件或者pb文件,如何转换到.h5文件用到这个项目中呢?
- encoder = gdet.create_box_encoder(model_filename, batch_size=1)中的batch_size有什么用?
- Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR HOT 1
- How to count each object separately?
- UnboundLocalError: local variable 'track' referenced before assignment HOT 3
- requirements.txt
- i want to set the gpu fraction,but it failed, gpu is always fully occupied
- process killed on running demo.py
- Error
- cpu占用率暴涨
- what is mars-small128.pb ? and what is it use for ?
- A typo in README.md
- confusing
- No ID of people on output .txt detections file
- 为什么我的darknet运行yolov4只有10帧左右
- 人出去之后,还有追踪框停留。max_age设置为0,依旧存在该问题
- 我在keras-yolov3训练了改动的yolov3,生成的h5用到deepsort,会多一个functional层,如何解决
- 我可以保存检测到的路径吗
- QQ群不见了吗 HOT 1
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