A Portrait Style Transfer Method Based on Semantic Segmentation and Deep Convolutional Neural Network
A technology of semantic segmentation and deep convolution, applied in the field of deep learning, can solve problems such as unsatisfactory migration effect, unsatisfactory effect, large randomness of images, etc.
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[0056] see figure 1 and figure 2 , are respectively the system flowchart and the model architecture diagram of the present invention, see Figure 4 , this embodiment selects an artistic image as the style portrait Choose another image as content portrait like image 3 shown. where w c , h c are the length and width of the content portrait image respectively, w s , h s are the length and width of the content portrait image respectively; then use the semantic-based image segmentation algorithm to semantically segment the style portrait and content portrait:
[0057] Step 1. Select the CRF as RNN model developed by Oxford University as the model for the semantic segmentation of the image portrait area, perform semantic segmentation on the content image and style image respectively, and segment the portrait area and background area,
[0058] Step 2. Use the OpenFace face area segmentation algorithm, and then calibrate the face, nose, eyes, mouth, and body areas in the ...
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