模型检测

关键参数

weights: 训练好的模型文件

source: 检测的目标，可以是单张图片、文件夹、屏幕或者摄像头等

conf-thres: 置信度闯值，越低框越多，越高框越少

iou-thres: IOU 闻值，越低框越少，越少框越多

torch.hub 检测方法

安装 Jupyter

命令行输入以下代码

python

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pip install -i https://pypi.tuna.tsinghua.edu.cn/simple jupyterlab
conda install ipykernel

激活环境

python

1	python -m ipykernel install --name yolov5

新建 Jupyter 文件

hub_detect.ipynb

python

import torch

#Model
model = torch.hub.load("./","yolov5s",source= "local")

#Images
img = "./data/images/zidane.jpg"

# Inference
results = model(img)

# Results
results.show()

注意运行环境，在下 yolov5

数据集构建

视频放在 data02 文件夹下

抽取视频帧

python

import cv2
import matplotlib.pyplot as plt
#%%
# 打开视频文件
video = cv2.VideoCapture("./BVN.mp4")
# 读取一帧
ret, frame = video.read()

plt.imshow(frame)

plt.imshow(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))

video = cv2.VideoCapture("./BVN.mp4")
num = 0         # 计数器
save_step = 30  # 间隔帧
while True:
    ret, frame = video.read()
    if not ret:
        break
    num += 1
    if num % save_step == 0:
        cv2.imwrite("./images/" + str(num) + ".jpg", frame)

安装标准工具 labelimg

python

1	pip install -i https://pypi.tuna.tsinghua.edu.cn/simple labelimg

使用 labelimg

终端输入 labelimg
打开需要标注的文件夹 images

设置保存路径

点击下图的标志，将保存格式改为 YOLO

开启自动保存

开始标注，鼠标右键点击 Create RectBox

框出两个人物，并命名

切换下一张图片，继续标准（快捷键 A 下一张，D 下一张，W 创建 RectBox）
标准完成后，文件夹内容如图所示

模型训练

调整文件命名

命名严格一致，不能改

文件调整

设置 yaml 文件

复制 coco128.yaml 文件，并命名为 bvn.yaml

修改 bvn.yaml

修改 train.py

文件名改为 bvn

workers 设置为 1

运行 train.py，训练模型

中间肯能需要下载一写东西，比较慢，慢慢等（可以挂个梯子）

报错，查看下面的报错解决

报错解决

页面文件太小，无法完成操作

训练过程中，发生下图所示的报错，同时 pycharm 崩溃

1. 更改虚拟内存

进入高级系统设置，应该都会进，就不说过程了

设置虚拟内存大小

2. 减小占用内容大小

新建一个 fixNvPe.py 程序

python

# Simple script to disable ASLR and make .nv_fatb sections read-only
# Requires: pefile  ( python -m pip install pefile )
# Usage:  fixNvPe.py --input path/to/*.dll
 
import argparse
import pefile
import glob
import os
import shutil
 
def main(args):
    failures = []
    for file in glob.glob( args.input, recursive=args.recursive ):
        print(f"\n---\nChecking {file}...")
        pe = pefile.PE(file, fast_load=True)
        nvbSect = [ section for section in pe.sections if section.Name.decode().startswith(".nv_fatb")]
        if len(nvbSect) == 1:
            sect = nvbSect[0]
            size = sect.Misc_VirtualSize
            aslr = pe.OPTIONAL_HEADER.IMAGE_DLLCHARACTERISTICS_DYNAMIC_BASE
            writable = 0 != ( sect.Characteristics & pefile.SECTION_CHARACTERISTICS['IMAGE_SCN_MEM_WRITE'] )
            print(f"Found NV FatBin! Size: {size/1024/1024:0.2f}MB  ASLR: {aslr}  Writable: {writable}")
            if (writable or aslr) and size > 0:
                print("- Modifying DLL")
                if args.backup:
                    bakFile = f"{file}_bak"
                    print(f"- Backing up [{file}] -> [{bakFile}]")
                    if os.path.exists( bakFile ):
                        print( f"- Warning: Backup file already exists ({bakFile}), not modifying file! Delete the 'bak' to allow modification")
                        failures.append( file )
                        continue
                    try:
                        shutil.copy2( file, bakFile)
                    except Exception as e:
                        print( f"- Failed to create backup! [{str(e)}], not modifying file!")
                        failures.append( file )
                        continue
                # Disable ASLR for DLL, and disable writing for section
                pe.OPTIONAL_HEADER.DllCharacteristics &= ~pefile.DLL_CHARACTERISTICS['IMAGE_DLLCHARACTERISTICS_DYNAMIC_BASE']
                sect.Characteristics = sect.Characteristics & ~pefile.SECTION_CHARACTERISTICS['IMAGE_SCN_MEM_WRITE']
                try:
                    newFile = f"{file}_mod"
                    print( f"- Writing modified DLL to [{newFile}]")
                    pe.write( newFile )
                    pe.close()
                    print( f"- Moving modified DLL to [{file}]")
                    os.remove( file )
                    shutil.move( newFile, file )
                except Exception as e:
                    print( f"- Failed to write modified DLL! [{str(e)}]")
                    failures.append( file )
                    continue
 
    print("\n\nDone!")
    if len(failures) > 0:
        print("***WARNING**** These files needed modification but failed: ")
        for failure in failures:
            print( f" - {failure}")
 
 
 
 
 
 
 
def parseArgs():
    parser = argparse.ArgumentParser( description="Disable ASLR and make .nv_fatb sections read-only", formatter_class=argparse.ArgumentDefaultsHelpFormatter )
    parser.add_argument('--input', help="Glob to parse", default="*.dll")
    parser.add_argument('--backup', help="Backup modified files", default=True, required=False)
    parser.add_argument('--recursive', '-r', default=False, action='store_true', help="Recurse into subdirectories")
 
    return parser.parse_args()
 
 
###############################
# program entry point
#
if __name__ == "__main__":
    args = parseArgs()
    main( args )