YOLObile

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Bumps [numpy](https://github.com/numpy/numpy) from 1.17.5 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...

dependabot[bot]

您好： 我在调试您的yolobile代码的时候，换用VOC数据集，但是当有一层shape是（75, 256）的时候出现了"the layer size is not divisible"，想请教一下您该如何处理这种不能被block_size整除的情况呢？

FancyL1999

Running Yolov5 with yolobile

1

Can this be implemented on the yolov5 model? I am looking to run the yolov5s model.

abhishekbalu

How to export onnx models or to trained onnx files

1

Hi, guys I want to use the tencent ncnn library to run YOLObile in the android mobile can you provide me a trained onnx file? or tell me how to...

JiweiMaster

请问可以告诉我这部分的代码优化在哪里么？

fantow

模型文件大

14

第一步训练生成的4个模型文件的大小为256M，第二步生成的模型文件大小为500M左右，请问为啥会折磨大呢，这不是要部署在手机上吗，这样大的模型文件怎麼部署呢，请作者看到后能不能回复一下，万分感谢

baisong666

train.py

2

Hi, Thank you for approaching me efficient pruning method. I implemented 1 of 2 pruning steps(Training & Masked retraining). While I train with train.py, 4 batch size, and 25 epoch,...

hhb1224

请问csdarknet53s-panet-spp.cfg是什么模型？

1

csdarknet53s-panet-spp.cfg和yolov4的config不一致，用yolov4dense.pt计算出的mAP为45.7（python test.py --img-size 320 --batch-size 64 --device 0 --cfg cfg/csdarknet53s-panet-spp.cfg --weights weights/yolov4dense.pt --data data/coco2017.data）,而yolov4 mAP仅为38.2。所以该模型不是yolov4,请问是什么模型呢？

ananasfl

problem when compute COCO mAP

1

hair drier 5e+03 11 0 0 0.0385 0 toothbrush 5e+03 57 0.335 0.386 0.337 0.359 Speed: 43.3/3.9/47.2 ms inference/NMS/total per 320x320 image at batch-size 64 COCO mAP with pycocotools... WARNING:...

job2003

The problem of speed in TX2

1

when I run your .cfg and weight on NVIDIA Jetson TX2 , the speed is only 5 fps . But when i run Yolov3-tiny .cfg and .weight , the speed...

f64051041