Picture composition method, electronic equipment thereof and computer readable storage medium
A composition and image technology, applied in the field of image processing, can solve the problems of small selection range of cropping, inability to obtain the best composition, unsatisfactory composition effect, etc., and achieve the effect of avoiding poor composition
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Embodiment 1
[0070] Such as figure 2 As shown, the camera photo contains a clear subject, and the composition method of the present invention specifically includes the following steps:
[0071] Statistical composition rules, specifically:
[0072] Step S1, the photographs obtained from social media and photographic works websites whose number of users’ likes exceeds the preset first threshold are used as reference pictures, where the first threshold refers to preset parameters, and when the number of likes of the photograph exceeds This parameter is later defined as a photo with a higher number of likes (that is, an excellent photo), and this photo is used as a reference photo. The photos screened here are photos containing clear subjects, that is, photos containing subjects such as people and animals.
[0073] Step S2, using a convolutional neural network to learn and train the photos containing a clear subject, and establish a subject judgment and recognition model, specifically includ...
Embodiment 2
[0088] Such as image 3 As shown, the camera photo does not contain a clear subject, and the composition method of the present invention specifically includes the following steps, in order:
[0089] Statistical composition rules, specifically:
[0090] Step S1, the photographs obtained from social media and photographic works websites whose number of users’ likes exceeds the preset first threshold are used as reference pictures, where the first threshold refers to preset parameters, and when the number of likes of the photograph exceeds This parameter is defined as a photo with a high number of likes, and this photo is used as a reference photo. The photos screened here are photos that do not contain clear main photos, that is, photos that include the sky, mountains, lake scenery, etc.
[0091] Step S4. Use a clustering algorithm to perform color clustering on photos that do not contain clear subjects, and obtain statistical laws of spatial distribution that do not contain cl...
Embodiment 3
[0099] Embodiment three: as figure 1 As shown, the preferred embodiment of this embodiment is a combination of the above embodiments, specifically including the following steps:
[0100] Step S1, taking photos obtained from social media and photographic works websites whose number of likes exceeds the preset first threshold as reference pictures, where the first threshold refers to the preset parameters, the number of likes in the photographed photos After this parameter is exceeded, it is defined as a photo with a high number of likes, and this photo is used as a reference photo. The photos screened here include photos that contain a clear subject and photos that do not contain a clear subject. Photos that contain a clear subject are those that contain people and animals. Photos with subjects such as the sky, mountains, lakes, etc. that do not contain clear subjects.
[0101] Step S2, using the convolutional neural network to learn and train the photo containing a clear subj...
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