JeVoisBase  1.18
JeVois Smart Embedded Machine Vision Toolkit Base Modules
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demo.py File Reference

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Namespaces

 demo
 

Functions

def demo.str2bool (v)
 
def demo.visualize (image, results, box_color=(0, 255, 0), text_color=(0, 0, 255), fps=None)
 

Variables

list demo.backends = [cv.dnn.DNN_BACKEND_OPENCV, cv.dnn.DNN_BACKEND_CUDA]
 
list demo.targets = [cv.dnn.DNN_TARGET_CPU, cv.dnn.DNN_TARGET_CUDA, cv.dnn.DNN_TARGET_CUDA_FP16]
 
string demo.help_msg_backends = "Choose one of the computation backends: {:d}: OpenCV implementation (default); {:d}: CUDA"
 
string demo.help_msg_targets = "Chose one of the target computation devices: {:d}: CPU (default); {:d}: CUDA; {:d}: CUDA fp16"
 
 demo.parser = argparse.ArgumentParser(description='YuNet: A Fast and Accurate CNN-based Face Detector (https://github.com/ShiqiYu/libfacedetection).')
 
 demo.type
 
 demo.str
 
 demo.help
 
 demo.default
 
 demo.int
 
 demo.float
 
 demo.False
 
 demo.str2bool
 
 demo.True
 
 demo.args = parser.parse_args()
 
 demo.model
 
 demo.image = cv.imread(args.input)
 
 demo.h = int(cap.get(cv.CAP_PROP_FRAME_HEIGHT))
 
 demo.w = int(cap.get(cv.CAP_PROP_FRAME_WIDTH))
 
 demo.results = model.infer(image)
 
int demo.deviceId = 0
 
 demo.cap = cv.VideoCapture(deviceId)
 
 demo.tm = cv.TickMeter()
 
 demo.hasFrame
 
 demo.frame = visualize(frame, results, fps=tm.getFPS())