rendi.eka.putra/People-Counting-in-Real-Time
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update requirements

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SSUBHAKA 2022-07-22 13:18:35 +02:00
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6
README.md
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@ -40,16 +40,16 @@ People Counting in Real-Time using live video stream/IP camera in OpenCV.
- Then an unique ID is assigned to every particular object deteced, for tracking over the sequence of frames. - Then an unique ID is assigned to every particular object deteced, for tracking over the sequence of frames.
## Running Inference ## Running Inference
- Install all the required Python dependencies: - First up, install all the required Python dependencies:
``` ```
pip install -r requirements.txt pip install -r requirements.txt
``` ```
> The requirements will be updated timely, but note that there can always be verion conflicts between the dependenceies themselves and other factors like OS, hardware etc.
- To run inference on a test video file, head into the directory/use the command: - To run inference on a test video file, head into the directory/use the command:
``` ```
python run.py --prototxt mobilenet_ssd/MobileNetSSD_deploy.prototxt --model mobilenet_ssd/MobileNetSSD_deploy.caffemodel --input videos/example_01.mp4 python run.py --prototxt mobilenet_ssd/MobileNetSSD_deploy.prototxt --model mobilenet_ssd/MobileNetSSD_deploy.caffemodel --input videos/example_01.mp4
``` ```
> To run inference on an IP camera: - To run inference on an IP camera, first setup your camera url in 'mylib/config.py':
- Setup your camera url in 'mylib/config.py':
``` ```
# Enter the ip camera url (e.g., url = 'http://191.138.0.100:8040/video') # Enter the ip camera url (e.g., url = 'http://191.138.0.100:8040/video')

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requirements.txt
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@ -1,7 +1,8 @@
schedule==0.6.0 schedule==1.1.0
numpy==1.19.2 numpy==1.22.3
argparse==1.4.0 argparse==1.4.0
imutils==0.5.3 imutils==0.5.4
dlib==19.18.0 dlib==19.18.0
opencv-python==4.2.0.32 opencv-python==4.5.5.64
scipy==1.4.1 scipy==1.8.0
cmake==3.22.5