JeVoisBase  1.18
JeVois Smart Embedded Machine Vision Toolkit Base Modules
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def demo.str2bool (v)
def demo.visualize (image, results, box_color=(0, 255, 0), text_color=(0, 0, 255), fps=None)


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 (')
 demo.args = parser.parse_args()
 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) = cv.TickMeter()
 demo.frame = visualize(frame, results, fps=tm.getFPS())