数据集——个人收集的目标检测数据集待续更新

1、鸟类检测

鸟类识别目标检测，只有bird一个类别，标注格式xml和txt两种，标注工具是labelImg,数据数量4849张，可用于yolo目标检测。
xml格式如下：

<annotation>
	<folder>bird1</folder>
	<filename>捕食的鸟_0.jpg</filename>
	<path>bird\捕食的鸟_0.jpg</path>
	<source>
		<database>Unknown</database>
	</source>
	<size>
		<width>1080</width>
		<height>1424</height>
		<depth>3</depth>
	</size>
	<segmented>0</segmented>
	<object>
		<name>bird</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>397</xmin>
			<ymin>105</ymin>
			<xmax>871</xmax>
			<ymax>988</ymax>
		</bndbox>
	</object>
</annotation>

txt格式如下：

0 0.0693815987933635 0.3286445012787724 0.1297134238310709 0.18670076726342713
0 0.2450980392156863 0.592071611253197 0.1493212669683258 0.2225063938618926
0 0.11463046757164405 0.7161125319693096 0.1568627450980392 0.2915601023017903
0 0.07390648567119155 0.9079283887468031 0.10256410256410257 0.1790281329923274
0 0.40950226244343896 0.8542199488491049 0.15837104072398192 0.1534526854219949
0 0.5105580693815989 0.3900255754475704 0.16742081447963802 0.16112531969309465
0 0.7420814479638009 0.6662404092071612 0.18401206636500755 0.28900255754475707
0 0.9539969834087482 0.5549872122762148 0.07692307692307693 0.19437340153452687

数据集下载地址：https://download.csdn.net/download/matt45m/90358867?spm=1001.2014.3001.5503

2、 无人机目标检测

无人机目标检测，只有无人机一个类别，标注格式xml，标注工具是labelImg,数据数量1097张，可以使用脚本把xml转成txt或者json格式的标签，可用于yolo目标检测。

<annotation>
	<folder>drone _ Google_da Ara</folder>
	<filename>pic_518.png</filename>
	<path>C:\Users\mehdi\Downloads\ss\drone _ Google_da Ara\pic_518.png</path>
	<source>
		<database>Unknown</database>
	</source>
	<size>
		<width>400</width>
		<height>300</height>
		<depth>3</depth>
	</size>
	<segmented>0</segmented>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>64</xmin>
			<ymin>115</ymin>
			<xmax>200</xmax>
			<ymax>172</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>191</xmin>
			<ymin>129</ymin>
			<xmax>283</xmax>
			<ymax>166</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>188</xmin>
			<ymin>178</ymin>
			<xmax>334</xmax>
			<ymax>234</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>130</xmin>
			<ymin>248</ymin>
			<xmax>267</xmax>
			<ymax>292</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>88</xmin>
			<ymin>203</ymin>
			<xmax>170</xmax>
			<ymax>241</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>20</xmin>
			<ymin>193</ymin>
			<xmax>77</xmax>
			<ymax>237</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>1</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>137</xmin>
			<ymin>1</ymin>
			<xmax>288</xmax>
			<ymax>55</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>245</xmin>
			<ymin>105</ymin>
			<xmax>377</xmax>
			<ymax>165</ymax>
		</bndbox>
	</object>
	<object>
		<name>drone</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>319</xmin>
			<ymin>243</ymin>
			<xmax>399</xmax