Face detection method and device and equipment and computer readable storage medium
A face detection and detection algorithm technology, applied in the field of face recognition, can solve problems such as difficult to solve real-time problems, and achieve the effects of improving detection speed and accuracy, small memory footprint, and high real-time performance
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Embodiment 1
[0050] refer to figure 1 As shown, it is a schematic flowchart of a face detection method provided by an embodiment of the present invention. The method may be performed by a device, and the device may be implemented by software and / or hardware.
[0051] In this embodiment, the face detection method includes:
[0052] Step S1: Collect sample images of human head pictures in real time, and train the sample images based on the target object detection algorithm yolov3 to obtain a trained human head detection network model;
[0053]Specifically include the following steps:
[0054] 1) Create sample sets and label files
[0055] 1.1) Sample collection: Preprocess the collected sample images and make a pedestrian sample set;
[0056] 1.2) Convert the size of the collected sample image to 2048×2048, and randomly divide the sample set formed by the sample image into a training set and a verification set according to a certain ratio;
[0057] 1.3) Obtain the head labeling informat...
Embodiment 2
[0092] This embodiment is basically the same as the first embodiment, a face detection method, characterized in that the method comprises the following steps:
[0093] Step S1: Real-time head detection based on the target object detection algorithm YOLOv3 to obtain a head picture;
[0094] Step S2: Use the trained YOLOv3 network model to detect the head, obtain the head bounding box information, and intercept the bounding box where the head is located on the head picture through the head bounding box information to obtain a sub-image;
[0095] Step S3: performing skin color clustering on the sub-images, and extracting head features;
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