JeVoisBase
1.22
JeVois Smart Embedded Machine Vision Toolkit Base Modules
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Go to the source code of this file.
Namespaces | |
namespace | demo |
Functions | |
demo.str2bool (v) | |
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] |
str | demo.help_msg_backends = "Choose one of the computation backends: {:d}: OpenCV implementation (default); {:d}: CUDA" |
str | 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._ | |
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()) | |