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Fall-detection(摔倒/跌倒检测)

Fall-detection(摔倒/跌倒检测)in the room

this fall-detection is based on darknet.

Examples

  we first detect humans in the room, then we use some simple ways to judge whether he or she is falling down. fall detection example

fall-detection algorithms

  • detect human
  • classify whether fall down or not(still on the way)/custom rules

Installation

Requirements

  • Python and opencv,
  • Linux (Windows and Mac os are not officially supported, but should work)

Installation Options:

Install on Linux

First, make sure you have install python and opencv environment(p.s. if you do not have GPU support, change the first line and second line of Makefile value from 1 to 0)

Then, install this module :

git clone https://github.com/qiaoguan/Fall-detection
cd Fall-detection
sudo make

If you are having trouble with installation, you can Issue me!

run the demo

First, download yolo.weights, the password is: bp6c. Then, install this module :

python gq.py

for opencv3 users, you can refer to this code

the speed is about 12fps using GPU(GTX 1080)

Thanks

  • Many, many thanks to pjreddie for his Great work!

p.s. If libdarknet.so Error happened, you can alter the relative path for libdarknet.so in python/darknet.py to absolute path, if you have any questions,you can open an issue!

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