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关键参数与规格
关键参数与规格
参数
值
语言
Python
类别
Applications
子类别
Object detection
星标数
769
分叉数
258
贡献者
4
创建日期
2017-09-12
更新日期
2026-10-12
1 天星标数
0
7 天星标数
-2
排名
14,023
上次排名
13,898
排名变化
-125
7 天星标排名
18,432
上次 7 天星标排名
18,366
7 天星标排名变化
-66
总星标排名
13,794
上次总星标排名
13,771
总星标排名变化
-23
国家
China
README 摘录
Tensorflow Face Detector A mobilenet SSD(single shot multibox detector) based face detector with pretrained model provided, powered by tensorflow object detection api, trained by WIDERFACE dataset. Features Speed, run 60fps on a nvidia GTX1080 GPU. Memory, requires less than 364Mb GPU memory for single inference. Robust, adapt to different poses, this feature is credit to WIDERFACE dataset, I manually cleaned the dataset to balance the precision and recall trade off. Parallel, multiple process video processing, can inference multiple input
simultaneously, I tested to process 4 videos on a single GPU card at the same time, the speed is still competitive, and there's still room to accommodate more processes. 2 Tensorflow object detection api (Please follow the official installation instruction, otherwise, I cannot guarantee that you can run the code) OpenCV python Usage Effect Click Youtube to view the effect or Youku. Prepare pre-trained model Click here to download the pre-trained model from google drive. Prepare video Put
your test video (mp4 format) under the media folder, rename it as test. Run video detection At the source root After finished the processing, find the output video at media folder. Run detection from usb camera You can see how this face detection works with your web camera. Here is an example to use usb camera with cameraID=0. Known Issue Please view that issue here if your output video is blank. A brief reminder is: check the input codec
and check the input/output resolution, since this part is irrelevant to the algorithm, no modification will be made to master branch. Further The model released by this repo. has already been merged into Deep Video Analytics / Visual Data Network. Please click the following link for more applications. [1] [2] License Usage of the code and model by yeephycho is under the license of Apache 2. The code is based on GOOGLE tensorflow object detection api. Please refer to the
license of tensorflow. Please refer to the license to the WIDERFACE license.
A mobilenet SSD(single shot multibox detector) based face detector with pretrained model provided, powered by tensorflow object detection api, trained by WIDERFACE dataset.
Features
Speed, run 60fps on a nvidia GTX1080 GPU.
Memory, requires less than 364Mb GPU memory for single inference.
Robust, adapt to different poses, this feature is credit to WIDERFACE dataset, I manually cleaned the dataset to balance the precision and recall trade off.
Parallel, multiple process video processing, can inference multiple input simultaneously, I tested to process 4 videos on a single GPU card at the same time, the speed is still competitive, and there's still room to accommodate more processes.
Dependencies
Tensorflow > 1.2
Tensorflow object detection api (Please follow the official installation instruction, otherwise, I cannot guarantee that you can run the code)
Here is an example to use usb camera with cameraID=0.
python inference_usbCam_face.py 0
Note: this script does not save video.
Known Issue
Please view that issue here if your output video is blank. A brief reminder is: check the input codec and check the input/output resolution, since this part is irrelevant to the algorithm, no modification will be made to master branch.
Further
The model released by this repo. has already been merged into Deep Video Analytics / Visual Data Network.
Please click the following link for more applications.
