Comments (3)
- Part of the functions is supported.
- It can be trained normally.
from yolox.
I want to ask for your advice. I want to identify the bottles in the trash can. The real image is about this:
The most complex part of this scene is the dense shielding and stacking of bottles. Our purpose is to tell the customer who threw the bottle what kind of bottle he threw in, and it's better to return the location information of the bottle at the bottom of the trash can. At present, I use Yolo series for testing, and the effect is always unsatisfactory.
I want to know does you have any suggestions to improve the detection and classification ability in this scenario?
Much obliged for your assistance.
from yolox.
More effective training data in this scene is necessary.
from yolox.
Related Issues (19)
- Getting Error while executing yolo_utils.non_max_suppression(predictions) HOT 1
- AP is not improved!!! HOT 1
- yolox initial weight HOT 3
- conv2d_17_loss 和conv2d_20_loss HOT 1
- convert weights to .h5 HOT 2
- IndexError: index 3 is out of bounds for axis 0 with size 3 HOT 5
- Reason for calling fit thrice in train.py HOT 4
- GPU usage HOT 1
- backbone yolov4 HOT 3
- Handling non-square images HOT 2
- where do I find ./ckpts/yolov4.weights
- yolov4-tiny pretrained model? HOT 1
- train.py not working HOT 4
- 利用单gpu训练,速度很慢,GPU利用率很低,CPU经常跑满 HOT 3
- train error!!!!! HOT 2
- 通过关闭cfg中的数据增强手段和减小epch大小 确实加快了训练速度 但map值却一直没有上涨 HOT 3
- Transform Model to Real_Time: Serialize Model HOT 1
- Weights file used in the implementation HOT 7
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from yolox.